diff --git a/challenges/PIQUE challenge/QuantumVoyagers/README.md b/challenges/PIQUE challenge/QuantumVoyagers/README.md
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+# Quantum Algorithms for Tic Tac Toe
+
+This repository contains Python code and Jupyter Notebooks implementing quantum algorithms, specifically Grover's algorithm and Quantum Approximate Optimization Algorithm (QAOA), to solve the Tic Tac Toe game.
+
+## Table of Contents
+
+- [Grover's Algorithm](#grovers-algorithm)
+
+  - [General Solution](./app/grover/general_solution.ipynb)
+  - [Grover Circuit Complete Image](./app/grover/grover_circuit_complete_image)
+  - [Solution Notebook](./app/grover/solution.ipynb)
+
+- [QAOA](./app/qaoa/qaoa.ipynb)
+
+- [Images](./app/Images)
+
+  - [Best Play - Regular](./app/Images/best_play.png)
+  - [Best Play - Bonus](./app/Images/best_play_bonus.png)
+  - [Parts Oracle Grover](./app/Images/parts_oracle_grover.jpg)
+  - [Tic Tac Toe Image](./app/Images/tic-tac-toe-1777880_1280.jpg)
+
+- [Package](./pkg)
+  - [General Utilities](./pkg/general_utils.py)
+  - [Quantum Utilities](./pkg/quantum_utils.py)
+
+## Grover's Algorithm
+
+### General Solution
+
+The [General Solution](./app/grover/general_solution.ipynb) notebook contains the Python code for Grover's algorithm, focusing on solving Tic Tac Toe.
+
+### Grover Circuit Complete Image
+
+The [Grover Circuit Complete Image](./app/grover/grover_circuit_complete_image) directory includes the LaTeX file (`file.tex`) and the complete Grover circuit in PDF format (`grover_circuit.pdf`).
+
+### Solution Notebook
+
+The [Solution Notebook](./app/grover/solution.ipynb) provides detailed information on the solution implemented using Grover's algorithm.
+
+## QAOA
+
+The [QAOA Notebook](./app/qaoa/qaoa.ipynb) contains the Python code for Quantum Approximate Optimization Algorithm applied to Tic Tac Toe.
+
+## Images
+
+Various images related to Tic Tac Toe and the algorithms used, such as best plays and the Tic Tac Toe game itself.
+
+## Package
+
+### General Utilities
+
+The [General Utilities](./pkg/general_utils.py) module includes Python functions used for Tic Tac Toe and algorithm implementations.
+
+### Quantum Utilities
+
+The [Quantum Utilities](./pkg/quantum_utils.py) module contains Python functions specific to quantum operations in the Tic Tac Toe algorithms.
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diff --git a/challenges/PIQUE challenge/QuantumVoyagers/app/grover/general_solution.ipynb b/challenges/PIQUE challenge/QuantumVoyagers/app/grover/general_solution.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qiskit.visualization import plot_histogram\n",
+    "\n",
+    "import sys\n",
+    "sys.path.append('../../')\n",
+    "from pkg.general_utils import display_board, generate_random_board, complete_lists_with_dictionary, filter_values_above_average\n",
+    "from pkg.quantum_utils import grover_algorithm, circuit_execute"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[['O', 'X', ' '], [' ', ' ', 'O'], [' ', ' ', 'X']]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "challenge = generate_random_board(num_moves=4)\n",
+    "challenge"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "O | X |  \n",
+      "---------\n",
+      "  |   | O\n",
+      "---------\n",
+      "  |   | X\n",
+      "---------\n"
+     ]
+    }
+   ],
+   "source": [
+    "display_board(challenge)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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3Px7bvTP58f9MWkfXc+DoE5MZr6m/Hs1i7+5kw4pkwy/qOXDghwJ270h+8FfJ+KOSyTPq45/8quapg7Vafe4//bNky9PJ9s37P757Z3Lf3yZjxiWTpiXHnpIcNy8ZNaaaeIdCT3fy9GPJplVJ14aXNsN270ju/kK99k05PpmxsD4fml0pa6FDKX38IAcAdQBQB6D5aJBB6m8Ir3kg6Xgk2dWH33E7tta/NqxIxh2ZnPD6+huELSP4nMxNv0xW/TjZ+vQrb7unp35W0XNPJSv/rd4ke/UbR3aTYGdX8st/rzdHX+nMiFqtfkbFtk1Jx8PJkTOTE9+QHD27IaEOiVpvff6v/Wl9br+Snm31JuLGlcnY9mTm4uSEM5JRI/i3ytbO+hx4tg8fBOvdU8+VrU8nq36UHDu3ngPtRw99nENl985k9Y+TdT9P9ux85e23P1f/6vx5vVFywhn1hulIbZTVavWm4OqfJNueeeXtd++oN5OfXZ088YP6ByZOPGtkf2Bg+3PJk/clzzxerwkvp9Zbb551baj//jx6dnLiG5MjX9WQUAEAAAAO2wh+KxMGx5Z1ybLv1N8YHIgdW5IV30s6lycLzht5n6LfvTN5/K6kc9nA9u/dUz/bZsPjySm/MfLeIK/V6meMPX73wC8bt6UjeXhJ/Q3yk8+tn2E3knQ/W8+BrZ0D239Xd/LL+5INy5NTz08mTx/c+Iba3j31+Nc8mP3OmOyrWm+9sbJxZTLnnOT400des3zTqmT5d+uNz4HYtjFZ+u16g3n+25O2iYMb31Dr2ZYs/9dk05MD239PT725vOEXyfy3JVPnDG58Q63Wm6x9KHny3oFfOvGFZuHxr0/mnN1cZ9QBAAAAzWmEvYUHg6dWS1bfnzx408CbYy+2dV390msbVhz+czVK1zPJj28YeHPsxfbsrL9B/vM7Rs69afbuSR77Vr05NBj3VHr658mPbqg3C0aK9cuT+/9h4M2xF+venDzwtfrZJCPFzueTn/zjr2I+zHtK9e5Nnvhh8tOv1xvPI0GtVm8OP3LLwJtjL/bsqnpNeXbN4T9Xo2xeW8/bgTbHXqxnW/LIPyW/+P7IuUfZnp7koSX1s+AGo3avfbCeU305ExUAAACgShpk9MmMGTNy7bXXZsaMGVWHMmievDdZec/gPmfvnuSx25Onlw7u8w6F59cnP715cN4Uf7ENK5JHvzn8m2R79ySP/lP9UmKDqacrefDm+r2bhrt1j/2qobn3lbfts1q9SfTLfx/E5xwiO7bWG+Tdzw7u827pqOfWgffuGm5qtfpZY2t/OrjPu6cneeTW+mVbh7tnV9dj7cslJfvjqYeTpXcO/ybZ7p31hu5zawf3ebs3Jw/+3/X7+TWTZlwL9Ufp4wc5AKgDgDoAzaelVhvub9+Up7u7OxMm1G/mtG3btrS3tw/6MVasGPrTnObNmzfkxxioNQ/WPy0/ZFqSxe8evpfZ2r4leeDGoX0Df9opyWkXDM/LLdZqyc9uSzY+MXTHGDMuOfMPknGTh+4Yh+OZJ5KffXNoj3HKbyazXju0xxio3TuTn/yv+iVSh8rk6cnplySto4buGIfjiR8O7dl+raOT0393+F5y8/n19SbOUDbzZ72ufunZ4ah3b/LQ1+uXGR4q4yYnZ/xBMnbc0B3jcDRiLZQM7/VQ6etBkANQNmsBwFoARq7B6qE4g4w+2bx5c2688cZs3ry56lAOW9fGZOW/9W+fM/8gOec/17/3SS1Z9t1k1/Z+hzfkarVk2Z39a471e/yp34tnMC7dOBSefqz/zbH+vga7d9Qv3TgcP4LQ050s/5f+7TOQOfDEDwb/7KzB8vhd/WuODWT8WzuTVT/qd2gNsXlt/5tj/X0NevfUL7u6d3f/4xtqe/ckP/92/5pjA5kDTz1UP0ttOFr9k/43x/r7GuzYWr/cZLNoprXQQJQ+fpADgDoAqAPQfIpskG3atClXX311TjrppLS1tWXWrFm58sor093dncsvvzwtLS25/vrrqw5zWOns7MxnPvOZdHYOwo2KKtS791dNi97+7Te2PWmbWP/eV7u2J7+4q3/HaYSnHur/m6IDGX9Sb0IM9iUcD9fO55PHf9D//QbyGjz3VLLu0f4fayjVasmK7/X/7MGBjL93b7J0APk21DY+2f/m7UBzYPX9w+9ym3t21etgfw3kNdj+XP1ytsPNL+9Ltvfz/zMDnQPLvjs49zgcTF0bB9a8HchrsGFF/YzVZtAsa6GBKn38IAcAdQBQB6D5FNcge+SRR/Ka17wm//W//tesX78+p556anbv3p0vfOEL+d3f/d0sX748SbJ48eJqA2VIdC5Nuhr4ZvWGFUN7+ar+2r2zsW9W7+kZfm+Or7w32burccd74t/qDYnh4rmnhvbSkgd6vnN4nUlY6603bht2vFry+N2NO15frH2w3ihu2PF+Wm+UDRc7ttYvs9soPV3J6iG8lOVAPPGDxjauH78r6R1mjXIAAACAohpkmzZtyoUXXpj169fnYx/7WDo7O/PQQw9l/fr1ufbaa3PHHXfkgQceSEtLSxYuXFh1uAyyWi156uHGH7fjkcYf81A6lzX+cmfrV9Qbc8PBru31Sz820t5dyfph1CDqKDwHnl1db5A00paOZNvGxh7zUHr3Jut+1vjjdgyjMynXPZqkwZc+ffpn9dd+OOh+Ntm8prHH3NmVbPplY48JAAAA8EqKapBdccUV6ejoyEc/+tF8/vOfz8SJE/c9dvXVV2fRokXZs2dPZs+enUmTJlUYKUNh69PVvEm94RfJru7GH/dAtVo1jYrePcnTP2/8cQ/m6ceSWgVvUnc8MjzuRbazK9m4svHHfX59/Ws4qKpZN1waRBufrOayp0//fHjci6x3T7LuscYfd9f24XOZwarm4nBqlAMAAAAkBTXIli9fnptvvjlTp07NZz/72YNuc/rppydJFi1atO9nS5YsyXve856ccMIJGT9+fObNm5c//dM/zbZt+7/D+ELj7cwzz8wRRxyRlpaWoRtMBdrb23P22Wenvb2fN18ZRqp6c7LWOzw+Od/9bP/vuTNYGnlJv5dT1RzYtinZsaWaY7/Ypiera9QNh+bA3t3Js6uqOfZwGH9SXS7u2Zk811HNsV9sy7r+339vsDzzeDXHPVBVc3Hz6uF1udmBaIa10OEoffwgBwB1AFAHoPmMrjqARrnpppvS29ubSy+9NBMmTDjoNuPGjUuyf4Ps85//fI4//vj85V/+ZWbOnJlHHnkkn/70p/PDH/4w//Zv/5bW1nqPceXKlbnllltyxhlnZOzYsbnvvvuGflANNHv27HzlK1+pOozD0sh7jx3o+Q3Jq15T3fGTasff9Uy9UdhSYUu+d2+1l7l7fkMy/qjqjv9CDFWpcv7ti2FjdQ3CXd31M7eOOPivn4apeg5MPbG64yfVj79qu7bX74lWla4NyVGzqjv+4WqGtdDhKH38IAcAdQBQB6D5FNMgu+uuu5Ik55577iG36eiof7z9xQ2yb33rWznmmGP2/f0tb3lLjjnmmFx66aW599578+Y3vzlJ8uY3vzmdnZ1Jkk996lNN1yDbu3dvduzYkXHjxmXUqFFVh9NvtZo3Rqsc/97dyfbnkvajq4uh+9lq7wHUtSE5bl51x38hhqo8v6Geh1WeXNtV8WUen9+QHFNhg2zPrurOIk2qrUEvqDIHdmyt349xTFt1MVT9b/D8CG+QjfS10OEqffwgBwB1AFAHoPkUc4nFNWvqd6Q/4YQTDvr4nj179jW1Xtwge3Fz7AWvf/3rkyTr1q3b97MXziRrVitWrMgZZ5yRFStWVB3KgOzekeyt8NJO27dUd+wXVH2Jv9KPPyzmwNbqjl11DibJ9grHn1Q/B3cWPv6k+jysMgeT6v8Nqj7+4Rrpa6HDVfr4QQ4A6gCgDkDzKeYMsu7u7iTJjh0Hv/nIzTffnE2bNmXixIk58cSXvwbU3XffnSSZP3/+4AZ5EHPnzh2S5ttll13Wr+1fODvu29/+dh5++OE+7XPDDTf0M6qhc9SE6fkff/TAIR8/8w+SsS9z+eAj2v/j+zn/+dDb7epOfvK/Xvrz57d0ZebMoZ8vL+f/+O2v5bQT3nzQxwZr/MmhX4M/uvw/58GVd/Qx2sH3a6dclD85/4sHfeyVxp8c/hz43r98P+/8yAf6GO3Q+NuPrsyY0Qc/fWWocyBJFr5mcZ7fvqmP0Q6+9537F/nNRQf/N2hEDvzFn382dzx48DnYCCdOW5RP/t7Bc7ARObDy8V/mvTMPXoMa5TN/8L3MnHrwUzkbMQfedcG7s7LzwT5GO/h+67UfzO+95ZMHfawRc+DG/3VT/v6yj/cx2qHXiLVQMrzWQwfqz2vQjOMHOQBlsxYASnt/FJpJb2/vvj+fc845/frd/GLFNMiOO+64PPfcc3nooYdy1lln7fdYZ2dnPv7x+hs2CxcuTMvLXANs3bp1+bM/+7Ocd955Wbx48VCGvC+2obB9+/Z+bb9z58593/u674vPsKva9ol7Xvbxse1J28RXfp6W1r5td6Dde3ZV/nps39F9yMeGevxJ8sym9ZW+BpuOfuaQj/V1/MnAX4Nt3V2Vz4E9e/dkzCGqfiPmQEfH2nTteG5gOw+C57sOffpOI8a/+blNlc6BttpLz4h+QSNyYGfPjspzoGfXzkM+1og5sH7D05W+BptnP3vIxxoxB57v2lL5HHixRqyFkuG1HjpQf8bRjOMHOQBlsxYASnt/FJrVhg0Dv6dEMQ2yt771rVm+fHmuvfbavO1tb8vJJ5+cJHnggQfyvve9L5s21c9qeLmm17Zt23LRRRdl7Nix+epXv9qIsDN9+vQhOYNs/Pjx/dq+ra1t3/e+7jtjxox+xzVUxoxqS2+tN60tB38tdx26d5Sk/mn5ltak1pv0vMy2h3qeHbu7Kn899ubQbwwP1vhf7rna2kdX+hocMf7Q14Z+pfEnhz8Helt6Kp8D23u2ZtwRB78J1lDnwJ69u3PU1Mm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A2Sfss88+SXZukF166aU56KCD8rd/+7eZNm1a7rrrrnzsYx/LT3/60/zsZz9LU5NeJLD3mjFjRr7yla9UHUZlSh7/9sc7s3nT2qrDqFTTwrel+xe3puvLX0nT/b9N/Tf3pumsP09t+rSqQxtSJedBSTrWJW2/7ts699+SHDgzqdUGJyaGh5JrQOnzgHOBHo2WAy9/+ctzySWX7Pj6/PPPz2c/+9l+b2/s2LH50z/904x4UtN49OjRee1rX5vbbrvt2YQKMGw02lwAaJA9xU033ZQkOf744592mdbW1iQ7N8i+//3v58ADD9zx9Stf+coceOCBWbhwYX7+85/veDAtwN6oq6srmzdvzj777LPTD72lKHn8v7z6I/nl1R+pOoxK1UaOzMgL/jLb/+f/Sve116V2+Lw0/ekbqg5ryJWcByVpvbvv63T8IdnQmjxn+sDHw/BRcg0ofR5wLtCjkXJg7Nix+Yd/+IcdX3/4wx9+Vs2xlpaWXH/99Tt+7/HYY49l7NixGTlyZD784Q/nmmuuyT333PNswwaoXCPNBUAPlzXt4oEHHkjS83DZ3dm+fXuWLFmSZOcG2ZObY0948YtfnCRZs2bNQIcJMKRWrFiRY445JitWrKg6lEqUPP7Djz8rb/z//Wi3H0VpaUlGjUqS1I55cWoFXhlech6U5Pf3Du167D2KrwEFzwPOBXo0Ug586EMfysyZM5MkP//5z/N//s//6fe2dm2OrVu3Lq961at2XJ02evTofPnLX372QQMMA400FwA9XEG2i46OjiTJ5s2bd/v6VVddlbVr12b8+PE55JBDnnFbN998c5Jk7ty5/Y5n1qxZw+L2jJ8+87ZMHD8lbW1tmTbtmKrDYYj5/2/M9+CMM87o9bJtbW1Jkuuvv75PzxC44oor+hjV0GnU8Y8YtU/eeNF9A7a9/SbPykGHnzBg29ud2bNmpWvb7ufdvqqPHp1c/sUB2daObdbr6frUZ5Lt25KDpqf7m/+Sple+IrXnTRmQ7c+eNTu1xx8fkG31RV9yIOlfHgznGsDuXf7+ezNm1Ng+r/etK/81l7/rfw5CRAymRp0LB3ou2NvmgdLPBfqiUXOgu7v7aV8bO3Zs3ve+9yVJtmzZkne/+93PuPwz2V1z7IQTTsidd96ZpUuX5g1veEMOO+yw/NEf/VH++I//OL/85S+fdlvD5XcfQFn8TASNYfLkybn99tv7ta4G2S4mT56c9evX54477shxxx2302ttbW254IILkiTz589P7RketLBmzZp86EMfyoknnpijjjqq3/E8UXir9sSDdru6ulwRVyD//435HnR2dvZ62S1btuz43Jf1hvN71ajjHzmm77/YrtrDbQ9n+9bev6/PqHlMRg3Mlnbo/u41qd/9qzT92bvSdNwfZ/v7/2e6PvWZjLj04mc8F+ith9seTrZsHYBI+6Yvx3LSvzwYzjWA3du6bUu/GmQbHlvn/3sv1Khz4UDPBXvbPFD8uUAfNGwOPIPTTz89++23X5KeZ7Dfd1//mqnP1BxLkscffzwXX3xx/vEf/zFJcvbZZz9jg2y4/O4DKIufiQANsl2ccMIJWb58eS6++OK85jWvyezZs5Mkt912W97xjndk7dqehxM/U9Orvb09p556akaPHp2vfe1rzyqeKVOmDIu/onrivrojRozI1KlTK46Goeb/vzHfg7Fje//Lk+bm5h2f+7LecH6vGnX8I0btM+T7fLaeN+V5A3oF2aMDsqX/2t6aNen+2hWpvWB2mt5yWmojRqTp7QvT/Q//mO7vXpMRbzz1We/jeVOeV8kVZH05lpP+5cFwrgHs3iPrV2bfscf2eb2NW9b4/94LNepcOJBzwd44D5R+LtAXjZoD3d3dT9twete73rXj33/3d3/Xr+3vqTn2hG9961v59Kc/nf333z9vectb8t73vvdp79YzXH73AZTFz0TQGCZPntzvdTXIdrFo0aJ885vfzEMPPZR58+Zlzpw52bJlS1auXJmTTjopM2bMyA9/+MOdnj/2ZJs3b86CBQuyatWq3HLLLZky5dndduO+++5LS0vLs9rGQLjl75Ot7T0nra2trVWHwxDz/9+Y70Ff7pm9dOnSfO1rX8vrXve6zJs3r9frXXTRRf0JbUg06vi3bk8uvGrId/us3HvffRkzQGckHV3b85ybBuaZKPXu7nR98tNJd3dGXPCXqf1Xo7zpLaelvuTf0/21K9L0R8c+61ts3XvfvWkZMfSnZH29b35/8mA41wB2r21ZsvT6vq3TNCL5u3/5cEaP/fDgBMWgadS5cKDmgr11Hij9XKAvGjYHOjoybty4p3x/xIgRO56Vfv/99/frVkS9bY4lPVdYfPe7382ZZ56ZMWPG5Mgjj3zaq8iGy+8+gLL4mQjw5zm7mDZtWm655ZacfPLJaW5uzurVqzNx4sRcfvnlue6663LvvT1PIN9dg2zbtm057bTTcvvtt+cHP/hBDjvssKEOH2BQzJ49O0uWLNlxVW1pSh9/qboXfyf1ZcvT9K63p3bQQTu+XxsxIiP+6i+T7q50feozqdfrFUY5dORBGZ47Oxndx7uzTZrT93XY+5RYA8wDPFkj5MCcOXN2XPEw2M2xJzx5P0cffXSf9wkwnDTCXADsTINsN+bOnZtrr702mzZtyqZNm3LrrbfmrLPOSkdHR1avXp2mpqYcfvjhO63T3d2dhQsX5sc//nG+973v5dhj+35rGoDhatSoUZk4cWJGjRropzvtHUoff4nqDz6Y7n/8p9TmzknTm/70Ka/XZhycprcvTP2eX6f7u9dUEOHQkwdlGDEyOWJBUhvRu+VbJiazjx/cmBgeSqsB5gF21Qg58OTfYzxTU2t3+tMc23U/RxxxRJ/2CTDcNMJcAOxMg6wPli5dmnq9nlmzZj3lPrPvf//78+1vfzvnn39+xo4dm1/+8pc7Ph59dCCfhgIw9B588MGcffbZefDBB6sOpRIljn/aYa/Kef9cz9En/9XTLnPeP9dz6l9dO4RRDZ3aQQdl1HXfy8jPfXrHLbV2NeJtb82of7t+QJ4/szcoMQ9K9ZzpyQvflIwc88zL7Ts5edFbk1HNQxMX1SqtBpgHnAvsqhFy4Mm3XezL7yn62xzbdT+7u+0jwN6kEeYCYGcaZH1wzz33JNn97RV/8IMfJEk+8YlP5Ljjjtvp47rrrhvSOAEG2qZNm3LzzTdn06ZNVYdSidLHD4k8KM3Eg5KXnZW84E+Slv13fu2A5ydH/WlyzMJkjMfFFEMNoHSNkANf/epXM2rUqIwfPz7//M//3Ov1Ro8evaO51ZfmWJKsXr06++23X8aMGZO3v/3t/YobYLhohLkA2FkFj8Hdez1Tg2z16tVDHA0AAAyekWOS6S/s+fjZ/00e70hGt/Q0xwDYO23fvj3t7e19Wmf9+vU54YQT8q1vfSuLFi3q0+0Zu7u7s3Hjxr6GCQAwJDTI+uCZGmQAANCoarWdPwNQlvXr1+c1r3lN1WEAAAwoDbI+uOmmm6oOAQAAAAAAgGfJM8gA2KNJkyblwgsvzKRJk6oOpRKljx8SeQClUwMonRwAwFwAjccVZADs0QEHHJAzzjij6jAqU/r4IZEHUDo1gNLJAQDMBdB4XEEGwB5t3LgxN9xwQ7EP2C59/JDIAyidGkDp5AAA5gJoPBpkAOxRa2trzj///LS2tlYdSiVKHz8k8gBKpwZQOjkAgLkAGo8GGQAAAAAAAEXRIAMAAAAAAKAoGmQAAAAAAAAURYMMgD1qbm7O3Llz09zcXHUolSh9/JDIAyidGkDp5AAA5gJoPCOrDgCA4W/mzJn5zne+U3UYlSl9/JDIAyidGkDp5AAA5gJoPK4gAwAAAAAAoCgaZADs0bJlyzJ//vwsW7as6lAqUfr4IZEHUDo1gNLJAQDMBdB4NMgA2KN6vZ5t27alXq9XHUolSh8/JPIASqcGUDo5AIC5ABqPZ5ABQAMZPSK5+K1VR9E3o0cM3LbGNo3I+le/ZuA2OATGNg3gGwDAXjcXDPQ8UPq5AMnYsWPT3t4+YNv75OX/ksc6OrNvy9hc8N7Tn/L1QBg7duyAbAcAoC80yACggdRqyZiCZ/darZaWEQW/AQAUPxeUfi7Af+VAS8uAbW/0mOaM3taV0WOa09LS8pSvAQD2Vm6xCAAAAAAAQFH8XRkAezRz5sxcc801mT59etWhVKL08UMiD6B0agClkwMAmAug8WiQAbBHzc3NmTVrVtVhVKb08UMiD6B0agClkwMAmAug8bjFIgB7tGbNmnzwgx/MmjVrqg6lEqWPHxJ5AKVTAyidHADAXACNR4MMgD3asGFDrr766mzYsKHqUCpR+vghkQdQOjWA0skBAMwF0Hg0yAAAAAAAACiKBhkAAAAAAABF0SADAAAAAACgKBpkAOxRU1NTjjnmmDQ1lTltlD5+SOQBlE4NoHRyAABzATQe2QzAHnV3d+e2225Ld3d31aFUovTxQyIPoHRqAKWTAwCYC6DxaJABAAAAAABQFA0yAAAAAAAAiqJBBgAAAAAAQFE0yADYowkTJmTBggWZMGFC1aFUovTxQyIPoHRqAKWTAwCYC6DxjKw6AACGv2nTpuWSSy6pOozKlD5+SOQBlE4NoHRyAABzATQeV5ABsEdbt27NAw88kK1bt1YdSiVKHz8k8gBKpwZQOjkAgLkAGo8GGQB7tHLlypx44olZuXJl1aFUovTxQyIPoHRqAKWTAwCYC6DxuMUiADSQej15vKvqKPpm9IikVhuYbdXr9XR2711vwNimEakN1BsAwF43Fwz0PFD6uQDU6/V0dnZWHUafjB071vkgAFRAgwwAGsjjXcmFV1UdRd9c/NZkzACdkXR2d+U5N/1oYDY2RNa/+jVpGeGUDGCg7G1zwUDPA6WfC0BnZ2fGjRtXdRh90t7enpaWlqrDAIDiuMUiAAAAAAAARdEgAwAAAAAAoChuYgDAHs2bNy/Lly+vOozKlD5+SOQBlE4NoHRyAABzATQeV5ABAAAAAABQFA0yAPZo1apVOf3007Nq1aqqQ6lE6eOHRB5A6dQASicHADAXQOPRIANgjzo7O3P33Xens7Oz6lAqUfr4IZEHUDo1gNLJAQDMBdB4NMgAAAAAAAAoigYZAAAAAAAARdEgAwAAAAAAoCgaZADs0dSpU3PxxRdn6tSpVYdSidLHD4k8gNKpAZRODgBgLoDGM7LqAAAY/vbbb7+8/vWvrzqMypQ+fkjkAZRODaB0coBnY5999snmzZurDgN4lswF0HhcQQbAHq1bty7f+MY3sm7duqpDqUTp44dEHkDp1ABKJwfKM3LkyBx55JF597vfnU996lO5/PLL86UvfSmf/vSnc+aZZ+aoo47KqFGj9ridWbNmZcWKFVm4cOEQRA0MJnMBNB5XkAGwR21tbbnoooty1FFHZeLEiVWHM+RKHz8k8gBKpwZQOjlQjhe+8IU5++yz87a3vS0tLS3PuGxnZ2euvPLK/N3f/V3uuOOOp7w+a9as3HzzzZk6dWr+8R//MY899li+//3vD1bowCAzF0DjcQXZM1i7dm0WLVqUQw89NM3NzZk+fXrOO++8dHR05Mwzz0ytVstll11WdZgMsm1bko4/JJ3rk+2PVx0NVdjannR39/y7Xq82Fhgqrct+ks+9vZb/vO7Sp13mc2+v5XuXnjKEUQ2trq9dkW2vfV26b/i3p7xWr9ez/a8uzLaTX5/6qtVDHxwMoe6upP7EPNhtLqQcpc8DzgUozZw5c/LTn/40d9xxR/78z/98j82xJBk7dmzOPPPM/Od//md+9rOfZe7cuTtee3JzLEl+/etf59///d8HLX4AoO9cQfY07rrrrpx00kl55JFH0tLSksMOOywPP/xwPv/5z+f+++/fcSntUUcdVW2gDIp6PfnD6qT1rmTt/f/9/aYRyaQ5ybSjkglTKgqOIdG1Lfndip5j4LHf/ff3H+9IVv4smXpkss+EysIDhkDTOxam+5e3puvyL6d29ItSO/CAHa91f+e7qf/qnjS9+4zUDplRXZAwiLY8lrTenTx8T/J4Z8/3Hu9M/uOfkmkvTCbPSUbs+c5SsNcyD0AZRowYkQ984AP52Mc+lubm5h3f37hxY66//vrcdtttufPOO7N27dokyQEHHJAXvvCFefGLX5yTTz45Eyb0/GD48pe/PHfeeWc+8pGP5Hvf+15uvPHGHc2xu+++O3/yJ3+SP/zhD0M/QADgaWmQ7cbatWuzYMGCPPLII/nABz6Qj3zkIxk/fnyS5JJLLsmFF16YkSNHplarZf78+RVHy0Dr2pbcc+3OjbEndHclbUt7PqYfncx+VVKrDXmIDLLNG5I7v5N0Ps0tpVf/R/LA7cm8k5LJc3e/DLD3q40alZEXfCDbzz0/XZ/+bEZ+/KIkSf2h1nRf8fXU5rwgTW9+U8VRwuD43Ypk6Q96zn12ten3yfIfJg/8R3LUnyZjnzP08cFQMA9A4xszZkyuuuqqnHrqqTu+d9999+WTn/xkvvnNb6ajo2O36/3kJz9J0nMF2dve9rZccMEFecELXpAxY8bkE5/4RD7ykY9kn332SaI5BgDDmVss7sa5556b1tbWnHPOObn00kt3NMeSZNGiRTnyyCOzffv2zJgxI/vuu2+FkTLQuruTX31v982xXT30n8m9Nw9+TAytrR3Jf37r6ZtjT6h3J7++Lvndb4Ymrqq1tLTkpS99aa9uM9KISh9/yWqzDk3T6W9J/T/vSPd1P0i9qytdl1ya1OsZccEHUhsxouoQh4w8KMfv7+v5Y6HdNceerHN9z5y5ZdPQxEW1Sq0B5gGeUGoONLJRo0blO9/5zo7mWHd3dz75yU9m/vz5+fKXv/y0zbEn6+zszFe/+tUceeSRufjii9PV1TN5PtEc+9WvfqU5Bg3EXACNxxVku1i+fHmuuuqqHHDAAfn4xz++22WOPvro3H333TnyyCN3fO+WW27Jxz72sSxdujTr1q3LgQcemJe+9KX56Ec/utM9qBneHv5Vz60Ve+uhO5LnzkqeM33QQmKI3Xtzzy2lemvZDcn+M5KRYwYtpGFhxowZ+cpXvlJ1GJUpefzbH+/M5k1rqw6jUk0L35buX9yari9/JU33/zb139ybprP+PLXp06oObUiVnAcl2f54z5VjvbV1U8/cOf/1gxcTw0PJNaD0ecC5QI+Sc6BRfe5zn8vrXve6JEl7e3ve+MY35sYbb+zXtrZu3ZqvfvWrOfPMM3PAAf99O9Y777xTcwwaiLkAGo8G2S6uvPLKdHd3Z+HChRk3btxul3niL4Ge3CBbv359jjjiiLz3ve/Nc5/73LS2tubjH/94jjvuuPz617/OtGll/PC0N6vXk4fu6vt6rXdpkDWKrR3J7+/t2zpd25K2Zcn0Fw5OTMNFV1dXNm/enH322ScjCvxL6ZLH/8urP5JfXv2RqsOoVG3kyIy84C+z/X/+r3Rfe11qh89L05++oeqwhlzJeVCSR5YnXY/3bZ1H70u2tidjdn/qTIMouQaUPg84F+hRcg40ohNOOCF/8Rd/kSTZvHlzXve61+WWW27p9/ZmzZqVm2++eUdzrLu7O01NTXnXu96VK6+8Mj/84Q8HJG6gWuYCaDwaZLu46aabkiTHH3/80y7T2tqaZOcG2etf//q8/vU7/+nsMccckxe84AW5+uqrc9555w1CtAykx9qSjn78YeTv7+t5YP3osQMfE0OrbWnPrRP7as2vGr9BtmLFipx22mlZvHhx5s2bV3U4Q67k8R9+/FmZ9Udv3u1r//qJ1wxxNBVqaUlGjUq2b0/tmBen1lTeXapLzoOSPPyrvq9TrycP/zo55I8HPh6Gj+JrQMHzgHOBHsXnQAMZN25cvvrVr+74+i//8i8HpDk2derUJD3PHLviiivymc98Jkny5S9/OYcffngee6wPtyoBhiVzATQeDbJdPPDAA0mSgw8+eLevb9++PUuWLEmyc4Nsd/bff/8kyciR/X+bZ82alaZh8MPXp8+8LRPHT0lbW1umTTum6nAGxUvmvClnnfi5Pq9X706Of+mJeeDRXw9CVMNDCf//SXLGn1ycVx2xsM/r/eHhzkybNnsQIhpcZ5xxRq+XbWtrS5Jcf/31ufPOO3u93hVXXNHHqIZOo45/xKh98saL7huw7e03eVYOOvyEAdve7syeNStd2zYPyLbqo0cnl39xQLa1Y5v1ero+9Zlk+7bkoOnp/ua/pOmVr0jteVMGZPuzZ81O7fE+XrIzAPqSA0n/8mA41wB27+/+YmnGjpnQ5/WuuPyqfPW0DwxCRAymRp0LB3ou2NvmgdLPBfqiUXNgoL3xz/5XWsbtm7ZH2jJt2rSnfD3cdHc/8189vvvd785BBx2UJPnxj3+cyy+/vN/72l1z7Ilnjp100kl57Wtfm+nTp+fMM8/c0TB7uu0Mh9/9QGn8TASNYfLkybn99tv7ta4G2S6eeAjr5s27Pzm/6qqrsnbt2owfPz6HHHLIU17v6upKd3d3Hnjggfy//+//m8mTJ+ctb3lLv+N5ovBW7YkHzXZ1dWXNmjUVRzM4HpvS/7/mWveH9Q37viRl/P8nyZbNW/u1XlNt5F75vnR2dvZ62S1btuz43Jf1hvP70qjjHzlm77uc9eG2h7N9a+/f12fUPCajBmZLO3R/95rU7/5Vmv7sXWk67o+z/f3/M12f+kxGXHpxarXas97+w20PJ1v6V3+ejb4cy0n/8mA41wB2r5b+3Spm69Zt/r/3Qo06Fw70XLC3zQPFnwv0QcPmwADr/q+fB7v/6+fBXb/e25x99tk7/v0//+f/TL1e79d2nqk59sS2f/Ob3yRJ/uIv/iKf/exnn3Zfw+V3P1AaPxMBGmS7mDx5ctavX5877rgjxx133E6vtbW15YILLkiSzJ8/f7c/DL3yla/ccYXZoYcemptuuikHHnhgv+OZMmXKsPgroifuqztixIgdJ3+NpmlMV5/XqdfrqdVqGTOu1rDvS1LG/3+SbK/174fyxzav3Svfl7Fje//Lk+bm5h2f+7LecH5fGnX8I0btM+T7fLaeN+V5A3oF2aMDsqX/2t6aNen+2hWpvWB2mt5yWmojRqTp7QvT/Q//mO7vXpMRbzz1We/jeVOeV8kVZH05lpP+5cFwrgHs3qbNa7NPPx4mtr3e4f97L9Soc+FAzgV74zxQ+rlAXzRqDgy0pv/6ebDpv34e3PXr4aa7u/tpG07HH398XvCCFyRJbr755ixfvrxf+9hTcyxJ7r333tx444054YQTMmvWrPzJn/xJbrzxxt1ub7j87gdK42ciaAyTJ0/u97oaZLs44YQTsnz58lx88cV5zWtek9mze26bdtttt+Ud73hH1q7teUjVUUcdtdv1v/rVr2bDhg1ZtWpVPvnJT+a1r31tlixZsuPy/b6677770tLS0q91B9Itf9/z8PUpU6bseAZbo+nentxyedKXn8tqtVomTEnuWvbLwQtsGCjh/z9JNv0+ufXrfV/vRa9+Xlo/tve9LytWrOj1skuXLs3Xvva1vO51r+vTfbYvuuii/oQ2JBp1/Fu3JxdeNeS7fVbuve++jBmgM5KOru15zk0/GpBt1bu70/XJTyfd3RlxwV+m9sQvg95yWupL/j3dX7siTX907LO+xda9992blhFDf0rWlxxI+pcHw7kGsHsrf56s7sdpzYc/895cOvm9Ax8Qg6pR58KBmgv21nmg9HOBvmjUHBhof/vFb+Sx9o5Mmdzz8+CuXw83HR0dGTdu93/s8Sd/8ic7/v2Vr3ylX9vvTXPsCV/+8pdzwgk9tyh99atf/bQNsuHyux8ojZ+JAH+esotFixZl//33z0MPPZR58+bliCOOyKxZs3Lsscfm+c9/fl796lcnefrnj73gBS/IH/3RH+X000/Pj3/842zatCmXXHLJUA6BfmoamUw9ou/rTTtqwEOhIuOfm0zoxx/2TH3mxxE2hNmzZ2fJkiU7/migNKWPv1Tdi7+T+rLlaXrX21N70h+61EaMyIi/+sukuytdn/pMv2/Ls7eRB2WYNj9JH+8Yt+/kng8aW4k1wDzAk5WYA43o6KOP3vHvW265pc/r96U5liQ///nPd7tvYO9kLoDGo0G2i2nTpuWWW27JySefnObm5qxevToTJ07M5Zdfnuuuuy733ntvkqdvkD3Zfvvtl0MPPTQrV64c7LAZINOPTprH9375CVOSSS8YvHgYerNentT68PiV6S9Kxu43aOEMG6NGjcrEiRMzatRAP91p71D6+EtUf/DBdP/jP6U2d06a3vSnT3m9NuPgNL19Yer3/Drd372mggiHnjwoQ/O+ycF9+P1drSk59BWDFw/DR2k1wDzArkrLgUb1ohe9KEny6KOP5qGHHurTun1tjiXJww8/nEceeSSJBhk0AnMBNB4Nst2YO3durr322mzatCmbNm3KrbfemrPOOisdHR1ZvXp1mpqacvjhh+9xO7///e/zm9/8JjNnzhyCqBkIY1qSF56WjOlFk2z8pOTIN/ZceUbj2G9acsQpSVMvmmRT5iWzXzXoIQ0LDz74YM4+++w8+OCDVYdSiRLHP+2wV+W8f67n6JP/6mmXOe+f6zn1r64dwqiGTu2ggzLquu9l5Oc+veOWWrsa8ba3ZtS/XT8gz5/ZG5SYB6U69JXJ83pxVX1tRHL4ycnE/t1JnL1MaTXAPOBcYFel5UCjeu5zn5skuf/++/u0Xn+aY094Yl/777+/54zBXs5cAI3HzNwHS5cuTb1ez6xZs57yIMa3v/3t+ehHP5rvfve7+clPfpIvf/nLedWrXpWRI0fm/PPPryhi+qNl/+TYhT1Xk40c89TXx4xLnv+S5MVvTUb37Vme7CWeOyt58f/Tc3VgbTdVctxzk8NO7PnY3euNaNOmTbn55puzadOmqkOpROnjh0QelKRWS+a+NjnspJ4/CNrd68+dnRzzNlfSl0QNoHRyYO/X1NSUM888M+ecc04++9nP9mndT3/60/1qjiXJ5z73uZxzzjn58z//89RqfbyPMTCsmAug8bj2pQ/uueeeJLu/veIf//Ef5+tf/3o+97nPZcuWLZk+fXqOP/74/O///b9z8MEHD3WoPEtjxiUvOD459KXJ2t8my/4t6Xo8GdmcvPSsxB99Nb59JyVHLEi2tid/WJX85uaeY2DUPskfvaPnl4MA0KhqteR585IphyWPPZLcuTjZvrXnj4eO+7OecyUA2Jt0d3fna1/7Wr/Wfec735kbb7wxI0aM6FNzLEm+/e1v92ufAMDg0yDrg2dqkJ1zzjk555xzhjokBtmI0cmkOcm9P+lpjowYqTlWmjHjem4zdf+SnmOgaYTmGADlqNV6nrk6YlRPg2zEKM0xAMqzfv36nHDCCWlqaupTcwwAGN40yPrgmRpkAAAAADSm9evXVx0CADDANMj64Kabbqo6BIBKTJo0KRdeeGEmTdrNw2gKUPr4IZEHUDo1gNLJAQDMBdB4NMgA2KMDDjggZ5xxRtVhVKb08UMiD6B0agClkwMAmAug8XiaEgB7tHHjxtxwww3ZuHFj1aFUovTxQyIPoHRqAKWTAwCYC6DxaJABsEetra05//zz09raWnUolSh9/JDIAyidGkDp5AAA5gJoPBpkAAAAAAAAFEWDDAAAAAAAgKJokAEAAAAAAFAUDTIA9qi5uTlz585Nc3Nz1aFUovTxQyIPoHRqAKWTAwCYC6DxjKw6AACGv5kzZ+Y73/lO1WFUpvTxQyIPoHRqAKWTAwCYC6DxuIIMAAAAAACAomiQAbBHy5Yty/z587Ns2bKqQ6lE6eOHRB5A6dQASicHADAXQOPRIANgj+r1erZt25Z6vV51KJUoffyQyAMonRpA6eQAAOYCaDyeQQYADWT0iOTit1YdRd+MHjFw2xrbNCLrX/2agdvgEBjbNIBvAAB73Vww0PNA6ecCMHbs2LS3tw/Y9j55+b/ksY7O7NsyNhe89/SnfD0Qxo4dOyDbAQD6RoMMABpIrZaMKXh2r9VqaRlR8BsAQPFzQennAlCr1dLS0jJg2xs9pjmjt3Vl9JjmtLS0POVrAGDv5RaLAAAAAAAAFMXflQGwRzNnzsw111yT6dOnVx1KJUofPyTyAEqnBlA6OQCAuQAajwYZAHvU3NycWbNmVR1GZUofPyTyAEqnBlA6OQCAuQAaj1ssArBHa9asyQc/+MGsWbOm6lAqUfr4IZEHUDo1gNLJAQDMBdB4NMgA2KMNGzbk6quvzoYNG6oOpRKljx8SeQClUwMonRwAwFwAjUeDDAAAAAAAgKJokAEAAAAAAFAUDTIAAAAAAACKokEGwB41NTXlmGOOSVNTmdNG6eOHRB5A6dQASicHADAXQOORzQDsUXd3d2677bZ0d3dXHUolSh8/JPIASqcGUDo5AIC5ABqPBhkAAAAAAABF0SADAAAAAACgKBpkAAAAAAAAFEWDDIA9mjBhQhYsWJAJEyZUHUolSh8/JPIASqcGUDo5AIC5ABrPyKoDAGD4mzZtWi655JKqw6hM6eOHRB5A6dQASicHADAXQONxBRkAe7R169Y88MAD2bp1a9WhVKL08UMiD6B0agClkwMAmAug8WiQAbBHK1euzIknnpiVK1dWHUolSh8/JPIASqcGUDo5AIC5ABqPBhkAAAAAAABF8QwyAGgg9XryeFfVUfTN6BFJrTYw26rX6+ns3rvegLFNI1IbqDcAgL1uLhjoeaD0cwEoXb1eT2dnZ9Vh9MnYsWOdDwNQCQ0yAGggj3clF15VdRR9c/FbkzEDdEbS2d2V59z0o4HZ2BBZ/+rXpGWEUzKAgbK3zQUDPQ+Ufi4Apevs7My4ceOqDqNP2tvb09LSUnUYABTILRYBAAAAAAAoir/RAmCP5s2bl+XLl1cdRmVKHz8k8gBKpwZQOjkAgLkAGo8ryAAAAAAAACiKBhkAe7Rq1aqcfvrpWbVqVdWhVKL08UMiD6B0agClkwMAmAug8WiQAbBHnZ2dufvuu9PZ2Vl1KJUoffyQyAMonRpA6eQAAOYCaDwaZAAAAAAAABRFgwwAAAAAAICiaJABAAAAAABQFA0yAPZo6tSpufjiizN16tSqQ6lE6eOHRB5A6dQASicHADAXQOMZWXUAAAx/++23X17/+tdXHUZlSh8/JPIASqcGUDo5AIC5ABqPK8gA2KN169blG9/4RtatW1d1KJUoffyQyAMonRpA6eQAJZsxY0aOOeaYvOQlL8nRRx+dAw88sE/rL1iwIAsXLhyk6GDomAug8biCDIA9amtry0UXXZSjjjoqEydOrDqcIVf6+CGRB1A6NYDSyQFKMmnSpLz73e/O8cf//9m7+/io6jP//++ZSWDIEMAYS2ISiIVEIJhQKd7UrtUWuqKCN9WCRSou9Y66oEsJv21t7SpbGqS69YvdoqxLt0VKBbQIFqsLWpa2FORGJEEIC4SEiSWFhJA7ksz8/ghkIQQmEybzmZzP6/l48IiTOefkusZc5zozV845N2vkyJHt/s4fOnRIH374oVavXq2lS5eqtra23W2NGzdOy5cvV1xcy0eQS5Ys6dLYga5ELwCchzPIzqOiokL5+fkaPHiwvF6vMjIyNGPGDNXU1Gjq1KlyuVxasGCB6TABAAAAAACAi3bVVVdp6dKlOnTokH70ox9pzJgx5x0CZGRk6M4779SiRYtUVlamF154QZ/5zGfOWub0cKxHjx5yu90aM2ZMNNIAAKDDGJC1Y/v27brqqqv03HPPqby8XMOGDVNjY6NefPFFTZgwQUVFRZKkESNGmA20i52skfZvkra+Lp089YdATQ1SfbXZuKIlEJD+ulf66Lf/l39jvXTskBQMmo0tWmr+Jn2y7oz866TSHVLTSbNxAeh6pYXv66f3u/ThmvnnXean97v02/m3RzGq6Gp+dbEav3qrAmt/f85zwWBQTd+Zrcbbxiu4/0D0gwOipPaYtOd96WRdy+OTddKhrS3HhIDT2d4HOBYA7BEXF6cf/OAH+vDDDzVx4kTFx8e3Puf3+7V69Wr9v//3//T888/r3//93/X+++/r+PHjrcv069dPTzzxhHbt2qUJEyZIOns4Jkm/+tWv9A//8A/RTQwAgBC4xGIbFRUVGjdunMrLyzVz5kw9/fTTSkxMlCTNmzdPs2fPVlxcnFwul3Jzcw1H2zUCTdIn66XDO6Vg4OznmhuljS9L/YdIQ8ZIcT3MxNjVPt0j7VkvNbQZBgaapA+XSb5LpWF/L/W93Ex8Xa2+WipcKx09ePb3A83S7nelvR9IA0dJV1wnuVxmYgSAruaePEmBP29S88JX5Bp5tVyXJbc+F1j5poIf7ZT7H6bIdUWmuSCBLnKyRtq1Vvrb/rO/H2xu+eOZ4g3SgJHSZ2/gWADORR8AYIPU1FS99dZbGjlyZOv3/vrXv2rRokVatGiR9u/f3+56LpdLI0eO1GOPPab77rtPvXr1UnJysn7961/rscce0/XXX3/WcOyBBx5QIBBod1sAAJjCGWRtTJ8+XaWlpXr88cc1f/781uGYJOXn5ysvL09NTU3KzMxUnz59DEbaNQJN0raVUtmOc4djpwWDUnmRtPU3zjyTqOwjaeeqc4djZ6r5m/Thb6SjJdGLK1rqqqTNr507HDtT80npfze2DMtsOZvOdj6fTzfccIN8Pp/pUIywPX9bueLjFTdrplRfr+bn/631+8FDpQos/i+5hlwp971fMxdglFEH9mg4IW1eeu5w7EzNjdL+P0u7fsexgC1s3AfQB3AmG2sAzpeRkaH/+Z//aR2ONTU16dlnn9WAAQP0ve9977zDManlTNotW7Zo6tSpGjhwoH7zm9+0PvelL32J4RgciV4AOA8DsjMUFRVp2bJlSk5O1ty5c9td5vRBQ15e3nm3M3bsWLlcLv3whz/sijC71J710rEODn2Ol0tF73RtPNFWeVgqerdjywaapB1vOuuSk8FgS04XGg6eqewjqXRbl4aEGJGZmalFixYpMzPTdChG2J6/zVxZg+We+HUFP9yqwJr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+      "text/plain": [
+       "<Figure size 2228.78x9983.17 with 1 Axes>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qc = grover_algorithm(challenge, rep=1)\n",
+    "qc.draw('mpl')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'01110': 389, '01101': 352, '01001': 333, '01000': 365, '00011': 4738, '11100': 342, '11000': 377, '11010': 351, '10111': 326, '11001': 360, '10100': 355, '10010': 344, '01011': 383, '10001': 332, '10110': 350, '00110': 379, '00010': 330, '10011': 334, '00000': 380, '00001': 345, '11111': 354, '11011': 355, '10101': 353, '00101': 4615, '11101': 341, '01100': 347, '10000': 380, '00111': 329, '11110': 372, '01010': 348, '00100': 329, '01111': 412}\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "counts_without_qiskit_convention = circuit_execute(qc, shots=20000)\n",
+    "print(counts_without_qiskit_convention)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot_histogram(counts_without_qiskit_convention, color='midnightblue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'00011': 4738, '00101': 4615}\n"
+     ]
+    }
+   ],
+   "source": [
+    "possible_results = filter_values_above_average(counts_without_qiskit_convention)\n",
+    "\n",
+    "print(possible_results)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "List 1: [['O', 'X', 'O'], ['O', 'O', 'O'], ['X', 'X', 'X']]\n",
+      "List 2: [['O', 'X', 'O'], ['O', 'X', 'O'], ['O', 'X', 'X']]\n"
+     ]
+    }
+   ],
+   "source": [
+    "completed_lists = complete_lists_with_dictionary(challenge, possible_results)\n",
+    "\n",
+    "for i, lst in enumerate(completed_lists, start=1):\n",
+    "    print(f'List {i}: {lst}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Challenge:\n",
+      "O | X |  \n",
+      "---------\n",
+      "  |   | O\n",
+      "---------\n",
+      "  |   | X\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 1:\n",
+      "O | X | O\n",
+      "---------\n",
+      "O | O | O\n",
+      "---------\n",
+      "X | X | X\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 2:\n",
+      "O | X | O\n",
+      "---------\n",
+      "O | X | O\n",
+      "---------\n",
+      "O | X | X\n",
+      "---------\n",
+      "\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Challenge:')\n",
+    "display_board(challenge)\n",
+    "print('\\n')\n",
+    "\n",
+    "for index, lst in enumerate(completed_lists):\n",
+    "    print('Solution {}:'.format(index + 1))\n",
+    "    display_board(lst)\n",
+    "    print('\\n')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "WOMANIUM",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/challenges/PIQUE challenge/QuantumVoyagers/app/grover/grover_circuit_complete_image/file.tex b/challenges/PIQUE challenge/QuantumVoyagers/app/grover/grover_circuit_complete_image/file.tex
new file mode 100644
index 0000000..1122f84
--- /dev/null
+++ b/challenges/PIQUE challenge/QuantumVoyagers/app/grover/grover_circuit_complete_image/file.tex	
@@ -0,0 +1,33 @@
+\documentclass[border=2px]{standalone}
+
+\usepackage[braket, qm]{qcircuit}
+\usepackage{graphicx}
+
+\begin{document}
+\scalebox{1.0}{
+\Qcircuit @C=1.0em @R=0.2em @!R { \\
+	 	\nghost{{q}_{0} :  } & \lstick{{q}_{0} :  } & \gate{\mathrm{X}} \barrier[0em]{21} & \qw \barrier[0em]{21} & \qw & \ctrl{3} & \ctrl{4} & \qw & \qw & \ctrl{1} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \ctrl{9} \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{21} & \qw \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \ctrl{9} \barrier[0em]{21} & \qw & \qw & \qw & \qw & \ctrl{1} & \qw & \qw & \ctrl{4} & \ctrl{3} \barrier[0em]{21} & \qw \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{8} & \qw & \qw & \qw & \qw \barrier[0em]{8} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw\\
+	 	\nghost{{q}_{1} :  } & \lstick{{q}_{1} :  } & \gate{\mathrm{I}} & \qw & \qw & \qw & \qw & \qw & \ctrl{3} & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{8} & \ctrl{8} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{8} & \ctrl{8} & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \ctrl{3} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{2} :  } & \lstick{{q}_{2} :  } & \gate{\mathrm{I}} & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{15} & \ctrl{3} & \qw & \ctrl{2} & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{7} & \ctrl{7} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{7} & \ctrl{7} & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{2} & \qw & \ctrl{3} & \ctrl{15} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{3} :  } & \lstick{{q}_{3} :  } & \gate{\mathrm{X}} & \qw & \qw & \ctrl{3} & \qw & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{6} & \ctrl{6} & \ctrl{6} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{6} & \ctrl{6} & \ctrl{6} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \qw & \ctrl{3} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{4} :  } & \lstick{{q}_{4} :  } & \gate{\mathrm{H}} & \qw & \qw & \qw & \ctrl{4} & \ctrl{1} & \ctrl{3} & \qw & \qw & \qw & \ctrl{2} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{5} & \ctrl{5} & \ctrl{5} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{5} & \ctrl{5} & \ctrl{5} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{2} & \qw & \qw & \qw & \ctrl{3} & \ctrl{1} & \ctrl{4} & \qw & \qw & \qw & \gate{\mathrm{H}} & \gate{\mathrm{X}} & \qw & \qw & \ctrl{1} & \qw & \qw & \gate{\mathrm{X}} & \gate{\mathrm{H}} & \qw & \meter & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{5} :  } & \lstick{{q}_{5} :  } & \gate{\mathrm{H}} & \qw & \qw & \qw & \qw & \ctrl{10} & \qw & \qw & \ctrl{3} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{4} & \ctrl{4} & \ctrl{4} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{4} & \ctrl{4} & \ctrl{4} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{3} & \qw & \qw & \ctrl{10} & \qw & \qw & \qw & \qw & \gate{\mathrm{H}} & \gate{\mathrm{X}} & \qw & \qw & \ctrl{2} & \qw & \qw & \gate{\mathrm{X}} & \gate{\mathrm{H}} & \qw & \qw & \meter & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{6} :  } & \lstick{{q}_{6} :  } & \gate{\mathrm{I}} & \qw & \qw & \ctrl{7} & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \ctrl{14} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{3} & \ctrl{3} & \ctrl{3} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{3} & \ctrl{3} & \ctrl{3} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{14} & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \ctrl{7} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{7} :  } & \lstick{{q}_{7} :  } & \gate{\mathrm{H}} & \qw & \qw & \qw & \qw & \qw & \ctrl{9} & \qw & \qw & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{2} & \ctrl{2} & \ctrl{2} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{2} & \ctrl{2} & \ctrl{2} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \qw & \qw & \ctrl{9} & \qw & \qw & \qw & \qw & \qw & \gate{\mathrm{H}} & \gate{\mathrm{X}} & \qw & \qw & \ctrl{1} & \qw & \qw & \gate{\mathrm{X}} & \gate{\mathrm{H}} & \qw & \qw & \qw & \meter & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{8} :  } & \lstick{{q}_{8} :  } & \gate{\mathrm{H}} & \qw & \qw & \qw & \ctrl{6} & \qw & \qw & \qw & \ctrl{10} & \ctrl{11} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \ctrl{1} & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \ctrl{1} & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{11} & \ctrl{10} & \qw & \qw & \qw & \ctrl{6} & \qw & \qw & \qw & \gate{\mathrm{H}} & \gate{\mathrm{X}} & \qw & \gate{\mathrm{H}} & \targ & \gate{\mathrm{H}} & \qw & \gate{\mathrm{X}} & \gate{\mathrm{H}} & \qw & \qw & \qw & \qw & \meter & \qw & \qw & \qw\\
+	 	\nghost{{q}_{9} :  } & \lstick{{q}_{9} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \ctrl{1} & \targ & \qw & \ctrl{1} & \targ & \qw & \ctrl{1} & \ctrl{1} & \targ & \qw & \ctrl{1} & \ctrl{1} & \targ & \qw & \ctrl{1} & \ctrl{1} & \targ & \qw & \ctrl{1} & \ctrl{1} & \targ & \qw & \ctrl{1} & \ctrl{1} & \targ & \qw & \ctrl{1} & \ctrl{1} & \targ & \qw & \gate{\mathrm{X}} & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \gate{\mathrm{X}} & \qw & \targ & \ctrl{1} & \ctrl{1} & \qw & \targ & \ctrl{1} & \ctrl{1} & \qw & \targ & \ctrl{1} & \ctrl{1} & \qw & \targ & \ctrl{1} & \ctrl{1} & \qw & \targ & \ctrl{1} & \ctrl{1} & \qw & \targ & \ctrl{1} & \ctrl{1} & \qw & \targ & \ctrl{1} & \qw & \targ & \ctrl{1} & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{10} :  } & \lstick{{q}_{10} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \targ & \qw & \qw & \ctrl{1} & \targ & \qw & \qw & \ctrl{1} & \targ & \qw & \qw & \ctrl{1} & \targ & \qw & \qw & \ctrl{1} & \targ & \qw & \qw & \ctrl{1} & \targ & \qw & \qw & \ctrl{1} & \targ & \qw & \qw & \gate{\mathrm{X}} & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \gate{\mathrm{X}} & \qw & \qw & \targ & \ctrl{1} & \qw & \qw & \targ & \ctrl{1} & \qw & \qw & \targ & \ctrl{1} & \qw & \qw & \targ & \ctrl{1} & \qw & \qw & \targ & \ctrl{1} & \qw & \qw & \targ & \ctrl{1} & \qw & \qw & \targ & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{11} :  } & \lstick{{q}_{11} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{12} :  } & \lstick{{q}_{12} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \ctrl{2} & \ctrl{3} & \ctrl{4} & \ctrl{5} & \ctrl{6} & \ctrl{7} & \ctrl{8} & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{13} :  } & \lstick{{q}_{13} :  } & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{8} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{14} :  } & \lstick{{q}_{14} :  } & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{7} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{15} :  } & \lstick{{q}_{15} :  } & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{6} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{16} :  } & \lstick{{q}_{16} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{5} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{17} :  } & \lstick{{q}_{17} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{4} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{18} :  } & \lstick{{q}_{18} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{3} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{19} :  } & \lstick{{q}_{19} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{2} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{20} :  } & \lstick{{q}_{20} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{21} :  } & \lstick{{q}_{21} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \gate{\mathrm{X}} & \gate{\mathrm{H}} & \qw & \targ & \targ & \targ & \targ & \targ & \targ & \targ & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{\mathrm{{c} :  }} & \lstick{\mathrm{{c} :  }} & \lstick{/_{_{4}}} \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \dstick{_{_{\hspace{0.0em}0}}} \cw \ar @{<=} [-18,0] & \dstick{_{_{\hspace{0.0em}1}}} \cw \ar @{<=} [-17,0] & \dstick{_{_{\hspace{0.0em}2}}} \cw \ar @{<=} [-15,0] & \dstick{_{_{\hspace{0.0em}3}}} \cw \ar @{<=} [-14,0] & \cw & \cw & \cw\\
+\\ }}
+\end{document}
\ No newline at end of file
diff --git a/challenges/PIQUE challenge/QuantumVoyagers/app/grover/grover_circuit_complete_image/grover_circuit.pdf b/challenges/PIQUE challenge/QuantumVoyagers/app/grover/grover_circuit_complete_image/grover_circuit.pdf
new file mode 100644
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diff --git a/challenges/PIQUE challenge/QuantumVoyagers/app/grover/solution.ipynb b/challenges/PIQUE challenge/QuantumVoyagers/app/grover/solution.ipynb
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@@ -0,0 +1,834 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Solving Tic Tac Toe with Quantum Computing\n",
+    "In this notebook, we will explore how to apply quantum algorithms to solve the game of Tic Tac Toe. We will use two popular quantum algorithms: the Grover algorithm and the Quantum Approximate Optimization Algorithm (QAOA)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1. Introduction"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 1.1 Overview of Tic Tac Toe\n",
+    "\n",
+    "Tic Tac Toe, also known as Noughts and Crosses, is a classic two-player game where players take turns marking spaces on a 3x3 grid. The grid is initially empty, and players alternate placing their symbols ('X' or 'O') in an attempt to form a horizontal, vertical, or diagonal line of three of their symbols. The game ends when one player achieves this goal, resulting in a win, or if the entire grid is filled without a winner, leading to a draw.\n",
+    "\n",
+    "#### Key Rules:\n",
+    "\n",
+    "1. **Players:** Two players, typically represented by 'X' and 'O'.\n",
+    "2. **Grid:** A 3x3 square grid.\n",
+    "3. **Objective:** Form a line of three of your symbols horizontally, vertically, or diagonally.\n",
+    "4. **Turns:** Players take turns to place their symbol in an empty grid space.\n",
+    "5. **Winning:** The game ends when a player forms a line of three symbols, declaring them the winner.\n",
+    "6. **Draw:** If the grid is fully occupied and no player has won, the game is a draw.\n",
+    "\n",
+    "Tic Tac Toe is a simple yet strategic game often used for educational purposes to teach basic game theory concepts. Now, let's explore how quantum algorithms can be applied to enhance the strategies involved in playing Tic Tac Toe.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div>\n",
+    "<p style = 'text-align:center;'>\n",
+    "<img src=\"../Images/tic-tac-toe-1777880_1280.jpg\" alt=\"JuveYell\" width=\"500px\">\n",
+    "</p>\n",
+    "</div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. Grover's Algorithm"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2.1 Explanation of Grover's Quantum Search Algorithm\n",
+    "\n",
+    "Grover's Quantum Search Algorithm, developed by Lov Grover in 1996, is a potent quantum algorithm designed to perform a quadratic speedup in searching an unsorted database compared to the best classical algorithms. This algorithm relies on the principles of amplitude amplification, enabling efficient solution discovery within a large solution space.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Key Concepts:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "1. **Amplitude Amplification:**\n",
+    "In the quest for a marked element in a quantum list, we start in a uniform superposition:\n",
+    "\n",
+    "   $$ \\ket{s} = \\frac{1}{\\sqrt{N}} \\sum_{x=0}^{N-1} \\ket{x} $$\n",
+    "\n",
+    "   When measured in the standard basis, the probability of finding the correct element is $ \\frac{1}{N} = \\frac{1}{2^n} $. Amplitude amplification improves this probability by extending the amplitude of the marked element and reducing others. The algorithm's geometric interpretation involves two reflections generating a rotation in a two-dimensional plane. Introducing an additional state $ \\ket{s'} $, perpendicular to $ \\ket{w} $, achieves this by eliminating $ \\ket{w} $ from $ \\ket{s} $ and adjusting the scale."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img width=\"800px\" 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+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<p ><a href=\"https://learn.qiskit.org/course/ch-algorithms/grovers-algorithm\" target=\"_blank\">Image obtained from the Qiskit Textbook</a></p>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "2. **Oracle:**\n",
+    "   In quantum algorithms like Grover's, an oracle designates specific states as solutions. In Tic Tac Toe, it flips the sign of the probability amplitude for correct states:\n",
+    "   $$U_\\omega\\ket{x}=\\begin{cases}\n",
+    "   \\ket{x},& \\text{si } x\\neq \\omega\\\\\n",
+    "   -\\ket{x},& \\text{si } x= \\omega\n",
+    "   \\end{cases}\n",
+    "   $$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img width=\"800px\" 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\"/>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<p ><a href=\"https://learn.qiskit.org/course/ch-algorithms/grovers-algorithm\" target=\"_blank\">Image obtained from the Qiskit Textbook</a></p>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "3. **Grover Diffusion Operator:**\n",
+    "   The Grover diffusion operator enhances the amplitudes of marked states and suppresses unmarked states. It involves a sequence of quantum gates:\n",
+    "   $$U_s=2\\ket{s}\\bra{s}-\\mathbb{1}$$\n",
+    "   This sequence concentrates probability amplitudes on marked states, contributing to the algorithm's efficiency."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img width=\"800px\" 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+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<p ><a href=\"https://learn.qiskit.org/course/ch-algorithms/grovers-algorithm\" target=\"_blank\">Image obtained from the Qiskit Textbook</a></p>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finally, Grover's algorithm looks like:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img width=\"700px\" 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+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<p ><a href=\"https://learn.qiskit.org/course/ch-algorithms/grovers-algorithm\" target=\"_blank\">Imagen obtenida del Qiskit Textbook</a></p>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "\n",
+    "#### Application in Tic Tac Toe:\n",
+    "\n",
+    "For Tic Tac Toe, Grover's algorithm can be applied to search for optimal moves on the game board. By defining the oracle to identify winning board configurations and implementing the Grover diffusion operator, we can efficiently determine the optimal moves that lead to victory.\n",
+    "\n",
+    "<div>\n",
+    "<p style = 'text-align:center;'>\n",
+    "<img src=\"../Images/image9.png\" alt=\"JuveYell\" width=\"800px\">\n",
+    "</p>\n",
+    "</div>\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The concept revolves around assigning a qubit to each box, such that when the qubit is in the state |1>, it represents 'X', and when in the state |0>, it represents 'O'. The empty spaces are filled with Hadamard gates, as these states are the ones sought by the Grover's algorithm.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For this case, our Oracle consists of two crucial components. First, there are the eight victory conditions detailed in the preceding figure. However, it is essential to filter only valid plays based on both logic and the rules established earlier. Therefore, the Oracle is composed of two parts:\n",
+    "\n",
+    "1. **Victory Conditions:**\n",
+    "   - The eight specific conditions determining a win in the game.\n",
+    "\n",
+    "2. **X's Counter:**\n",
+    "   - A mechanism to count the total number of 'X' on the board. Since in any game where 'O' starts, there must be a total of 5 'O' and 4 'X', our counter verifies the presence of exactly 4 'X'.\n",
+    "\n",
+    "Finally, it is imperative to mark the states that meet any of the eight winning conditions, always ensuring there are exactly 4 'X' throughout the game. For this reason, we implement eight controlled-NOT gates, one for each winning condition, targeting the oracle qubit. This approach ensures the validity of winning plays while adhering to the restriction of having 4 'X' in the game.\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div>\n",
+    "<p style = 'text-align:center;'>\n",
+    "<img src=\"../Images/parts_oracle_grover.jpg\" alt=\"JuveYell\" width=\"1200px\">\n",
+    "</p>\n",
+    "</div>\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the preceding image, we can identify the most crucial part of our circuit. Each number represents a component of the total circuit:\n",
+    "\n",
+    "1. **Tic Tac Toe Representation Circuit:**\n",
+    "   - This circuit represents the Tic Tac Toe game, where 'H' denotes empty spaces, NOT gates represent 'X's, and 'I's represent 'O's.\n",
+    "\n",
+    "2. **Oracle Sub-Circuit:**\n",
+    "   - This sub-circuit is part of the oracle and encompasses all possible winning scenarios (8 in total).\n",
+    "\n",
+    "3. **Counter:**\n",
+    "   - The counter activates a Multi-Controlled NOT gate only if the number of 'X's is equal to 4.\n",
+    "\n",
+    "4. **State | - >:**\n",
+    "   - This state, when the required conditions are met, changes sign, marking the desired state.\n",
+    "\n",
+    "5. **Toffoli Gates:**\n",
+    "   - Toffoli gates determine the sought-after states, activating when the necessary conditions are fulfilled.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The remainder of the circuit corresponds to the inverse of circuits 2 and 3 from the preceding figure, followed by the application of the diffuser. Finally, the qubits in the 'H' states are measured, as these are the ones sought based on the established conditions.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we will see the results of implementing Grover's algorithm for our specific problem."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qiskit.visualization import plot_histogram\n",
+    "\n",
+    "import sys\n",
+    "sys.path.append('../../')\n",
+    "from pkg.general_utils import display_board, complete_lists_with_dictionary, filter_values_above_average\n",
+    "from pkg.quantum_utils import grover_algorithm, circuit_execute"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Setting up the board the way it is asked to solve it"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "X | O | O\n",
+      "---------\n",
+      "X |   |  \n",
+      "---------\n",
+      "O |   |  \n",
+      "---------\n"
+     ]
+    }
+   ],
+   "source": [
+    "challenge = [['X', 'O', 'O'], ['X', ' ', ' '], ['O', ' ', ' ']]\n",
+    "display_board(challenge)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Building the complete circuit and graphing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2228.78x9983.17 with 1 Axes>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qc = grover_algorithm(challenge, rep=1)\n",
+    "\n",
+    "qc.draw('mpl')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'\\\\documentclass[border=2px]{standalone}\\n\\n\\\\usepackage[braket, qm]{qcircuit}\\n\\\\usepackage{graphicx}\\n\\n\\\\begin{document}\\n\\\\scalebox{1.0}{\\n\\\\Qcircuit @C=1.0em @R=0.2em @!R { \\\\\\\\\\n\\t \\t\\\\nghost{{q}_{0} :  } & \\\\lstick{{q}_{0} :  } & \\\\gate{\\\\mathrm{X}} \\\\barrier[0em]{21} & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\ctrl{3} & \\\\ctrl{4} & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\ctrl{9} \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\ctrl{9} \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\ctrl{4} & \\\\ctrl{3} \\\\barrier[0em]{21} & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{8} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{8} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{1} :  } & \\\\lstick{{q}_{1} :  } & \\\\gate{\\\\mathrm{I}} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{8} & \\\\ctrl{8} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{8} & \\\\ctrl{8} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{2} :  } & \\\\lstick{{q}_{2} :  } & \\\\gate{\\\\mathrm{I}} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{15} & \\\\ctrl{3} & \\\\qw & \\\\ctrl{2} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{7} & \\\\ctrl{7} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{7} & \\\\ctrl{7} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{2} & \\\\qw & \\\\ctrl{3} & \\\\ctrl{15} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{3} :  } & \\\\lstick{{q}_{3} :  } & \\\\gate{\\\\mathrm{X}} & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{6} & \\\\ctrl{6} & \\\\ctrl{6} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{6} & \\\\ctrl{6} & \\\\ctrl{6} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{4} :  } & \\\\lstick{{q}_{4} :  } & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{4} & \\\\ctrl{1} & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{2} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{5} & \\\\ctrl{5} & \\\\ctrl{5} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{5} & \\\\ctrl{5} & \\\\ctrl{5} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{2} & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\ctrl{1} & \\\\ctrl{4} & \\\\qw & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{H}} & \\\\gate{\\\\mathrm{X}} & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{X}} & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\meter & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{5} :  } & \\\\lstick{{q}_{5} :  } & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{10} & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{4} & \\\\ctrl{4} & \\\\ctrl{4} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{4} & \\\\ctrl{4} & \\\\ctrl{4} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\ctrl{10} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{H}} & \\\\gate{\\\\mathrm{X}} & \\\\qw & \\\\qw & \\\\ctrl{2} & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{X}} & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\qw & \\\\meter & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{6} :  } & \\\\lstick{{q}_{6} :  } & \\\\gate{\\\\mathrm{I}} & \\\\qw & \\\\qw & \\\\ctrl{7} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\ctrl{14} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\ctrl{3} & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\ctrl{3} & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{14} & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{7} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{7} :  } & \\\\lstick{{q}_{7} :  } & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{9} & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{2} & \\\\ctrl{2} & \\\\ctrl{2} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{2} & \\\\ctrl{2} & \\\\ctrl{2} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\ctrl{9} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{H}} & \\\\gate{\\\\mathrm{X}} & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{X}} & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\qw & \\\\qw & \\\\meter & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{8} :  } & \\\\lstick{{q}_{8} :  } & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{6} & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{10} & \\\\ctrl{11} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{11} & \\\\ctrl{10} & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{6} & \\\\qw & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{H}} & \\\\gate{\\\\mathrm{X}} & \\\\qw & \\\\gate{\\\\mathrm{H}} & \\\\targ & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\gate{\\\\mathrm{X}} & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\meter & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{9} :  } & \\\\lstick{{q}_{9} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\gate{\\\\mathrm{X}} & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\gate{\\\\mathrm{X}} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{10} :  } & \\\\lstick{{q}_{10} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{X}} & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\gate{\\\\mathrm{X}} & \\\\qw & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{11} :  } & \\\\lstick{{q}_{11} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{12} :  } & \\\\lstick{{q}_{12} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\ctrl{2} & \\\\ctrl{3} & \\\\ctrl{4} & \\\\ctrl{5} & \\\\ctrl{6} & \\\\ctrl{7} & \\\\ctrl{8} & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{13} :  } & \\\\lstick{{q}_{13} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{8} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{14} :  } & \\\\lstick{{q}_{14} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{7} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{15} :  } & \\\\lstick{{q}_{15} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{6} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{16} :  } & \\\\lstick{{q}_{16} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{5} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{17} :  } & \\\\lstick{{q}_{17} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{4} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{18} :  } & \\\\lstick{{q}_{18} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{19} :  } & \\\\lstick{{q}_{19} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{2} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{20} :  } & \\\\lstick{{q}_{20} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{21} :  } & \\\\lstick{{q}_{21} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{X}} & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\targ & \\\\targ & \\\\targ & \\\\targ & \\\\targ & \\\\targ & \\\\targ & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{\\\\mathrm{{c} :  }} & \\\\lstick{\\\\mathrm{{c} :  }} & \\\\lstick{/_{_{4}}} \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\dstick{_{_{\\\\hspace{0.0em}0}}} \\\\cw \\\\ar @{<=} [-18,0] & \\\\dstick{_{_{\\\\hspace{0.0em}1}}} \\\\cw \\\\ar @{<=} [-17,0] & \\\\dstick{_{_{\\\\hspace{0.0em}2}}} \\\\cw \\\\ar @{<=} [-15,0] & \\\\dstick{_{_{\\\\hspace{0.0em}3}}} \\\\cw \\\\ar @{<=} [-14,0] & \\\\cw & \\\\cw & \\\\cw\\\\\\\\\\n\\\\\\\\ }}\\n\\\\end{document}'"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qc.draw('latex_source', filename='./grover_circuit_complete_image/file.tex')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Running the complete circuit and graphing the results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'1011': 288, '0000': 293, '1000': 296, '0011': 317, '1101': 293, '1100': 7852, '1110': 315, '0111': 323, '1001': 7791, '1010': 319, '0010': 286, '1111': 329, '0101': 323, '0001': 298, '0110': 348, '0100': 329}\n"
+     ]
+    }
+   ],
+   "source": [
+    "counts_without_qiskit_convention = circuit_execute(qc, shots=20000)\n",
+    "print(counts_without_qiskit_convention)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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oKAgTJ05ErVq1DPrHx8fj008/xR9//IFbt27Bw8MDPXv2xJQpU+Dg4JDp+XU6HRYuXIgffvgBly5dgr29PV555RXMmDED1apVy3Kdtm7dipkzZ+L48eNQFAUvvvgiPv74Y7zyyiu5yo1FIRERFQQWhZSdYl0UlmQsComIqCCwKKTs5LT2KHK3pCEiouKJRQlR8VbkLjQhIiIiosLHopCIiIiIWBQSEREREYtCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIgKLQiIiIiICi0IiIiIiAotCIiIiIkIRLwo3bNiANm3awMXFBdbW1qhSpQr69OmDqKgog34JCQkYM2YMvL29YWVlhcqVK+PDDz9EYmJils+r0+mwYMEC1K1bFzY2NnBzc0OfPn0QGRmZ7bqEhIQgMDAQDg4OcHR0RFBQEHbs2GHUfImIiIhMpUgWhSKC4cOH47XXXsOVK1fw+uuv4/3338fLL7+MAwcO4Nq1a2rfpKQkBAYGYt68efD19cXo0aNRs2ZNzJkzB61atcKTJ08yPf/w4cMxatQoiAhGjRqFdu3aYf369WjcuDEiIiIy9V+xYgXatWuHc+fOYdCgQRg4cCDOnj2LNm3aYN26dQW6LYiIiIgKg7mpVyAr33zzDX744Qe88847+Oabb2BmZmawPDU1Vf3/L774AuHh4Rg3bhxmzZqlto8fPx6zZ8/GvHnzMGHCBLV9165dWLJkCVq0aIFt27bB0tISAPC///0PHTp0wIgRIxASEqL2f/DgAUaOHAlXV1ccP34cFStWBACMGzcODRo0wNtvv422bdvCwcGhQLYFERERUWEociOFjx8/xtSpU1G1alXMnz8/U0EIAObmT2tZEcGSJUtgb2+PyZMnG/SZPHky7O3tsWTJEoP2H3/8EQAwffp0tSAEgPbt26Nly5YIDQ3F9evX1fa1a9ciLi4OI0eOVAtCAKhYsSJGjBiB2NhYbNiwIf+JExEREZlQkSsKQ0ND8eDBA3Tt2hVpaWlYv349Zs2ahUWLFuHSpUsGfSMiIhAdHY2AgADY2dkZLLOzs0NAQAAiIyMNzkHcvXu3uiyjtm3bAgD27Nlj0B8AgoODc9SfiIiIqDgqcoePjx07BgAwMzNDvXr1cPHiRXWZRqPB6NGjMWfOHABQz//z8fHJ8rl8fHwQEhKCiIgIeHl5ISkpCTExMXjhhReyHIHUP0/68wqfFSOr/hklJycjOTlZ/XdCQgIAQKvVQqvVqnmZmZkhLS0NOp3OIF8zMzOkpqZCRNR2MzMzaDSabNv1z6unH1lNf9j9We0WFhbQ6XRIS0tT2xRFgbm5ebbt2a07c2JOzKn05JRfWq22yOVUnF4nYyhqOZXE18lUOeVEkSsK79y5AwD46quv0LBhQ4SFhaFWrVo4ceIEhg0bhrlz56JatWp4++23ER8fDwBwcnLK8rkcHR0BQO2X2/7Pe0xW/TP6/PPPMXXq1EztoaGhsLW1BQBUqlQJDRo0wKlTpwwOXdesWRO+vr4ICwvD3bt31XY/Pz94e3tj7969ePjwodrerFkzuLu7IzQ01OANEBQUBBsbG2zevNlgHTp06IDHjx9j165dapu5uTk6duyI2NhYHDx4UG13cHBAq1atEBUVhfDwcLXdzc0N/v7+iIiIwIULF9R25sScmFPpyym/Nm/eXORyKk6vkzEUtZxK4utkipz0A27Po0j6srcIGDZsGH788UfY2Njg0qVL8PT0VJedOXMG9evXR5UqVXDp0iWsXLkSffv2xaRJk/DZZ59leq5JkyZh5syZWL9+Pbp164bo6GhUqFABAQEB2LdvX6b+27ZtQ3BwMEaNGoX58+cDAGrUqIGIiAhotdpMv8a0Wi0sLS1Rr149nDx5Mst8shop9PLyQmxsrFpUltZfLcyJOTGnkpVTpUofIj+uXfuiyOVUnF6nChXGID+io+cVuZxK4utkipzu378PFxcXxMfHq7VHVorcSKF+RK5Ro0YGBSEAvPDCC6hatSouXbqEuLg4tW92I3X6Q7X6frntn/ExLi4uz+2fkZWVFaysrDK1W1hYwMLCwqDNzMzsmRfW5LQ94/PmpV2j0UCjyXzKaXbt2a07c2JOuW1nTsU7p/xIH6co5VRcXidjKGo5lcTXqSjllClejnoVopo1awIAypQpk+Vyffvjx4+fe05fxvMB7ezs4OHhgStXrhhU3tn1T///WcV43jmNRERERMVFkSsKg4KCAADnzp3LtEyr1eLSpUuws7ODm5sbfHx84Onpif379yMpKcmgb1JSEvbv348qVarAy8tLbQ8MDFSXZaS/P2GLFi0M+gNPzwHMrr++DxEREVFxVeSKwmrVqiE4OBiXLl3KdI/BWbNmIS4uDt26dYO5uTkURcGQIUOQmJiI6dOnG/SdPn06EhMTMXToUIP2YcOGAXh6H8OUlBS1fcuWLdi9ezeCg4Ph7e2ttvfq1QtOTk5YsGABbty4obbfuHEDCxcuhKurK7p162a0/ImIiIhMochdaAIAly9fhr+/P+7cuYOOHTvC19cXJ06cwM6dO+Ht7Y1Dhw6hfPnyAJ6OCAYEBODkyZMIDg5Gw4YNcfz4cYSGhqJx48bYs2cPbGxsDJ5/6NChWLJkCerUqYOOHTsiJiYGq1evhr29PQ4ePIgaNWoY9F+xYgX69+8PNzc39O7dGwCwevVqxMbGYvXq1ejZs2eOc0tISICTk9NzT/YkIipuPD1H5+vx0dHzjLQmpRO3P2Unp7VHkRspBJ6OFh49ehSDBg3CsWPH8M033yAiIgLvvvsuwsLC1IIQeHqe4J49e/D+++/j3LlzmDt3Ls6fP4+xY8dix44dmQpCAFi8eLF6dfH8+fOxefNmdOvWDWFhYZkKQgDo168ftmzZAl9fXyxbtgzLly9H7dq1ERoamquCkIiIiKioKpIjhSUZRwqJqKTiSJVpcftTdor1SCERERERFS4WhURERETEopCIiIiIWBQSEREREVgUEhERERFYFBIRERERWBQSEREREVgUEhERERFYFBIRERERWBQSEREREVgUEhERERFYFBIRERERWBQSEREREVgUEhERERFYFBIRERERWBQSEREREVgUEhERERFYFBIRERERWBQSEREREVgUEhERERFYFBIRERERWBQSEREREVgUEhERERFYFBIRERERWBQSEREREVgUEhERERFYFBIRERERWBQSEREREVgUEhERERFYFBIRERERWBQSEREREVgUEhERERFYFBIRERERWBQSEREREVgUEhERERFYFBIRERERWBQSEREREVgUEhERERFYFBIRERERWBQSEREREfJRFO7duxfXr19/Zp+oqCjs3bs3ryGIiIiIqJDkuSgMCgrC8uXLn9nnl19+QVBQUF5DEBEREVEhyXNRKCLP7aPT6aAoSl5DEBEREVEhKdBzCiMiIuDk5FSQIYiIiIjICMxz03nw4MEG//7zzz9x9erVTP3S0tLU8wnbt2+frxUkIiIiooKXq6Iw/TmEiqIgPDwc4eHhWfZVFAWNGzfGvHnz8rN+RERERFQIclUUXrlyBcDT8wmrVq2K999/H++9916mfmZmZihbtizs7OyMs5ZEREREVKByVRR6e3ur/79s2TI0aNDAoI2IiIiIiqdcFYXpDRw40JjrQUREREQmlOeiUC8sLAxHjhxBXFwc0tLSMi1XFAWTJ0/ObxgiIiIiKkB5Lgrv37+Prl27Yv/+/c+8ZyGLQiIiIqKiL89F4ZgxY7Bv3z60bNkSAwcORMWKFWFunu+BRyIiIiIygTxXcZs2bUKTJk2wY8cOzlpCREREVMzleUaTx48fo0WLFiwIiYiIiEqAPBeFfn5+Wc5mQkRERETFT56LwilTpmDjxo04dOiQMdeHiIiIiEwgz+cU3rp1Cx07dkRgYCD69u2Lhg0bwtHRMcu+AwYMyPMKEhEREVHBU+RZ95N5Bo1GA0VRDG5Hk/H8QhGBoihZ3r+wtEpISICTkxPi4+OzLaKJiIojT8/R+Xp8dPQ8I61J6cTtT9nJae2R55HCZcuW5fWhRERERFTEcJo7IiIiIsr7hSZEREREVHLkeaTw+vXrOe5bqVKlvIYhIiIiokKQ56KwcuXKObpxtaIoSE1NzWsYIiIiIioEeS4KBwwYkGVRGB8fj5MnT+LKlSsIDAxE5cqV87N+RERERFQI8lwULl++PNtlIoK5c+fiiy++wE8//ZTXEERERERUSArkQhNFUfDBBx+gTp06+PDDDwsiBBEREREZUYFefdyoUSPs3LmzIEMQERERkREUaFF4+fJlXmRCREREVAzk+ZzC7Oh0Oty8eRPLly/HX3/9hdatWxs7BBEREREZWZ6LQv3cx9kREZQtWxZz587NawgiIiIiKiR5LgpbtGiRZVGo0WhQtmxZNG7cGG+88Qbc3d3ztYJEREREVPDyXBTu3r3biKtBRERERKbEuY+JiIiIyDgXmuzfvx/h4eFISEiAo6Mj/Pz8EBAQYIynJiIiIqJCkK+RwgMHDqBmzZpo0aIFRo0ahUmTJmHUqFFo0aIFfH19cfDgQaOs5OzZs6EoChRFwaFDhzItT0hIwJgxY+Dt7Q0rKytUrlwZH374IRITE7N8Pp1OhwULFqBu3bqwsbGBm5sb+vTpg8jIyGzXISQkBIGBgXBwcICjoyOCgoKwY8cOo+RHREREZGp5Hik8e/YsgoOD8ejRI7Rp0wZBQUHw8PDArVu3sGvXLoSGhqJt27Y4dOgQateunecVPHPmDKZMmQI7OzskJSVlWp6UlITAwECEh4cjODgYffr0wYkTJzBnzhzs2bMHe/fuhbW1tcFjhg8fjiVLlqBOnToYNWoUoqOjsWbNGoSGhuLQoUPw8fEx6L9ixQr0798fbm5uGDRoEABg9erVaNOmDdasWYMePXrkOT8iIiKiokAREcnLA3v37o0NGzZg48aNaNeuXablW7duRefOnfHaa6/h999/z9PKabVaNG3aFBYWFvDx8cGKFStw8OBBNG3aVO0zZcoUTJs2DePGjcOsWbPU9vHjx2P27NmYOXMmJkyYoLbv2rULrVq1QosWLbBt2zZYWloCALZs2YIOHTogODgYISEhav8HDx6gatWqMDc3x4kTJ1CxYkUAwI0bN9CgQQMAQGRkJBwcHHKUU0JCApycnBAfHw9HR8c8bRcioqLI03N0vh4fHT3PSGtSOnH7U3ZyWnvk+fDx7t270aNHjywLQgBo164devTogV27duU1BGbMmIGzZ89i6dKlMDMzy7RcRLBkyRLY29tj8uTJBssmT54Me3t7LFmyxKD9xx9/BABMnz5dLQgBoH379mjZsiVCQ0Nx/fp1tX3t2rWIi4vDyJEj1YIQACpWrIgRI0YgNjYWGzZsyHOOREREREVBnovC+Ph4VKlS5Zl9qlSpgvj4+Dw9//HjxzFjxgxMmTIl28PPERERiI6ORkBAAOzs7AyW2dnZISAgAJGRkYiKilLbd+/erS7LqG3btgCAPXv2GPQHgODg4Bz1JyIiIiqO8nxOoaenZ5YXfaR3+PBheHp65vq5k5OTMWDAAPj5+eGjjz7Ktl9ERAQAZDoHUM/HxwchISGIiIiAl5cXkpKSEBMTgxdeeCHLkUf98+if93kxsuqfVS7JycnqvxMSEgA8PTSu1WoBPL3ht5mZGdLS0qDT6dS++vbU1FSkP8pvZmYGjUaTbbv+efXMzZ++zBnnoc6u3cLCAjqdDmlpaWqboigwNzfPtj27dWdOzIk5lZ6c8kur1Ra5nIrT62QMRS2nkvg6mSqnnMjzO6lz585YsGABJk+ejEmTJhlczPHkyRN8/vnn2LVrF0aNGpXr5/7kk08QERGBY8eOZVm86elHIZ2cnLJcrj9uru+X2/7Pe0xW/TP6/PPPMXXq1EztoaGhsLW1BQBUqlQJDRo0wKlTpwwOXdesWRO+vr4ICwvD3bt31XY/Pz94e3tj7969ePjwodrerFkzuLu7IzQ01OANEBQUBBsbG2zevNlgHTp06IDHjx8bHOI3NzdHx44dERsba3D1uIODA1q1aoWoqCiEh4er7W5ubvD390dERAQuXLigtjMn5sScSl9O+bV58+Yil1Nxep2MoajlVBJfJ1PkdOzYMeREni80uXfvHl566SVcuXIFLi4uaNKkCcqVK4fbt2/jyJEjuHv3LqpWrYqwsDA4Ozvn+HkPHjyI5s2b49NPPzU4T3DQoEH4+eefDS40WblyJfr27YtJkybhs88+y/RckyZNwsyZM7F+/Xp069YN0dHRqFChAgICArBv375M/bdt24bg4GCMGjUK8+fPBwDUqFEDERER0Gq1mX6NabVaWFpaol69ejh58mSW+WQ1Uujl5YXY2Fi1qCytv1qYE3NiTiUrp0qVPkR+XLv2RZHLqTi9ThUqjEF+REfPK3I5lcTXyRQ53b9/Hy4uLs+90CTPI4UuLi44dOgQPvroI/z+++8GFbG1tTXeeOMNzJ49O1cFYWpqKgYOHIh69eph/Pjxz+2vH73LbqROf6hW3y+3/TM+xsXF5bn9M7KysoKVlVWmdgsLC1hYWBi0mZmZZTkymt2hgezaMz5vXto1Gg00msynnGbXnt26MyfmlNt25lS8c8qP9HGKUk7F5XUyhqKWU0l8nYpSTpn65ahXNlxdXbF06VIsXrwY58+fV2c08fX1zdObNjExUT0/L/2Vwek1a9YMALBhwwb1ApTszunLeD6gnZ0dPDw8cOXKFaSlpWXacFmdP+jj44OjR48iIiIiU1H4vHMaiYiIiIqLXBeFM2bMQFJSEqZOnaoWfhYWFqhbt67aJyUlBZMmTYKDg0OORvz0rKys8Oabb2a5bO/evYiIiEDnzp3h5uaGypUrw8fHB56enti/fz+SkpIMrkBOSkrC/v37UaVKFXh5eantgYGB+P3337F//360aNHCIIb+/oTp2wMDA7Fq1SqEhoYa3B8xff/AwMAc50hERERUFOVq7H/79u345JNP4OLi8syRQEtLS7i4uGDSpEm5uk+hjY0NlixZkuWfv78/AGDChAlYsmQJ/Pz8oCgKhgwZgsTEREyfPt3guaZPn47ExEQMHTrUoH3YsGEAnt7HMCUlRW3fsmULdu/ejeDgYHh7e6vtvXr1gpOTExYsWIAbN26o7Tdu3MDChQvh6uqKbt265ThHIiIioqIoVyOFv/zyC8qWLYsRI0Y8t++7776Lzz//HMuWLUNQUFCeV/B5PvroI/z111+YPXs2Tpw4gYYNG+L48eMIDQ1F48aN8f777xv0DwoKwpAhQ7BkyRI0bNgQHTt2RExMDFavXg1nZ2csWLDAoH/ZsmWxcOFC9O/fHw0bNkTv3r0BPJ3m7t69e1i9erVRrrojIiIiMqVcjRQeOHAAr7zySpYXTmRkZWWFV155Bfv378/zyuWEnZ0d9uzZg/fffx/nzp3D3Llzcf78eYwdOxY7duyAjY1NpscsXrxYvbp4/vz52Lx5M7p164awsDDUqFEjU/9+/fphy5Yt8PX1xbJly7B8+XLUrl0boaGh6NmzZ4HmR0RERFQYcnVLGltbW7z//vuYOXNmjvpPnDgRX3/9NR49epTnFSxpOPcxEZVUnHvXtLj9KTsFMvdxVvfjeRb93emJiIiIqGjLVcXm6emJM2fO5Lj/mTNnUKFChVyvFBEREREVrlwVhS+//DJ27tyJq1evPrfv1atXsXPnzky3fSEiIiKioidXReG7774LrVaLHj16IDY2Ntt+9+7dQ8+ePZGamoq333473ytJRERERAUrV7ekadiwId5//318/fXXqF27Nt566y0EBQWhYsWKAICbN29ix44d+OGHH3D37l2MGTMGDRs2LJAVJyIiIiLjyfWMJnPnzoW1tTW+/PJLzJgxAzNmzDBYLiIwMzPDhAkT8NlnnxltRYmIiIio4OS6KFQUBTNnzsSbb76JZcuW4cCBA7h16xYAoHz58ggICMCgQYNQrVo1o68sERERERWMXBeFetWqVeNIIBEREVEJwZsIEhERERGLQiIiIiJiUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREYFFIRERERGBRSERERERgUUhEREREKIJF4c2bN/H1118jODgYlSpVgqWlJcqXL4/u3bvj8OHDWT4mISEBY8aMgbe3N6ysrFC5cmV8+OGHSExMzLK/TqfDggULULduXdjY2MDNzQ19+vRBZGRktusVEhKCwMBAODg4wNHREUFBQdixY4dRciYiIiIytSJXFC5YsACjR49GZGQkgoODMXbsWDRv3hx//fUX/P39sXr1aoP+SUlJCAwMxLx58+Dr64vRo0ejZs2amDNnDlq1aoUnT55kijF8+HCMGjUKIoJRo0ahXbt2WL9+PRo3boyIiIhM/VesWIF27drh3LlzGDRoEAYOHIizZ8+iTZs2WLduXYFtCyIiIqLCooiImHol0lu/fj1cXFwQGBho0P7vv/+idevWsLe3R0xMDKysrAAAU6ZMwbRp0zBu3DjMmjVL7T9+/HjMnj0bM2fOxIQJE9T2Xbt2oVWrVmjRogW2bdsGS0tLAMCWLVvQoUMHBAcHIyQkRO3/4MEDVK1aFebm5jhx4gQqVqwIALhx4wYaNGgAAIiMjISDg0OO8ktISICTkxPi4+Ph6OiYhy1ERFQ0eXqOztfjo6PnGWlNSiduf8pOTmuPIjdS+Nprr2UqCAHg5ZdfRlBQEB48eIDTp08DAEQES5Ysgb29PSZPnmzQf/LkybC3t8eSJUsM2n/88UcAwPTp09WCEADat2+Pli1bIjQ0FNevX1fb165di7i4OIwcOVItCAGgYsWKGDFiBGJjY7Fhw4b8J05ERERkQkWuKHwWCwsLAIC5uTkAICIiAtHR0QgICICdnZ1BXzs7OwQEBCAyMhJRUVFq++7du9VlGbVt2xYAsGfPHoP+ABAcHJyj/kRERETFkbmpVyCnrl+/ju3bt8PDwwN169YFAPX8Px8fnywf4+Pjg5CQEERERMDLywtJSUmIiYnBCy+8ADMzsyz7p3/e58XIqn9GycnJSE5OVv+dkJAAANBqtdBqtQAAjUYDMzMzpKWlQafTqX317ampqUh/lN/MzAwajSbbdv3z6umL6NTU1By1W1hYQKfTIS0tTW1TFAXm5ubZtme37syJOTGn0pNTfmm12iKXU3F6nYyhqOVUEl8nU+WUE8WiKNRqtejfvz+Sk5Mxe/ZstaCLj48HADg5OWX5OP1xc32/3PZ/3mOy6p/R559/jqlTp2ZqDw0Nha2tLQCgUqVKaNCgAU6dOmVw6LpmzZrw9fVFWFgY7t69q7b7+fnB29sbe/fuxcOHD9X2Zs2awd3dHaGhoQZvgKCgINjY2GDz5s0G69ChQwc8fvwYu3btUtvMzc3RsWNHxMbG4uDBg2q7g4MDWrVqhaioKISHh6vtbm5u8Pf3R0REBC5cuKC2MyfmxJxKX075tXnz5iKXU3F6nYyhqOVUEl8nU+R07Ngx5ESRu9AkI51Oh/79+2PlypUYOnQofvjhB3XZypUr0bdvX0yaNAmfffZZpsdOmjQJM2fOxPr169GtWzdER0ejQoUKCAgIwL59+zL137ZtG4KDgzFq1CjMnz8fAFCjRg1ERERAq9Vm+jWm1WphaWmJevXq4eTJk1muf1YjhV5eXoiNjVWLytL6q4U5MSfmVLJyqlTpQ+THtWtfFLmcitPrVKHCGORHdPS8IpdTSXydTJHT/fv34eLi8twLTYr0SKFOp8PgwYOxcuVK9OvXD4sWLTJYrh+9y26kTn+oVt8vt/0zPsbFxeW5/TOysrJSr5ROz8LCQj1HUs/MzCzLw9rZHRrIrj3j8+alXaPRQKPJfMppdu3ZrTtzYk65bWdOxTun/EgfpyjlVFxeJ2MoajmVxNepKOWUKV6OepmATqfDG2+8gZ9//hl9+vTB8uXLM22Y553Tl/F8QDs7O3h4eODKlSsGlXd2/Z8X43nnNBIREREVF0WyKNQXhL/88gt69+6NX3/9NdsLQzw9PbF//34kJSUZLEtKSsL+/ftRpUoVeHl5qe2BgYHqsoz09yds0aKFQX/g6TmA2fXP6hY6RERERMVJkSsK9YeMf/nlF/Ts2RMrVqzIsiAEnh5bHzJkCBITEzF9+nSDZdOnT0diYiKGDh1q0D5s2DAAT+9jmJKSorZv2bIFu3fvRnBwMLy9vdX2Xr16wcnJCQsWLMCNGzfU9hs3bmDhwoVwdXVFt27d8p03ERERkSkVuXMKp02bhp9//hn29vaoUaNGlheQdO3aFX5+fgCAjz76CH/99Rdmz56NEydOoGHDhjh+/DhCQ0PRuHFjvP/++waPDQoKwpAhQ7BkyRI0bNgQHTt2RExMDFavXg1nZ2csWLDAoH/ZsmWxcOFC9O/fHw0bNkTv3r0BAKtXr8a9e/ewevVqo1x1R0RERGRKRa4ovHr1KgAgMTERM2bMyLJP5cqV1aLQzs4Oe/bswaeffoo//vgDu3btgoeHB8aOHYspU6bAxsYm0+MXL16MunXr4ocffsD8+fNhb2+Pbt26YcaMGahWrVqm/v369YOrqytmzpyJZcuWQVEUvPjii/j444/xyiuvGC13IiIiIlMp8rekKWk49zERlVSce9e0uP0pO8V27mMiIiIiKnwsComIiIiIRSERERERsSgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJCIiIiKwKCQiIiIisCgkIiIiIrAoJKJi7vvvv0e9evXg6OgIR0dHNGvWDFu2bMnUT0TQvn17KIqCP//802DZkSNH0Lp1a5QpUwZly5ZF27ZtcfLkyULKgIioaGBRSJRPzytKfvjhB7Rs2RKOjo5QFAVxcXEGj9+9ezcURcny78iRI/mKf//+fYwcORI1a9aEjY0NKlWqhFGjRiE+Pt7gOXbs2AF/f384ODigfPnyGDduHFJTU/Odf07i37t3D+3atYOnpyesrKzg5eWFESNGICEhIUfxK1asiFmzZuHYsWM4evQoWrVqhS5duuDs2bMG/b7++msoipLp8YmJiWjXrh0qVaqEw4cPY9++fXBwcEDbtm2h1WqLfP6lWX4/ewBw/PhxtGnTBmXKlIGLiwuGDRuGxMTEQsyC8sIYr33lypUz7XNnzZqV7/iFsd8tKCwKS4jPP/8cjRs3hoODA9zd3dG1a1dcuHDBoM/ly5fRrVs3uLm5wdHREb169cLt27cN+nTu3BmVKlWCtbU1PDw80L9/f0RHRxda/IsXL6JLly5wdXWFo6Mjmjdvjl27duVxqxSO5xUljx49Qrt27TBx4sQsH+/v74+YmBiDvyFDhqBKlSpo1KhRvuJHR0cjOjoac+bMwZkzZ7B8+XJs3boVb775pvr4kydPokOHDmjXrh1OnDiB1atXY+PGjRg/fny+889JfI1Ggy5dumDjxo24ePEili9fju3bt+Ott97KUfxOnTqhQ4cO8PHxQY0aNTBjxgzY29vj0KFDap/w8HDMnTsXS5cuzfT48+fP4/79+5g2bRpq1qyJOnXqYMqUKbh9+zauXbtWpPM31ucOAP755x+89NJLsLGxQdmyZdG1a9fnxje1/H72oqOj8corr6B69eo4fPgwtm7dirNnz2LQoEGFmEXxZOrvnPy+9nrTpk0z2PeOHDkyR/mber9bYIQKVXx8vACQ+Ph4oz5v27ZtZdmyZXLmzBkJDw+XDh06SKVKlSQxMVFERBITE6Vq1arSrVs3OXXqlJw6dUq6dOkijRs3lrS0NPV5vvrqKzl48KBcvXpV9u/fL82aNZNmzZoVWnwfHx/p0KGDnDx5Ui5evCjvvPOO2NraSkxMTLaxZ86cKY0aNRJ7e3txc3OTLl26yPnz5w36xMTESL9+/aRcuXJia2srDRo0kHXr1mV6rk2bNkmTJk3E2tpaypQpI126dHlu7lkpW7asLFmyxKBt165dAkAePHjwzMempKSIm5ubTJs2LU+xs4uvt2bNGrG0tBStVisiIhMmTJBGjRoZ9Nm4caNYW1tLQkJCgcfPyvz586VixYq5jpuamiqrVq0SS0tLOXv2rIiIJCUlSa1ateTPP/8UEREAsmHDBvUxCQkJ4uLiIlOmTJHk5GR59OiRvPfee1KrVq1nruOzFFb+xvrcrVu3TsqWLSvff/+9XLhwQc6ePSurV6/OZdYiHh7v5+vPGHLz2Vu8eLG4u7sbbItTp04JAImIiHhuLGPtey5cuCCdO3cWFxcXcXBwkICAANm5c2cuMy/c7W/q75ys5Ha/6+3tLfPmzctTrJzG1yuM/e6z5LT2YFFYyAqqKMzozp07AkD27NkjIiIhISGi0WgM4sbFxYmiKLJt27Zsn+evv/4SRVEkJSWlwOPfvXtXAMjevXvVPgkJCQLgmev4vJ2TiEibNm2kcePGcvjwYbl8+bJMnz5dNBqNHD9+XO1jjC/GrIoSvZwWhevWrRONRiNRUVG5iv28+Ho//vijuLq6qv8eM2aMNG/e3KDPtm3bBIDs2rWrwONndPPmTQkMDJS+ffvmOO6pU6fEzs5OzMzMxMnJSf755x912bBhw+TNN99U/52xKBQROX36tFSrVk00Go1oNBqpWbOmXL16Ncfx9UyVv15ePndarVYqVKiQ7ZdZbpiyKMzLZ++bb77JVHxHREQIAFm2bNlzYxpr35OXH8NZMeX2N+V3Tl73u97e3lKuXDlxdnYWPz8/+eKLL/L0Q9DU+92cYFFYRBVWUajfsZ0+fVpEnv4CMTMzkydPnqh9njx5ImZmZjJlypQsn+PevXvSq1cvCQgIKJT4Op1OatasKUOGDJHExETRarXy5Zdfiru7u9y/fz/HsTPunERE7Ozs5JdffjHo5+zsLD/++KOI5P+L8VlFiV5Oi8L27dtL+/btjR5f5GnhXalSJZk4caLapt95r1y5UlJTU+XGjRvy8ssvCwBZuXJlgcfXe/3118XGxkYASKdOneTx48c5ii0ikpycLBEREXL06FEZP368uLq6ytmzZ+Wvv/6S6tWry8OHD9W+GYvCR48eSZMmTWTAgAESFhYmBw8elO7du0udOnXk0aNHxSJ/vbx87g4fPiwAZOnSpeLn5yfly5eXdu3aqc+RG6YoSvLz2Ttz5oyYm5vLF198IcnJyXL//n3p3r27AJCZM2fmel3ysu/J64/hrJiyKDTFd05+97tz586VXbt2ycmTJ+X777+XMmXKyOjRo3MUO6fxRQpuv5sbLAqLqMIoCtPS0qRjx44GH6w7d+6Io6OjvPfee5KUlCSJiYkyYsQIASDDhg0zePxHH30ktra2AkCaNm0qsbGxhRY/KipKXnzxRVEURczMzMTDw8PgF3VOZNw5iTz9td6xY0e5d++epKWlyapVq8TW1lY9RJTfL8bsipL0clIURkVFiUajyfLQdn7jx8fHS5MmTaRdu3aZfoXPnTtXHB0dxczMTGxtbeXzzz8XAPL7778XSnyRp4fZzp07J3/99ZfUrl1b3n777Vxtg/Rat24tw4YNk/fee099L+n/AIhGo5HAwEAREVmyZEmmQ4jJyclia2srq1atKjb55/Vzt2rVKgEglSpVknXr1snRo0elT58+4uLiIvfu3cvVOpiiKMnvZ++3336TcuXKiZmZmVhaWsoHH3wg5cqVk1mzZuV6XfKy7zHWj2ER0xWFpvrOMdZ+V++nn34Sc3Nzg0I2v/ELcr+bGywKi6jCKArfeust8fb2znT4MSQkRKpWrap+Sfbr108aNmwob731lkG/u3fvyoULFyQ0NFQCAgKkQ4cOotPpCjy+TqeTzp07S/v27WXfvn1y7Ngxefvtt6VChQoSHR2do9hZ7ZxERB48eCDBwcECQMzNzcXR0VFCQkLU5cb8YhT5v6IkvZzsnKZNmyZubm65Plz/vPgJCQnSrFkzad26dbYjUDqdTm7evCmPHj2S//77TwBIWFhYocVP799//xUAOX7dMwoKCpKBAwdKTEyMnD592uAPgMyfP18iIyNF5OkhxPLlyxu8x7VardjZ2clvv/2Wp/imyD+vn7vffvtNAMjixYvVxzx58kRcXV1l0aJFOY4vUjTOKczrZ+/WrVvy8OFDSUxMFI1GI2vWrMlV3Lzue0SM82NYxHTb39TfOXp5fe31zpw5IwAynRea1/iFvd99lpzWHuZ5vD6FiqgRI0Zg06ZN2Lt3LypWrGiwLDg4GJcvX0ZsbCzMzc1RpkwZlC9fHlWrVjXo5+rqCldXV9SoUQO1atWCl5cXDh06hGbNmhVo/J07d2LTpk148OABHB0dAQDfffcdtm3bhp9//jlHV2W9++67OHPmDPbt22fQPnnyZMTFxWH79u1wdXXFn3/+iV69euHff/9F3bp1odPpAACTJk1C9+7dAQDLli1DxYoVsXbtWgwfPvy5sdPT6XRITk7O1WNEBMuWLcOAAQNgYWGRq8c+K35CQgLatm0LKysrbNy4EdbW1lk+RlEUeHp6AgBWrVoFLy8vNGzYsNDiZ3w8gBxtwwkTJqB9+/aoVKkSHj58iJUrV2L37t0ICQlB+fLlUb58+UyPqVSpEqpUqQIAaNOmDT788EO8++67GDlyJHQ6HWbNmgVzc3MEBQXlJm2D9S+s/IH8fe48PDwAALVr11YfY2VlhapVq+L69es5il+U5OWzBwDlypUDACxduhTW1tZo06ZNrh6f132PiODdd9+Fu7s7/v33X9jY2GDJkiXo1KkTjhw5or4+RZWpv3PSy+trrxceHg6NRgN3d/c8Pd7U+11jYFFYQogIRo4ciQ0bNmD37t3qF15WXF1dATwtwu7cuYPOnTtn2zenX07GiP/o0SMAT2/RkZ5Go1HX41my2zldvnwZCxcuxJkzZ1CnTh0AQP369fHvv//i22+/xaJFi/L1xfisogQAbt26hVu3buHSpUsAgNOnT8PBwQGVKlWCs7Oz+jw7d+7ElStXMGTIkOfmmtP4CQkJCA4OxqNHj7BixQokJCSo979zc3ODmZkZAODLL79Eu3btoNFosH79esyaNQtr1qxRlxdk/M2bN+P27dto3Lgx7O3tcfbsWXz44YcICAhA5cqVnxv/zp07GDBgAGJiYuDk5IR69eohJCQkx1/qvr6++PvvvzF16lQ0a9YMGo0GDRo0wNatW3P0hWzK/I3xuXvxxRdhZWWFCxcuoHnz5gAArVaLq1evwtvbOyeb0GSM8dlbuHAh/P39YW9vj23btuHDDz/ErFmzUKZMmRyvR372Pcb4MWwKpv7Oye9rf/DgQRw+fBhBQUFwcHDAwYMHMXr0aPTr1w9ly5Z9bv6m3u8WGKOPUdIzFdTh47ffflucnJxk9+7dEhMTo/6lP1F+6dKlcvDgQbl06ZL8+uuv4uzsLGPGjFGXHzp0SBYsWCAnTpyQq1evyo4dO8Tf31+qVav23HMsjBH/7t274uLiIq+99pqEh4fLhQsX5IMPPhALCwsJDw/PNrZOp5N3331XPD095eLFi5mW628x8d9//xm0BwcHy9ChQ0Xk6etiZWVlcKFJSkqKuLu7GxxWy8rgwYPF29tbLC0txc3NTVq3bi2hoaHq8ilTpgiATH8Zr27s06eP+Pv7PzNWbuPrD51k9XflyhX1OYKCgsTJyUmsra3lpZdeks2bNxda/J07d0qzZs3U+D4+PjJu3LgcHe4pCkyZvzE+dyIi7733nlSoUEFCQkLk/Pnz8uabbxaLc9qM8dnr37+/ODs7i6WlpdSrVy/TRSHPYox9z8aNG0Wj0RhcDCUiUqNGDZkxY0aO10WkcLe/qb9z8vvaHzt2TF566SX1c1erVi2ZOXNmjs8nNPV+N7d4TmERVVBFYXZvwPQ7v3Hjxkm5cuXEwsJCfHx8ZO7cuQbnbZw6dUqCgoLE2dlZrKyspHLlyvLWW2/JjRs3CiW+iMiRI0ckODhYnJ2dxcHBQZo2bfrcD8rzdk4pKSlSvXp1efnll+Xw4cNy6dIlmTNnjiiKYnC1mLG+GIkKi7E+dykpKTJ27Fhxd3cXBwcHeeWVV+TMmTO5Xp+icE5hYTLGvievP4azUpjb39TfOZQ7Oa09FBGRfA01Uq4kJCTAyckJ8fHx6qECyp+spi4Dnp4TqJ+ZICIiAuPHj8e+ffuQmJiI6tWr44MPPkD//v3V/lqtFhMmTMCvv/6Kx48f46WXXsLXX3+tHvYhomfz9Bydr8dHR88z0poUDmPte44ePYpJkybh6NGj0Gq1qFOnDj755BO0b98+V+tT2rY/5VxOaw8WhYWMRSFRweIXo+lw25sWtz9lJ6e1By80ISoA+dk553fHbOovBlPHN7XSnr8pcduXbqV5v2ssLApLKFO/QU0dn6i04mfPdEr7ti/t+ZcELAqpROLOiYiIKHc0z+9CRERERCUdi0IiIiIiYlFIRERERCwKiYiIiAgsComIiIgILAqJiIiICCwKc+XIkSPo0KEDypQpAzs7OzRt2hRr1qwx9WoRERER5RvvU5hDu3btQtu2bWFtbY3XX38dDg4O+OOPP9C7d29ERUVh7Nixpl5FIiIiojzjSGEOpKamYujQodBoNNi7dy9++OEHzJ07FydPnkSNGjUwceJEXLt2zdSrSURERJRnLApzYOfOnbh8+TL+97//wc/PT213cnLCxIkTkZKSgp9//tl0K0hERESUTzx8nAO7d+8GAAQHB2da1rZtWwDAnj17snxscnIykpOT1X/Hx8cDAO7fvw+tVgsA0Gg0MDMzQ1paGnQ6ndpX356amgoRUdvNzMyg0WiybddqtdDp/i9mXsTFxSEtLU39t6IoMDc3h06ny7I947rnN/69e/cAGOaUnrn507duampqlu35jZ+QkJDt65GT1yk/8fW562WXq4WFRZavhzG2Pd97pfO9Bxi+//je43uvuLz3nr5O+dvvFuf33vNep/v37wOAwfpnSei5evToIQDk6NGjWS63t7cXLy+vLJdNmTJFAPCPf/zjH//4xz/+mfQvKirqmfWOIvK8spGCg4Oxbds2REREoHr16pmWV6hQAYmJieooYHoZRwp1Oh3u378PFxcXKIpSoOudnYSEBHh5eSEqKgqOjo6MX0piMz7j873P+KUxfmnOXU9E8PDhQ3h6ekKjyf7MQR4+LmBWVlawsrIyaCtTpoxpViYDR0dHk71BS3v80pw745fu+KU5d8bne8+U8Z2cnJ7bhxea5IB+Q2Y1Egg8/RWQk41NREREVFSxKMwBHx8fAEBERESmZbdu3UJiYqLah4iIiKg4YlGYA4GBgQCA0NDQTMtCQkIM+hQHVlZWmDJlSqbD2oxfsmMzPuPzvc/4pTF+ac49t3ihSQ6kpqaiZs2auHnzJg4dOqTeqzA+Ph5NmjTB1atXceHCBVSuXNmk60lERESUVywKcyi7ae6uXbuGOXPmcJo7IiIiKtZYFOZCWFgYpkyZggMHDkCr1aJu3boYM2YMevfubepVIyIiIsoXFoVERERExAtNiIiIiIhFIRERERGBRSERERERgUUhEREREYFFYamnv86oNF5vlD7n0pZ/ac4dyJx/adwGREQZsSgs5RRFMfgvUHqKhPQ5p/9/nU5nitUpVKUx9/Tva0VRkJKSov6/fhukpaWZZN0KW/rXubR83tNLn39Jfs9npzTmn9X7vLTknhu8JU0plJqaigsXLiA0NBR2dnawsLCAu7s7/Pz8UKFCBVOvXoF7/PgxDhw4gO3bt8PCwgKKoqBKlSp4+eWXUa1aNVOvXoEqzbkDT2chWr9+Pfbv34+0tDTodDrUrl0bHTt2xAsvvKD2ExGDYtnYCvr5c0Kr1cLCwkL9t37EVKMpHWMFCQkJcHR0VP/N/EtH/ikpKYiLi4O7u7tBu06nK/G55wSLwlLmypUrmDt3Lr777juDdhsbG/j4+CAoKAidOnVC06ZNYWtrWyS+vIzp/Pnz+Oyzz7By5UoAgK2tLR49egQAcHJyQuvWrfH6668jODjYYIdpDFqtFmZmZrne8RjrNTBl7oDp8w8PD8cnn3yCTZs2AQBcXV0RGxurLm/QoAGGDh2KXr16wdnZOd/xMkpISIC5uTlsbW1z9ThjfgYjIyOxefNmnD17FpaWlrCzs8MLL7yAoKAgeHh4GCVGUSUiOHnyJH777TdcuXIFWq0WDg4OaNy4Mbp27Qpvb2+DviVpvweU7vxTU1Oxb98+LFq0CDExMYiPj4e9vT1atGiB7t2748UXX1T7loYfhM8kVKr06NFDzM3N5e2335bly5fLihUr5Ntvv5XevXtL2bJlRVEU8fT0lEmTJsmdO3eMHn/OnDmyY8cOefLkidGfOyc6d+4sVlZWMnnyZNm8ebP8+++/8vfff8uIESOkXLlyoiiKKIoiffv2lfDwcKPGnjx5sixZskQuXrwojx49ytFjdDqd0eKbMncR0+ffrl07sbOzk7lz50pYWJhERUXJiRMnZPr06dKoUSM1f39/f/nnn3+MFldv1KhR8vHHH8uOHTvk5s2botVqn/uYtLQ0o8X//fffpVKlSqIoimg0GrG3t1dz9vDwkMGDB8v27dslOTlZRIy77UVEHj16lKfnNNZ6LF68WDw8PERRFHF2dhZXV1c1f0VRpHXr1rJ27Vp5/PixUeJlFBMTo27b3GD++c//iy++UPOtWbOm+jnQ/9WtW1cWLVokiYmJ+Y6VlXPnzsnDhw8N2nQ63XNzM/ZnMCdYFJYiV65cETMzM/nggw+yfLPdvHlTvv/+e2ncuLEoiiKtWrWSiIgIo8bXfwhr164tU6ZMkVOnTmXZV/9lePPmTVm/fr1cuHAh3/GvXr0qGo1GJk6cmG2fTZs2SXBwsJibm4ufn58cPXo033H1sfW5e3t7y9ChQ2Xjxo1y48YNSUlJMeirz/3q1avyzTffyL59+4wS31S56+MXhfynTJmSbZ+DBw/K66+/LhYWFlK5cmUJCQkREePsmNPn7+LiIq+++qp88803cujQIYmNjTXoq48XEREh48aNkz///DPf8a9fvy6urq7i4+Mjmzdvlj179sjx48dlw4YN0r9/f7G1tVWLhQkTJkhcXFy+Y6Z38+ZNGThwoKxfv16uXbuWo+IgJ0VzTl27dk3KlCkjfn5+cvDgQTl37pzcv39fDh48KB999JHUrFlTfX1ef/11uXjxotFii4jcuHFD2rdvL/PmzZP9+/fLnTt3sn1f6dvzUkBlpzTnf/XqVbG3t5fmzZvL2bNn5d69eyIicubMGZk3b560bdtWzM3NRVEUadq0qezZs8cocfWioqKkYcOG8t5778maNWvk4sWLkpqaatBHn7P+vwVVmOcEi8JSZOHChWJjY6OOgmT3obtw4YK88847oiiKDB48ONMbOK+++eYbURRFGjZsaDAy9fLLL8t3330n169fV/vqPxzz588XRVHkjz/+yHf8xYsXi7W1tWzYsEFERC1GdDqdQY4PHz6UOXPmiKIo0r59e6P8evzuu+/UQrtJkyZiaWmp/kKdOHGi7N27V+7evWswMrRw4UJRFEVWrVqV7/imzF3E9PkvXbpUrKysZPXq1SLyf/mnpaVlen//8ccfYmFhIQ0aNDDaaPnixYtFURR57bXXpGfPnur7v1KlStK/f3/55Zdf5PTp05KQkKA+5vvvvxdFUeTnn3/Od/zJkyeLu7u7bNq0KcvlKSkpsmzZMmnQoIFoNBrp3r27UY8UTJo0SRRFETMzM/H19ZWxY8fKjh075Pbt29l+QYaEhMjMmTPl5s2b+Y7/ySefiLu7u2zdujXbPv/884+0bNlSFEWRli1byuXLl/MdV2/y5MmiKIpYWFiIp6envP766/LTTz9JeHh4pgJcn//69etl6NChcunSpXzHL835f/rpp+Lq6irbtm0TkaxH3/ft2yc9e/YURVGkXr16cvz4cYN1yY8pU6aIoihiZWUldnZ20rx5c/VozY0bNwz66uP9+uuv0qZNm2wHTQoSi8JSRP/FtGvXLhF59hv+8ePHMnToUFEUxSijdCIi77zzjmg0GgkLC5Pz58/LZ599Ji1btlRHKWxtbaV79+6yZs0aefjwoaSmpsrrr78uiqIYpThZt26dKIoif/3113P7pqWlqV9khw8fznfs0aNHi6IocujQIYmOjpalS5fKoEGDxMfHR91htGzZUubMmSOnT5+WW7duqTup4p67iOnz37FjhyiKIkuWLMm2T2pqqvqZ+Oqrr0RRFNmyZUu+Y4uIfPTRR6Ioihw4cEASExNly5YtMnXqVGnZsqU4ODiIubm5vPDCCzJq1CjZtGmTnD59Wrp37260/Fu3bi3169dXCyz9KFzGovjKlSvSv39/URRF5s6dm++4eoGBgWJjYyO9e/eWOnXqqAWCv7+/zJo1S44cOSJxcXHqujx58kS6dOkiNjY2Rhk16dixo9SqVUuioqJERNQ4GfPXarXqe3/MmDH5jqvXpk0bsbW1ldGjR0vbtm2lTJkyaoH8zjvvyLp16+TixYvqa52amiqvvfaaWFpa5vhUi2cpzfn37NlTqlatKlevXlWfW+Rp7hkLxB9//FEURZEePXrkK2Z6HTt2FDs7O/niiy9kyJAh6qFrNzc36dSpk8yZM0f27dtncMSgZ8+eotFoJCkpyWjrkVMsCkuRkydPiq2trbz88svqYeGMI0Ui/zeKsnbtWjEzM5Ply5fnO3Z8fLx07NhRFEUxKEaTkpJk+/bt8sEHH0iDBg3U0UNPT0/p0aOH2NnZSceOHfMdX0Tk8uXL4uzsLLVq1ZIDBw6o7emLAZH/+8LcunWrmJmZybfffpuvuAkJCdK1a1dRFMXgXMonT57I0aNH5euvv5Zu3bpJ+fLl1UN4rVu3FktLy2Kfu0jRyD8mJkYqVaok5cuXlz///DPbQkOf/549e8TS0lK+/PLLfMdOSkqSwYMHi5WVlcGoiFarlUuXLskff/who0ePlgYNGoilpaXY2tpKw4YNRVEUefXVV/MdPyUlRYYOHSr29vY5KrASExPFz89P6tevL/Hx8fmOHx0dLfXq1ZN69eqJiEh4eLh8++230qtXL6lYsaIoiiKOjo7SqVMnWbRokURFRcnOnTulfPny0rZt23zHF3lalJuZmWUamUlPXyDodDpp1aqV1KxZ0yijlLdu3ZKGDRuKj4+PiDwtvP/66y/56KOPpHHjxmJtbS1WVlby0ksvycSJE+Xff/+VP//8U9zd3aVdu3b5ji9SuvOfOXOmKIoix44dy7ZPamqq+tnv0aOHeHt7y/nz5/Md+/bt29KkSRPx8vISEZH79+/L0aNH5bvvvpPOnTuLi4uLKIoiVapUkb59+8qKFSvk559/Fjc3N2nfvn2+4+cFi8JS5NGjRzJs2DD1MNaJEycMlqelpRkUCMuXLxdzc3N12D0/UlJSZMGCBdK/f3+5f/++6HS6TL/Sbt++LWvWrJE33nhDqlWrphaIxjrpPy0tTaZOnSqKokhAQIBs3LjRYHnGkdOff/5ZzM3N1XPL8hN3xYoVMnDgQPWQXMbcHzx4IDt27JBPP/1UWrdurV4EsHnz5nzFTr8OpshdH9vU+YuILFmyRBRFkapVq8qCBQvk9u3b2fb9+eefxczMzCgjhTqdTv7++28ZO3as3L17V21LLykpSU6ePClLly6VN998Uz28bKz8f/31V1EURfr376+OmGT8QZj+Mzl8+HBxcXExylGCY8eOiZWVlXTt2tWgPSEhQfbu3SszZsyQNm3aqBe6VahQQZo0aSKKosjff/+d7/giTw+NKooibdq0kWPHjmV5Skz6/MeMGSOOjo5y5syZfMf+77//pGLFitKtWzeD9sePH8uZM2fk119/laFDh0qNGjXEzMxMypYtK7Vq1WL+Rsr/33//FY1GI35+frJt27YsRx7TX/QxefJksbW1VQ8h58fly5fFz89PunfvbtCempoqMTExsmfPHvnss8+kefPmYmNjI5aWluoPJWO99rnForCUSUlJkVGjRqkFV/v27WXVqlUG5zKJPP11FxgYKO7u7kaNn5ycnOkLMatzPMLCwsTHx0fKlClj1PgiIl9++aX6C61+/fqyYMECiY6OFhFRh+svX74sL730knh4eBg9fnpZ5X7q1Cl54YUXxMnJyejxilLuIoWf/++//65+4fj4+MjEiRPlwIEDcuPGDYmOjpbk5GQ5duyY1K9fX/11X5CyOoXj4sWL8uKLLxo1/7t378orr7wiiqJIr169nnkR0YMHD2TQoEFSvnx5o8ROSkqSTz/9VBYtWiRarTbLqy5v3bolGzdulPHjx6tXgpctW9Yo8UWe7nf69esniqJI8+bNZd26ddkelo+Li5NBgwaJm5ubUWI/fvxYFixYICtWrFBHozLmHxcXJ4cOHZLFixdLly5dmL+R8x8/frz6g3Du3Lly/vz5LEfN4+PjZeDAgeLi4mKUuMnJybJy5Ur5888/s71w6smTJxIZGSkhISHyzjvviKWlpVFzzy0WhaWI/gv49u3b8vXXX0vVqlXV4tDOzk7atGkjEyZMkF69eomnp6fY2dnJV199VWjrp9Pp1Itfdu/eLQ4ODvLmm28a9flFno5QrFq1Slq3bm1wW4ImTZpIv379pEWLFmJraytOTk5GOXwqIjm6WEd/2H7Hjh1ia2tr1Nz1r318fLysXLlSWrVqVWi5i0imK4yf1acg8te/9ikpKbJjxw4ZPHiwwcVONWvWlBYtWoivr68oiiLlypWTn376yWjxc/L66780QkNDxcrKyqj5izx937/55ptqzi1btpQVK1ZIbGysPHnyRO7fvy8iTy9wcXR0lLffftuo8bOS1Y+CpUuXiqIoMnz4cKPHmzp1qnprkoYNG8rs2bPl6NGjcuXKFYmKipLHjx/LrFmzxN7eXt59912jx88oqx8Fq1atEo1GI8OGDTN6vNKc//Lly9WrrH18fGTUqFGybt062b9/v5w/f16io6Plo48+Ejs7O3nvvfeMGjunNmzYIJaWljJ06FCTxBdhUVhqZHdRyZ9//ildu3YVV1dXMTMzUy/6aNSokaxevdpoJ7pmd7+17NZr7NixoiiKHDlyxCjxs7Nnzx557733pFGjRuo5Z+bm5tKhQwcJDQ3NUTFjbJ9++qkoiiJhYWFGeb7stvHOnTtl5MiRBZ57dvGze08YO//sHDt2TGbNmiU9evSQZs2aSY0aNcTNzU3eeOMNCQsLM8k9wkRE5s6dK2ZmZkbNX19wRkVFyVdffSX169dXi0MLCwsJCAiQV199VapXr66OJhnjqleRp6//824vk370cOLEiUb/7Ovfa3FxcbJq1Srp0qWLODg4iKIoYm5uLrVq1ZL69eurBVP79u0lMjLSKLGzOlUmqz76/PUXJRkzf/1n+f79+/Lbb78Vev7ZjRCm71NQ+eufNzU1VXbv3i3vvfee+Pr6ipmZmZiZmUm5cuWkbNmy6ndf7969De6Ekd/YudmPFNb33rNwRpNS5ObNm6hQoQIeP34MrVZrMGtFYmIijh8/DgCoUKEC7O3tUa5cuQKJn5KSgtTU1GxndhAR/PPPP1i3bh2WL19u1HXQP79kmM7pyZMniIiIgI2NDcqWLQtra2vY2dkZPXZO7N27F1u3bsXMmTON9pwRERFwd3dHXFwcrK2tDV7bR48eISIiAnZ2dgWWuz7+w4cPYWNjAxcXl2z7FkT+6WWcziolJQW3b99GmTJlYGFhASsrK5POOHDixAns378fI0aMKLAYycnJ2Lp1K/7++2+cPHkSCQkJePjwISwtLdG3b1+8/fbbqFixYoHFB7KeViwmJgZ9+vTB9evXERkZWWCxtVotDh06hJ07d+L06dO4d+8eYmJiUKZMGfTu3RuDBw+Gk5NTgcXPzt27dzFs2DCcO3cO58+fL7A4KSkp2L9/P3bv3o2zZ8+aJP+sXv/CyD8tLQ1nzpzBkSNHcP78ecTExODy5cuoVKkSOnTogH79+sHc3LxAYj/LgwcPMHbsWBw9ehSnTp0q9Ph6LApLOBHBpk2b8NNPP+H06dNITExEvXr1UK9ePTRo0AB169ZF9erVC6wAelb8hg0bokGDBqhWrRqsrKwKdPqftLQ0aDSaTM+flpYGRVEKdM7L7GIXtOTkZKxduxbfffcdTpw4AY1GAx8fH1SvXh0NGzZE06ZN0aBBA5QtW7bQ47/44osICAiAn59fgUyppyciSEtLg5mZWabtr9PpoChKpnZjvg+fFb+w3LlzB3fv3oWLiwvi4+Ph6upqUJQ/ePAA0dHRahHo6Oho1HVNHz8xMRGurq4oU6ZMln317xlra2v06NHDaOugl9UPwqSkJCQmJqJcuXJITk6GlZWV0ePmlFarxY4dO2Bubo5XXnkl38+XlpaGiIgIPHjwACICnU6HqlWrwtPTU+3z8OFDJCYmwsPDw+j5p4+vV7Vq1WwHHIydf0YZP9spKSnQaDQwNzdXP6emkpaWhhMnTkBE0LhxY5OtB4vCEu6TTz7BnDlzYGtrCy8vL2i1WqSkpCAqKgoigvr166NHjx7o378/ypcvb7L4AwYMMNhRGOsDGhUVBS8vL/XfOp0OIpLlcxu7KM1N7PRSU1ON8kt17NixmD9/Pry9veHj4wMLCwvExcXhzJkziI+Ph5eXF1599VW88cYbaNSoUb7j5TX+4MGDDeYeNdZrf/nyZVSrVk39t06ng06nK7RRAFPHj4mJwaRJk7Bt2zbcvHkTDg4OqFKlCnx9fdGkSRP4+/ujXr166oi9sd//z4rftGlTNG/eHHXr1i2QIkyfy7O2ecYfBfrHGGM75CR+Qbtw4QImTJiAzZs3IyUlBVZWVihbtiy8vb3RtGlTBAcHo3nz5nBwcACQ9chdQcX39/dHu3bt4O/vb5IjMhlzNeZrX+wV/BFqMpUrV66Ira2tdOjQQc6dOyciT69CPH78uKxdu1ZGjhwpNWrUEEVRxM/PT739hbHmWy0K8RVFkbZt28ry5cszTSeWmppqcG8uEeNNrWTK2CIikZGRYm1tLT179lRvA5OQkCDXr1+Xw4cPy5dffin+/v7qlG76WTOMdR6dqeNfunRJFEWRWrVqyZdffikxMTEGy1NTU9WLP/QxExMT5datW0aZXs3U8WNiYqRp06bq+WE9e/aU3r17S9OmTdVzp+rUqSNTp041yr3o8hNff/W7SM7Ov8uJ+Ph4uXbtmkFb+m1e0Ewd/+bNm1K3bl3RaDQycOBAGTt2rIwbN05effVVcXJyUq/uHTx4sBw6dMik8dPfID+35+Bl5f79+7J7926De6IWJlPHzy8WhSXYtGnTxNnZWbZv3y4imecSjY+PlwMHDsj7778viqJI+fLlM927sDjH19+0VP/n6uoqAwcOlH/++SfTuugLskWLFknr1q3zfX82U8YWEZkxY4Y4OzvLjh07RCTz1a9arVYiIyPl66+/Fjc3N1EU5ZlTYBW3+LNnzzbY/umvts14AU367d+kSROj3J/M1PE/+eQTcXJykq+//lpte/DggURFRcnevXvl448/ltq1a4tGo5FmzZqp80sbqyg3dfwxY8aIojydQnPp0qWZLpjTarWZis+YmBi5ffu2UdbB1PE//vhjKVu2rMEMPsnJyZKSkiLXr1+XxYsXS0BAgGg0Gqldu7Y6/aGxtr8p43/wwQfq1dXTp09/5r0W9fEuXrwo4eHhRrm4ztTx84tFYQk2YMAA8fDwkFu3bolI5km30/v999/FyclJmjZtWmLiv/rqq+Lg4CBLliyRgQMHqiMUiqJI9erV5YMPPsh0hedrr71mlKnFTBlb5OmUgmXKlFGntXrWzjY0NFQ8PDykZs2aRvt1a+r43bt3FxsbG1m5cqV88sknUrt2bYOrbV9//XW1YNUz5vY3dfzatWvLq6++qo7SZtz+T548kZMnT6rFi6+v7zNv5l3c4tetWzdTUd6tW7dMN8JPf5uqvn37Stu2bY0yUmvq+PXr15d27dqp2zSrz9/du3dlwYIF4uzsLA4ODvLff//lO25RiO/n5ycajUacnZ3VbR8UFCSLFy/OckaXxMRE6dOnjzRt2tQoRZmp4+cXi8ISbM6cOaIoiqxdu1Zty/jrNP2H9Y033hBXV1ejTO9j6vh37tyRJk2aSIUKFdS2x48fy2+//Zbp/oSNGzeWb775RtasWSMeHh7SqVOnYhtb76effhJFUeTbb781uCVDdsXZhAkTxN7e3iijVKaOf/fuXfH39ze4+XJycrJs2bJF3nzzTfHw8FC3v5ubm4wfP15WrFhhtO1v6vi3bt2SWrVqSZs2bZ7bV6vVyjfffCOKosi4cePyHbsoxL98+bK4ublJYGCg7N27V95++211vln9Yct33nnH4L124sQJKVu2rAQGBhb7+LGxsdKoUaMc/cDWarXy+++/G/W+kKaMf+XKFfH09JSmTZtKeHi4TJ8+XVq0aCHW1taiKIo4ODhIr169ZMOGDXLv3j0ReTpRgrOzswQFBRX7+MbAorAE27t3r9jb24uvr2+m+x6lP3dH/9+ZM2eKnZ2d0e6PZsr4169fl5dfflmdOzfj+XrR0dEyZ84cg1/0+g9ufqfVM2VsvdOnT0uFChXE2dk503RJ6ac302/7r776SqytrQ3mRS6u8W/duiXt2rWTNm3aiFarzfTr++7du/LLL79I586dxc7OzqBIN8b2N2V8/eeqR48e4ujoqJ6vldUc5+nVrVtXWrVqJQ8fPizW8UWejjwriiJjx45V2+Li4mT16tXSs2dP9Zw2RVGkWrVqMmvWLBk3bpwoiqIexiyu8fU/uoYOHSqK8nSqNP2PsWeNQAYEBEjjxo3VQqW4xt+5c6doNBoZNWqU2vbw4UMJCQmR0aNHS7169dRtX6FCBXn//fdl+PDhRnvtTR3fGFgUllD6D+ePP/4oZmZmoiiKDBs2TLZv355pSjuRp/Mi9+nTx2jT+5g6fkpKiuzcuVMOHDhgcEFH+gs89C5cuCDvvvuuKIoizs7OxTq2PpaIyJYtW9R5NNu2bStr1qxRZ61ILzExUXr16mX0195U8UVEIiIi5MyZM5m2f8aRyuvXr8u0adPE1tbWqFNLmTr+Dz/8oJ7TlvGcprS0NIN1iY+Plw4dOsgLL7xQIuIfOHBAvLy85IcffhCRzOcyX7t2TRYsWCAtW7Y0KMiNtf1NHV9EZPPmzaIoitSoUSPT/OX6C1702z8uLk66du0qNWrUKPbxw8PDxcfHR7755hs1VnoxMTGyatUqGThwoFSpUsXo297U8Y2BRWEJl5iYKN9//724u7uLoiji7u4uXbp0kZkzZ8r27dvl/v37cvjwYRk+fLhYWloa/LotCfGfNZOKVqtVP7RhYWFia2tr1KmVTBlb5OmX0bp16wx+ndavX1/effdd+eOPP+TcuXOyfv166d27t5iZmcn48eNLVPzs6As0/fY/ePBggWx/U8efNWuWaDQaURRFBg4cKCEhIQbzveq/lLdv3y4VKlQw+tRapoqfkpIiZ8+eVc9l1sfKaqTy4sWL6pzAxprWzdTx9X777Td1KsegoCBZvXq1wfmq+u3/zz//iKenp9Fff1PFT0hIyPTjM6t98c2bN2XEiBGiKIq88847RoldFOLnF4vCEirjiERiYqJ8/fXX0qxZMzE3N1e/pDUajVhaWoqiKPLGG29keSJscYyf/nYfObkNhP7DefTo0WIdOzsbNmyQjh07Ztr2iqKIpaWljB492uBLrKTFfxb9SG1Bbv/CjK//7D148EDmzp2r/iAzNzeXl156ScaMGSN///237N27V+bOnStVqlQRV1dXOXXqVImIn5P1S/+5nDp1aqG+/oUV/8mTJ/Lbb7/Jiy++qH7mypUrJ7169ZIff/xRfvnlF/noo4/ExcVFPD09n3mVbHGMn5WM2/6TTz4x6Wtf2PFzgjevLmViY2Nx8eJFHDp0CP/++y/S0tJQo0YN1KpVC2+++WaJj5+VhIQEDB8+HLt27cKtW7dKTGz5/zMYpL8R9K1bt7Br1y7s378fFhYW8PT0hK+vLzp16mTU2EUhfk4kJSXh3XffxebNm3Hnzp0SEV8y3ID3yZMn+Pnnn/HLL7/g4MGDmfrXrl0bEyZMQN++fUtEfP2NiZ91E3T9Ol68eBGdOnVCamoqLl++XCLiZxXr77//xg8//IDQ0FCkpqYaLG/WrBk+/vhjtG/fvkTGz05kZCS6du2Khw8f4sqVK4UauyjEzw6LwhLozp07OH36NC5evIjExEQ0adIEvr6+cHV1zbSTyjitUcYdekmK7+Lios4skHGHnZycjDt37hjMQFLcYgO5m5Ug43oYY9sXp/jpJSQkGGW6PVPHf57r169j+/btOHPmDMqXLw93d3c0b94c1atXL/DYRSF+RhcuXEDXrl3RqVMnfPHFFyUqvmQxpV98fDx2796NyMhIeHp6wt7eHo0bN4a7u7tRYxeF+M9z5coVDB8+HIGBgZg0aVKpi58dFoUlzJYtW/DZZ59l+kXu7OyM1q1bo3fv3ujUqRMsLCzUZcac3qgox3/llVfU+AUx7ZQpY2clu+2afi5mY02pV5zip5eamgpFUQpkzlNTxN+6dSvOnDmD8PBwlCtXDo0aNUL16tXh5eUFFxcXg89dQShK8d3d3dG4cWNUr14d3t7ecHFxgZmZWZY/Poz1PjR1/OxGJwtjjndTx8/r9JjGmlbT1PGNpvCOVFNBu379ulStWlXKlSsn48aNk61bt8p3330nQ4cOlSZNmqi3PalTp4789ttv6q1SjHUX++IS/4UXXjCIb4xptUwZW+TpbVDGjBkjW7dulQcPHhgsM8bUUYxftOM/ePBAPvroI/XcvfRXtbq4uEjnzp1l2bJlmW75Yaz1Ki7xM742xpp2ztTxs7r/a1b7lvTtz7tNTHGJn9PYGRlrWlFTxzc2FoUlyKRJk6Rs2bLyxx9/ZFoWFRUlq1evlr59+6o7q9mzZzN+CYgt8n8nLFepUkU6duwoX375pYSFhWWaIUR/OxARkV27dsmWLVsYvwTE/+KLL8TW1la6desmu3btkgsXLsjvv/8uU6dOlVdffVWdSrBhw4ayYcMGo8Rk/KIT/7vvvpNevXrJpk2bMt3rMS0tzWg/Poti/NKce0FgUViCvPTSS9KyZUu5e/euiIjBbU/S27lzpzRo0ECsrKzkp59+YvxiHlvk6dRKlpaW0rRpU/Vq7sqVK0vfvn1lyZIlcu7cOYP+SUlJ0rlzZ9FoNAa3CWH84hnf29tbOnbsKLGxsZmW3bx5UzZt2iTDhg1TR7F+/PHHfMdk/KITv3LlyupN8F966SWZPHmyHDx4MNNIrH5kLikpSebNmyc7d+4s9vFLc+4FgUVhCfHw4UN55ZVXxNfXV518Pf0vlIxD2sePH5eyZctK586d1eWMX/xiizw9dF25cmV58cUXJSUlRQ4ePCiTJ0+W+vXri6IoYmZmJvXq1ZMRI0bImjVrJD4+XsLCwqR8+fJGmVaN8U0b/9y5c2Jvby8TJ05U27IaoUhOTpZ//vlHqlatKs7OzkabvYbxTRv/zJkzoiiKNGrUSNq0aaMejbC3t5e2bdvK/PnzM/0o+ffff0VRFAkICCjW8Utz7gWFRWEJop8qKasRqPSFh35n1aVLF6lRo4ZcvXqV8Ytx7MOHD4uzs7MMHDhQRESdOeX27duyZcsWeeutt8Tb21sURRFbW1tp0aKFOgdzxinoGL/4xf/vv/+kYsWK0rt3bxF5OiKR8UdJ+vfgn3/+adRTGBjftPFXrVoliqLIV199JSJPZ0maPXu2+Pn5qUWKh4eH9OnTR3755Re5f/++zJ07VxTFOFOrmTJ+ac69oLAoLEFu3Lihzqc7cuRIOXbsWKZDU/oh7Pj4eOnZs6dUqlSJ8Yt57IiICHnttdfkt99+y3J5SkqKXL16VX799Vfp1auXODs7i6IYb2olxjdtfJGnpy84ODjI5s2bMy3TFyT6QuXevXtSpUoV6dGjB+OXgPiLFy8WRVGyjB0WFiajR48WLy8vtUipUaOGlC9fXpycnIp9/NKce0FhUVjCbNiwQZ1TsVGjRjJ9+nTZtWuXXL161aBIWbFihbi5ucnw4cMZvwTEjouLy/J8pvT0X0qLFi0SRTHu1EqMb5r4+oLj8OHDUqFCBVEURd5//305fPhwph8l+oteDhw4IJ6enjJq1CjGLwHxDx48KKNHj5ZLly5lWi+9x48fy6ZNm2TgwIHi5OQkiqLIiBEjinX80px7QWJRWAJkfBPeu3dPPvjgA6lUqZIoytP5hlu1aiX9+vWTYcOGSf/+/cXKykp8fX3l/PnzjF9MY2cVX+T/Dl9m58MPPxRFUeTYsWOMX8zjp4+5fPly8fDwEEV5etun0aNHy9q1a+Xs2bPq+ty4cUP69Okj5ubmjF+C4j98+DDbW5xkfI/qp1U8ceJEiYhfmnMvCCwKSwj9my8qKkrdAZ0+fVo+//xzadu2rVqkKIoizs7O0qpVK6PONVma4xeV3GNiYjIVI6mpqQY7pqioKKlXr564uroyfgmJn96dO3fkk08+EV9fX9FoNGJvby81a9aUF198Udq0aSNeXl5ibW0tb7/9NuOXwPjZ0b8HL126JC+++KJUr1691MQvzbnnBWc0KeZSU1Oxf/9+LF26FBcvXoSiKLC1tUXjxo3Rq1cvNGjQACKCqKgoPH78GJGRkfD19YWXlxfMzc3zPbVYaY5f1HLXaDSwsbFB/fr10b17d/j7+2d6TGxsLH799Vd4enqid+/eeY7N+KaPn56km2f68ePHiIiIwJEjR7B//34cPnwY58+fh5ubG7y8vDBkyBD069cPdnZ2jF9C4ufUpk2b0LlzZ3z44YeYPXt2qYpfmnPPFVNUomQ8X375pTg6OoqiKOLj4yO+vr7qqJT+MMa3334rt2/fZvwSFDsn8WvVqiVfffWVxMTEGDwuOTnZKDdUZXzTxn+etLQ0SUpKEq1WK7GxsUYdnWb8ohU/p7e1unXrlixfvjzTzDLFOX5pzr0gsCgsxiIjI8XOzk5efvlliYyMlBs3bohWq5WoqCj57rvvJCgoSP2CatWqlRw5coTxS0Ds3MZv3bq1Uc9fYnzTx3/06JGcP39eHj16lGlZWlqawRdVxi8tYxSkjF904z+PMabWM2X80px7YWBRWIxNnjxZ3N3dZfv27Wpbxh3QqVOnZMCAAWJtbS01a9aUo0ePMn4xj53f+MaYb5bxTRv/888/l0aNGsnMmTNl586dcvPmzUxfOBnvj3fnzh2jzXXL+EU/fkYlJX5pzr0wsCgsxl577TWpWrWqXLt2TUT+7z54Op0u05v066+/FkVRZNCgQYxfzGMzPuPrb39ibm4uLi4u0qlTJ1mwYIGEhYVleWucxMRE+eCDD+SNN94wykgV4xff+MYYrTJl/NKce2FgUViMTZ8+XRRFkbNnz2bbJ/0v1e7du0ulSpXk8uXLjF+MYzN+6Y5/4cIFsbe3F39/f1m4cKF06dJF3N3dRVEU8fb2loEDB8qvv/4qZ86ckQcPHoiIyKFDh8TJyUm6dOnC+IxfbOOX5twLC4vCYmzfvn2iKIr4+fnJjh07srxXUvqRi4kTJ4qtra2cPHmS8YtxbMYv3fH//vtvMTc3l08//VRERK5evSohISHy6aefSosWLcTe3l7Mzc2lXr168v7778vWrVvVeyMaY2otxmd8U8UvzbkXFhaFxVhqaqqMHTtWvdJx4cKFcuvWrSz73r9/XwYMGCBubm6MX8xjM37pjr927VpRFEVWr15t0J6SkiIRERGybt06ee+996R+/fpiaWkpdnZ2Ymtra7Rp9Rif8U0VvzTnXlhYFJYAixYtkmrVqomiKFKhQgUZMWKE/PPPP3Lq1Ck5e/as3Lx5U8aPHy/W1tYyZswYxi8hsRm/dMbX6XTy33//SWRkpPrvjBITE+X48eOyatUqCQ4OFkV5Oic34zN+cY5fmnMvLCwKSwCdTicXL16UDz/80GDy7XLlyknFihXFzMxMFEWR//3vfxIVFcX4JSQ24zN+VuuT0ciRI0VRFDl+/DjjM36JjV+aczcmzmhSwiQlJSEsLAwbN25EdHQ07ty5A0dHR/Tq1Qvdu3eHtbU145fA2IzP+OnpdDpoNBpcvXoVXbp0wYMHD3D9+nXGZ/wSH780524M5qZeATIuOzs7BAUFISgoCFqtFhYWFoxfCmIzPuOnp9FoAAA3b96EVqvFO++8w/iMXyril+bcjYEjhUREJZSI4MaNG3B2djbJXLuMz/imil+ac88PFoVEREREBI2pV4CIiIiITI9FIRERERGxKCQiIiIiFoVEREREBBaFRERERAQWhUREREQEFoVEREREBBaFRERERAQWhUREREQE4P8BEhaf6ejiuZ0AAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot_histogram(counts_without_qiskit_convention, color='midnightblue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'1100': 7852, '1001': 7791}\n"
+     ]
+    }
+   ],
+   "source": [
+    "possible_results = filter_values_above_average(counts_without_qiskit_convention)\n",
+    "\n",
+    "print(possible_results)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "List 1: [['X', 'O', 'O'], ['X', 'X', 'X'], ['O', 'O', 'O']]\n",
+      "List 2: [['X', 'O', 'O'], ['X', 'X', 'O'], ['O', 'O', 'X']]\n"
+     ]
+    }
+   ],
+   "source": [
+    "completed_lists = complete_lists_with_dictionary(challenge, possible_results)\n",
+    "\n",
+    "for i, lst in enumerate(completed_lists, start=1):\n",
+    "    print(f'List {i}: {lst}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Printing all possible valid results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Challenge:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X |   |  \n",
+      "---------\n",
+      "O |   |  \n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 1:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | X | X\n",
+      "---------\n",
+      "O | O | O\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 2:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | X | O\n",
+      "---------\n",
+      "O | O | X\n",
+      "---------\n",
+      "\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Challenge:')\n",
+    "display_board(challenge)\n",
+    "print('\\n')\n",
+    "\n",
+    "for index, lst in enumerate(completed_lists):\n",
+    "    print('Solution {}:'.format(index + 1))\n",
+    "    display_board(lst)\n",
+    "    print('\\n')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Post quantum analysis"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It is evident for us that there are only two ways to win if we play as 'X'. The first is with the move |1100>, and the second is with the move |1001>, as shown in the results obtained by the implemented Grover's algorithm. Furthermore, we observe that for both winning plays, the 'X's played in the first available position. This implies that making this move increases the probability of winning, which makes sense since having this move with the 'X's provides two winning options in the next turn. However, if we analyze the 'O' move, meaning if 'O' plays in the third available position, then a guaranteed win is ensured, as the subsequent moves of 'X' become irrelevant.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div>\n",
+    "<p style = 'text-align:center;'>\n",
+    "<img src=\"../Images/best_play.png\" alt=\"JuveYell\" width=\"100px\">\n",
+    "</p>\n",
+    "</div>\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Bonus"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "X | O | O\n",
+      "---------\n",
+      "X |   |  \n",
+      "---------\n",
+      "  |   |  \n",
+      "---------\n"
+     ]
+    }
+   ],
+   "source": [
+    "challenge_bonus = [['X', 'O', 'O'], ['X', ' ', ' '], [' ', ' ', ' ']]\n",
+    "display_board(challenge_bonus)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+r6CNlAMDzYBwSKqqnKL2rnPcyAEpFUsGSPHlQKZlwOC8Qv2/v66Ja9u/v+//6tWN/y/BLUqsq6d/XbfO+3afj6ViLvDcv/2HfvKV/xFla5EKzAXO9pW5j2j+Jd+Mebtj9b0qK6tIfIMS7J/vfE9D/CV9PpbsuYAsaca0mToeaIy+wUgq5gJny/Jm69/v2xvXto89/M/65TtPJbZBCfbZyV/RHZ/7pz4fS8Vc4IX/XKEf3vq30TUWKeHWuYCVmys984PEvZ5lKfRP35N6e6TR5Qr/7OfyXnG5POePStg+JlZOlKfbweUePlZccL6+e8e7cW17z9e/pTff/0mCW5Rcpr8Xmt5/ZLbTV+2bO3duTO9NpzOmQBYM2usIdHR09Pn48uXL1dzcrIKCAo0dOzbm16+pqdHNN9981s+nTJmimpr4DrZJnwTPQLVP6rvfkj0J9hVE9zoeb/TPPV1nR5caGhpi3xBJ094e/bohnZ2dp77Hsl2m/ZuHeuJbIy0ve3BG9DXL03/kR5sD8WaAJB053KyWgMOXs+KUWMayFF8OZMK4ON2wwvjXSezu6E37/gbG97+mUirmAt2dPWn/OzINc4Gz9XTHt1xMljdbhw81qyfWNVpTzHuOj3+pmAs0HzmqpmOZ9X/CzZgLnG2wrzDubXu6Qmnf37by/i+RTclcoDv950umce1cwJennAS+XPjlVbK2vi/v12+Xd/Zl6r3nbxT6p+8p66kl8ng8CdnHwcaDUqfz8wjviL5Pqo1GZ3vmzfdNfy80vf9wj0OH4r+E1ZgC2ciRI3X8+HFt2rRJs2fPPuOxxsZGPfTQQ5Kk6urquN7cjh8/riFDhpz18+LiYn344YdxtVmSRo0alZAryAb5ff0+Fs0a5Hl+exJshe2bdcb6WrmDclRaWhp5R0iZwYMHR/1cn8936nss22Xcv3lWfAfFOrrbMqKvveFu5arvLIiUAwPNAEkaPqJY/qJEfkzBQMQylqX4ciATxsXp8nJi+52cLjsv/fvr9w/q97GUzAV82Wn/OzINc4GzebLjWw+4p7dT55UMT3BrEi9k9b/GYSrmAsOGD1XWIOfPjoeNucDZPB6vwlZYXk/sn8G9uVba9ze/oP9/t1TMBXJyvWn/OzKNW+cCVm6ujiTqtRoaFP7RMnkumCjvl2+SJytL3lsXKvzj/1D45VXK+uIXErKf80ednxZXkBV8/G9rWVbMx0dzfZk3xk1/LzS9/8hs4XD41MVFJSV9r5IRDY9lZcJt5Qfuvvvu0/e//32Vl5frjTfe0MSJEyVJGzZs0G233abdu3erp6dH99xzj5YuXdrnazz66KN67LHH1NevLDc3V4sXL9bjj5+5jOCiRYv09ttvx1QkCwaDys+3z9gIBALy+yOscxCFph3SB6vj337uN+wzxDrbpLeeiX37C66Syi+Kf/9IvFjWC96+fbtuuukmrVixQlOmTIl6u6qqqnia5pjm3dKWl2LfbuQkaep1iW9Por39Y/teSfEYaAZk5UpX/o2UoJPrkACxrhkeTw5kWgZI0oafSa0HY9/ustul/BGJb08iHamTtr4c//YDzYEJn5UqLo1//0g85gJnO35Aem957NsNHy/N+GLi25No7/5UOtEU37YDzQBvlnTlffZ3pAfmAn3btEI6tjf27WYulIoSt9paUhzbJ216Mf7tB5oDYy+Txs+Nf/9IPLfOBYKhXg1d89sBv44VDiv0dw/J+qhO2f/6fXk+vq2KFQopdP/fydq3X9nP/L+ELLV4/Kpr5M9y/joGy5LW/4cUaI592zl/JQ0akvAmJZXp74Wm9x+ZLVE1FHfeUbIPixcv1rBhw3TgwAFNmTJF06ZNU2VlpWbNmqVx48bpqquuknTm/cdiMXToULW0tJz182PHjqm4uHggTU+IgviLqInZ/0hn94+BmThxotatW3eqsOxWwyqkQUWxb1c2I9EtSY5CB3OgsITiWKYzJQfiGc9DytK/OCalwVzA4f1jYEzJgCFlkn9Y7NuVz0h4U5LCyblA/giKY5nOlByIZy5QUCIVZsBnXqffi53ePwbGlAw4XXjFS7Jqdsh7+62nimOS5MnKUtZ/+zspHFLon77X54n0mcrjiS8Hh4/LvOJYPEwcB6czvf9wJ2MKZGVlZVq7dq2uu+46+Xw+7d27V8XFxXrmmWe0evVq7dy5U1L8BbJJkyb1ea+xmpoaTZo0aUBtT4TBQ+0rOBzhkQoy4MAh+peTk6Pi4mLl5Lh7eTyPN/arG4aUSUXnJ6c9ieZkoZoPw5nPlBwomWi/Z8YiU66KysuXcuNfRXLAyIHMZkoGeDz2FQ6xKCyRiiuS0pyEYy6AgTAlB4aPi/3El7GXZsbJYDm++E4ITBQni/QYOFMy4CRr/36F/+Mn8kyqkvdLf3HW456KMfLeulDWtg8UfnmVAy1MnpGTY7zPoEcaMzNpzUkrpo2DTzO9/3AnYwpkkl3EeuWVV9TW1qa2tjatX79ed911l4LBoPbu3Suv16upU6fG9drXX3+93nrrLdXX15/62fr167Vr1y4tWLAgUV2Im8cjDR/rzL6Ly6UscjOj7d+/X3fffbf279/vdFOS7vxp0uhLonuuf5hUfUNmfBiWnMsAyT7QgMxmSg54s6UZX7KLSdGYOM/ZsRULj0ca5tBYLBol5fZ/CzRkAFMyQLKXTh47O/LzJPtM6elfzJy5wLAK59rKXCDzmZIDXq+9ZKqvMLrnj/+sdF4GnUjv1FjMHy7lxXLAHWnHlAw4yTN6tHJW/5ey/+W78mT1fQl01le/opzfvJqw+5Cli+xc+zNRTpTz90mfk4aWJ7dN6cK0cfBppvcf7mRUgaw/27dvl2VZqqys7PMGgytWrNCKFStOXSF28u8bN2489Zy77rpLo0aN0he+8AW98sorWrFihb761a9q1qxZ+sIX0uON0qll4DJl+Tn0r62tTW+++aba2tqcbkrSeTxS5RX2ffP6u9LC47UPnl3yVWevxojV4KFS8RgH9ltszmTZzUzKgcFD7PuInOsA0qAiaer10uiLU9ashHBqGTjmApnPpAyQpPFz7IM9/RXLPR77gPjMv4y+oJ4OfAXS8AkO7Lcwc04mQP9MygFfoT0XGFEpqZ+icl6BNHm+ffVYJnHyuECmnEyAvpmUAbCL2jMXnvsYwuChUvWNUum0lDXLcaaPA9P7D3dy/u6PaWDbtm2S+l9e8eabb+7z77fffruWLVsmSSosLNSaNWt0//3365ZbblF2drauv/56fe9735PXmx51yJP3VAgeTd0+8/Kd+RAODITHI5VfJJVOl458JB3ZJR3eKYVD9lKln7lDyovvvo+OK7vQvjl3Svc5gw/DyDy+AmnGX0jtLdLBbdL+jXYGeLPtK0eHjc3M/9eFI+2vE02p22fOIOm8C1K3PyBRSqulUVOl5jrpcJ10+MOP5wI50uz/L8alh9JI+Qx7fpNKpdPtE4yATJLnl6Z/Qeo8ITW8L+3b8MlcYNr19ok0mfj/2j/MPnnt+IHU7TMr116yDUBmGTxEuuhmKXhMOvi+dGDzJzk4/YtS8ejM/EwEAKfLwOlc4kUqkFmW1efXyeLYSePHj9crr7yiQCCglpYW/fSnP9WIEelz862TV8ak0oTL7SUqgEzkzZJKqqSp132ytEB2buYWxyRpxHi7WJ4qg4vNOpsM7jN4iDThs59kQI7v4wNiGfxBMNVzgfFzpSxOyUKG8nrtK8Wmfv60uUBe5hbHJGnoaHupxVTxFUrlF6Zuf0Ci+Qrt97LT5wIjJmRmceykCZer3yvjkmHcZ+zPUQAyk79YqrzyzBwcNiazPxMBwEkZPKVLnEgFMjcZPs4+EzYl+xpvL0MHIH14PNLkP7fP+Er+zqTJ13IPQiDdDC23ryZNheIx9lU4ANKHxyNN+nP7io5UmPznHBgH0k3RKKliZor2VSqNvig1+wIAAIgVBTJJa9askWVZuu6665xuSkpMvNK+d0osuoNSZ5v9PRq5g6VJ13A2iVuUlJTo4YcfVklJidNNQQIMHipNnBfbNrFmgCRVzJKGnB/bfpC+yAF3qfysfYVnLGLNgZxB9j2cmAu4AxngLr4Cqerq2LaJZy5QfpEz9z9FcpAD7jLuM1L+ebFtE2sOZOXaRfJMvtoOnyADAMaB6f2HO7HgjYFyfNKFN0vv/VzqCkS3zbs/jf71sz9+/Uy6YTnObfjw4Vq0aJHTzUAClU2XutqkPe9E9/xYMkCSRk2xl6KBe5AD7pKVK110k7Tx5/a9VaIRSw5k5dr3cIv1hBykLzLAfUZNtucCdWuje36sc4GSC+wT8+Ae5IC7eLOlC79kHxdoPx7dNrHkgDdbuvAv7KXZ4A5kAMA4ML3/cCfO4zHU4CHSxbck/sBVXr50yVekgvS59RoSoLW1Va+99ppaW1udbgoSaNwcafxnE/+6ZTPspRW5asRdyAH38RVKl9yS+ANXOYOki79sL98E9yAD3Kni0tivKo/GqCnSlOu4asRtyAH3yfPbxwXyE/z5PdsnXXRzau99jOQjAwDGgen9hzvxkcVgg4dIl34tcfcGGTlJuvT2xE+u4bz6+no98MADqq+vd7opSCCPRxp7qXTRl+0D5QOVM0iatsBesonimPuQA+7kK5Rm3Wovg5YIIyqlyxZJhSMT83pIH2SAe42+2C6WDx468NfK9klTPm+fKOPlk6brkAPulOeXZv6lNGampATM4YeNlS67XRpSOvDXQnohAwDGgen9hzuxxKLhsvPs+4OcN9FeXqXtUOyv4R9mL6V2XmXi2wcg+YpH2we0d6+TGrZJoe7Ytvdm2QXyCZfb9x8EkFmycqULrrLfx+v+KLU2xv4ag4vte5mUXECBHMhEQ8rsE+f2vC3Vb5V6u2Lb3uOVSqqkystZZh3IRFk5UuUV9lzgoz9ILQ2xv8agIdLYy+wrSJkLAACATEGBDJKkYRX2DbRPNEn1W6Sje899492cQfbzy6bbH6iZAAOZLTvXXmJp3By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mfuD1gx9Qg50665xc/Z7/e0D7/vY7Ls3P1/xwkCMaWnKgf97xXx7I+MnT07m+MzNnNsfVo8wB4ECX/ea1+fXXXNrv/TpXPZ+ZM08dgogOrre3d9+fzznnnH7VpRfTIDtAd3d3kmTHjh0Hffzmm2/Opk2bMnHixJx44olDHs8Lv3wG2/bt2/u1/c6dO/d97+u+69at63dcQOP0pw4MpAYk6gAMZ9YCgLUApZMDL7Vr98AundbSOnbEjfVgZkzsGvC+z2/dNuJeAznQPy9cWnDv3r1NMy5zADjQrp49A9pv9KgjKsv3DRs2DHhfDbIDHHfccXnuuefy0EMP5ayzztrvsc7Oznz84x9PkixcuDAtLS1DHs/06dOH5Ayy8ePH92v7tra2fd/7uu+MGTP6HRfQOP2pAwOpAYk6AMOZtQBgLUDp5MBLtdYO/mHhV7J7x5YRN9aDaWsfNeB9jxjfOuJeAznQP6NGjdr3vVnGZQ4AB+pt7RnQft07n2tovvf29u47uWjatGkDfp6WWq02gKtLN68rrrgif/VXf5VZs2ble9/7Xk4++eQkyQMPPJD3ve99+eUvf5ndu3fnIx/5SK6//vqDPsenPvWpfPrTn85AX9ru7u5MmDAhSbJt27a0t7cPbDAvo7/XC166dGne+973ZsmSJVmwYEGf9pk3b95AQgMapD91YCA1IFEHYDizFgCsBSidHHip5U8nX7q7//v95qnJha8d/Hgarbc3ue9vk55+nkh2xITk7A8lQ3T3jSEjB/rnk7cmW3ckk8cln/6dqqMZHOYAcKAt65IHb+r/frNem5zym4Mfz6EMVg/FGWQHuPrqq/O1r30tTz31VBYsWJB58+Zl586dWblyZc4///zMnj073/3ud/e7/1gJTj755Nx3332ZOHFi1aEAFVADAHUAyqYGULpScuCU6cnUCcmmbX3fpyXJG+cOWUgN1dqazFyUPHlv//absXDkNcf6q5Qc4NDMASjD5FclE45Jtm3s334zFw9JOEOuyX9999/MmTNzzz335J3vfGfa2tqyevXqTJkyJV/60pdyxx135PHHH0+S4hpkY8aMyZQpUzJmzJiqQwEqoAYA6gCUTQ2gdKXkQGtL8o5+vt1x1knJ0ROGJp4qzFiYtPXj/f8jJtabas2ulBzg0MwBKENLSzLnnP7tc9ypSfvRQxPPUNMgO4j58+fn9ttvT1dXV7q6unL//ffnQx/6ULq7u7N69eq0trbmtNNOqzrMhlq7dm0+/OEPZ+3atVWHAlRADQDUASibGkDpSsqB181OLnpd37ZdOCt5zxlDGk7DjR2fLH5P/bKJr7hte/La36l/b3Yl5QAHZw5AOY6Zk8x7W9+2PfrE5NS3D208Q0mDrB+WLl2aWq2WuXPnHvRmlEuWLMmSJUuybNmy/f7+4IMPNjrUQdfV1ZW77747XV39vBA30BTUAEAdgLKpAZSutBw4d35y+ZuT4w/xafAjxyfvem1y2TnJqCZ8Z2nC1OSM30+mn5q0jnrp4y2j6p+WP+P365ehKkFpOcBLmQNQlpmL6h8Ymfyqgz9+xIT6mWaLfjtpHcE38hrBoTfeY489luTQl1e8+OKLD/r3D3zgA7nhhhuGNDYAAACAwfKaWfWvtc8my59Ovr8s2bUnGT82+f9c1Pz33GqblCx4RzL315MNv0hW/luyd3cyemzyxj+qn2kGAM1s6on1r65nko1PJmt+8qvfhW3J2R88+IdIRhoNsn54pQZZrVZrZDgAAAAAQ+r4o+tf//5EvUE2ZlTzN8debOz4ZNZrk9X3198UHDVWcwyAskw8tv617tFf/S4c3RzNscQlFvvllRpkAAAAAAAADH/OIOuHu+66q+oQKjNt2rRcc801mTZtWtWhABVQAwB1AMqmBlA6OUDp5ADmANCMNMjok6lTp+ayyy6rOgygImoAoA5A2dQASicHKJ0cwBwAmpFLLNInW7duzXe+851s3bq16lCACqgBgDoAZVMDKJ0coHRyAHMAaEYaZPRJR0dHrrrqqnR0dFQdClABNQBQB6BsagClkwOUTg5gDgDNSIMMAAAAAACAomiQAQAAAAAAUBQNMgAAAAAAAIqiQUaftLW1Zf78+Wlra6s6FKACagCgDkDZ1ABKJwconRzAHACa0eiqA2BkmDNnTm699daqwwAqogYA6gCUTQ2gdHKA0skBzAGgGTmDDAAAAAAAgKJokNEny5Yty8KFC7Ns2bKqQwEqoAYA6gCUTQ2gdHKA0skBzAGgGWmQ0Se1Wi27d+9OrVarOhSgAmoAoA5A2dQASicHKJ0cwBwAmpEGGQAAAAAAAEXRIAMAAAAAAKAoGmQAAAAAAAAUZXTVATAyzJkzJ7fddltmzZpVdShABdQAQB2AsqkBlE4OUDo5gDkANCMNMvqkra0tc+fOrToMoCJqAKAOQNnUAEonByidHMAcAJqRSyzSJ+vWrcsnPvGJrFu3rupQgAqoAYA6AGVTAyidHKB0cgBzAGhGGmT0yZYtW3LLLbdky5YtVYcCVEANANQBKJsaQOnkAKWTA5gDQDPSIAMAAAAAAKAoGmQAAAAAAAAURYMMAAAAAACAomiQ0Setra0544wz0tpqykCJ1ABAHYCyqQGUTg5QOjmAOQA0IxWNPunt7c0DDzyQ3t7eqkMBKqAGAOoAlE0NoHRygNLJAcwBoBlpkAEAAAAAAFAUDTIAAAAAAACKokEGAAAAAABAUTTI6JPJkyfnwgsvzOTJk6sOBaiAGgCoA1A2NYDSyQFKJwcwB4BmNLrqABgZZs6cmeuuu67qMICKqAGAOgBlUwMonRygdHIAcwBoRs4go096enqyZs2a9PT0VB0KUAE1AFAHoGxqAKWTA5RODmAOAM1Ig4w+WblyZc4777ysXLmy6lCACqgBgDoAZVMDKJ0coHRyAHMAaEYaZAAAAAAAABRFgwwAAAAAAICiaJABAAAAAABQFA0yAAAAAAAAijK66gAYGRYsWJDly5dXHQZQETUAUAegbGoApZMDlE4OYA4AzcgZZAAAAAAAABRFg4w+WbVqVS655JKsWrWq6lCACqgBgDoAZVMDKJ0coHRyAHMAaEYaZPTJ9u3b8+ijj2b79u1VhwJUQA0A1AEomxpA6eQApZMDmANAM9IgAwAAAAAAoCgaZAAAAAAAABRFgwwAAAAAAICiaJDRJzNmzMi1116bGTNmVB0KUAE1AFAHoGxqAKWTA5RODmAOAM1odNUBMDIceeSRede73lV1GEBF1ABAHYCyqQGUTg5QOjmAOQA0I2eQ0SebN2/OjTfemM2bN1cdClABNQBQB6BsagClkwOUTg5gDgDNSIOMPuns7MxnPvOZdHZ2Vh0KUAE1AFAHoGxqAKWTA5RODmAOAM1Ig+xlbNq0KVdffXVOOumktLW1ZdasWbnyyivT3d2dyy+/PC0tLbn++uurDhMAAAAAAIB+cA+yQ3jkkUdy/vnnZ/369Wlvb8+pp56ap59+Ol/4whfy5JNP7judePHixdUGCgAAwJDYtSd5aHXy5DNJz57kiNHJSdOS156QjC3gf9O1WrL16WT98mRXd9LSmow/KnnVacm4I6uODgCG3t7dyYZfJM89lezZlYwakxw1MzluXjJqbNXR0Qi7upOnf55s25Ts3ZOMaUuOPSk5+sT62qjZ9fYmm56sf+3eUf/Znl3Jrh3J2HHVxjYYCljS99+mTZty4YUXZv369fnYxz6WT37yk5k4cWKS5Lrrrss111yT0aNHp6WlJQsXLqw4WgAAAAbT3t7kOz9L7nk82bl7/8ceWJV886HkTackv3Va0tqkb4w8uzp54ofJto0vfWzVj5Opr05O+c1k3OSGhwYAQ67WW/9999RDye6d+z+2fln9d+TMRcmrz05aR1UTI0Nr987k8buS9b9Ianv3f+zpx5K2Scmr31j/4FCz6ni0ngc9Xfv/fO+u5N6/SY47NTn53GT0CG4WN+lS/vBcccUV6ejoyEc/+tF8/vOf39ccS5Krr746ixYtyp49ezJ79uxMmjSpwkgbp729PWeffXba29urDgWogBoAqANQtpJqwN7e5Kv/lvzr0pc2x16wfVfy3ceS/3lf/VO1zWb98uThWw7eHHvBpl8mD9yYdD/buLiqVFIOwMHIAUqaA7Xe5Od3JL/895c2x16wpydZ/ZPk0X9OevcefBtGrl3bkwdvSjqXvbQ59oKdzyfLvpP88keNja1RVt6TrPjXlzbHXtC7t94o/On/feg8GQk0yA6wfPny3HzzzZk6dWo++9nPHnSb008/PUmyaNGifT9bsmRJ3vOe9+SEE07I+PHjM2/evPzpn/5ptm3b1pC4h9rs2bPzla98JbNnz646FKACagCgDkDZSqoB//xQsnRd37Z9dG1y+yNDGk7Dbe1Mlt6ZpPbK2+7aXm+k7dk15GFVrqQcgIORA5Q0B568t35Zxb54dlX9LCOaR62W/Oybff8Q0C/vq3+4qJmseyxZfX/ftu16JnnsW/XXbSTSIDvATTfdlN7e3lx66aWZMGHCQbcZN65+cc0XN8g+//nPZ9SoUfnLv/zL3HnnnfmTP/mT/PVf/3XOO++89DbBRwr37t2bbdu2Ze9eH4mAEqkBgDoAZSulBnTtTP79if7tc8/jyfaeoYmnCqt/Uv/kfF/tfL5+qalmV0oOwKHIAUqZA3t6krUP9W+fdY8lPd1DEw+N99xTyZY+fljqBat+PHIbRAeq1ZLVP+7fPpvXJM+vH5p4hpoG2QHuuqve8j/33HMPuU1HR0eS/Rtk3/rWt/L1r389l156ad7ylrfkyiuvzPXXX5/77rsv995779AG3QArVqzIGWeckRUrVlQdClABNQBQB6BspdSAH6+sX2KxP3bvTX6yamjiabSdXcmmlf3fr+OR5nlT6FBKyQE4FDlAKXPg6aVJ757+7VPrTdb9bGjiofE6Hun/Pt3PJls6Bj2USjy7Ktmxtf/7DeR1Gw40yA6wZs2aJMkJJ5xw0Mf37Nm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+      "text/plain": [
+       "<Figure size 2228.78x9983.17 with 1 Axes>"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qc_bonus = grover_algorithm(challenge_bonus, rep=1)\n",
+    "\n",
+    "qc_bonus.draw('mpl')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'10010': 40, '00011': 47, '01111': 34, '10101': 31, '01001': 41, '00111': 28, '11111': 30, '11011': 37, '00001': 39, '01011': 41, '10100': 3164, '10001': 3212, '11010': 38, '11101': 40, '00101': 3080, '11000': 3170, '11100': 36, '10110': 38, '10000': 36, '01100': 3189, '00110': 3183, '00010': 34, '10111': 31, '01101': 42, '11110': 39, '01010': 48, '01000': 45, '01110': 51, '00100': 43, '00000': 36, '10011': 40, '11001': 37}\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "counts_without_qiskit_convention = circuit_execute(qc_bonus, shots=20000)\n",
+    "print(counts_without_qiskit_convention)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot_histogram(counts_without_qiskit_convention, color='midnightblue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'10100': 3164, '10001': 3212, '00101': 3080, '11000': 3170, '01100': 3189, '00110': 3183}\n"
+     ]
+    }
+   ],
+   "source": [
+    "possible_results = filter_values_above_average(counts_without_qiskit_convention)\n",
+    "\n",
+    "print(possible_results)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "List 1: [['X', 'O', 'O'], ['X', 'X', 'O'], ['O', 'X', 'O']]\n",
+      "List 2: [['X', 'O', 'O'], ['X', 'X', 'O'], ['O', 'O', 'O']]\n",
+      "List 3: [['X', 'O', 'O'], ['X', 'O', 'O'], ['O', 'X', 'O']]\n",
+      "List 4: [['X', 'O', 'O'], ['X', 'X', 'X'], ['O', 'O', 'O']]\n",
+      "List 5: [['X', 'O', 'O'], ['X', 'O', 'X'], ['O', 'X', 'O']]\n",
+      "List 6: [['X', 'O', 'O'], ['X', 'O', 'O'], ['O', 'X', 'X']]\n"
+     ]
+    }
+   ],
+   "source": [
+    "completed_lists = complete_lists_with_dictionary(challenge, possible_results)\n",
+    "\n",
+    "for i, lst in enumerate(completed_lists, start=1):\n",
+    "    print(f'List {i}: {lst}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Challenge:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X |   |  \n",
+      "---------\n",
+      "O |   |  \n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 1:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | X | O\n",
+      "---------\n",
+      "O | X | O\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 2:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | X | O\n",
+      "---------\n",
+      "O | O | O\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 3:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | O | O\n",
+      "---------\n",
+      "O | X | O\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 4:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | X | X\n",
+      "---------\n",
+      "O | O | O\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 5:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | O | X\n",
+      "---------\n",
+      "O | X | O\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 6:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | O | O\n",
+      "---------\n",
+      "O | X | X\n",
+      "---------\n",
+      "\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Challenge:')\n",
+    "display_board(challenge)\n",
+    "print('\\n')\n",
+    "\n",
+    "for index, lst in enumerate(completed_lists):\n",
+    "    print('Solution {}:'.format(index + 1))\n",
+    "    display_board(lst)\n",
+    "    print('\\n')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Post quantum analysis"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Para este caso tambien podemos hacer el analisis post cuantico. Para saber que jugadas podrían darnos una mayor probabilidad de ganar:\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div>\n",
+    "<p style = 'text-align:center;'>\n",
+    "<img src=\"../Images/best_play_bonus.png\" alt=\"JuveYell\" width=\"200px\">\n",
+    "</p>\n",
+    "</div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can observe that the optimal move for 'X' is marking the third playable box (in red), which logically results in an automatic win. On the other hand, if 'O' plays in the fourth possible box (in blue), it also increases our chances of winning, as the displayed results are for 'X' winning scenarios. Finally, we can notice that the second-best move for 'X' after 'O' has played is to choose the first available box (in green).\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The file `general_solution.ipynb` includes a function that generates a random initial game configuration. Subsequently, the execution of the algorithm yields results where 'X' emerges victorious. In such instances, post-quantum analysis could be performed, although results may vary across each execution. Two specific cases are highlighted for a comprehensive understanding.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 3. Conclusion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "   - The flexibility of the oracle demonstrates Grover's versatility in addressing specific game conditions."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Grover provides an  adaptable quantum solution for Tic Tac Toe, though the outcomes are statistically variable due to the quantum nature of the algorithm.*"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "WOMANIUM",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/challenges/PIQUE challenge/QuantumVoyagers/app/qaoa/qaoa.ipynb b/challenges/PIQUE challenge/QuantumVoyagers/app/qaoa/qaoa.ipynb
new file mode 100644
index 0000000..4f72b06
--- /dev/null
+++ b/challenges/PIQUE challenge/QuantumVoyagers/app/qaoa/qaoa.ipynb	
@@ -0,0 +1,955 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "clyv3IRsJNaG",
+      "metadata": {
+        "id": "clyv3IRsJNaG"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install h5py\n",
+        "!pip install typing-extensions\n",
+        "!pip install wheel"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "65DDjaGiFd_c",
+      "metadata": {
+        "id": "65DDjaGiFd_c"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install docplex\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "DM3iU9TvGGCo",
+      "metadata": {
+        "id": "DM3iU9TvGGCo"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install --upgrade azure-quantum\\[qiskit\\]\n",
+        "!pip install qiskit\n",
+        "!pip install cplex"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "7QQ56rCZLsex",
+      "metadata": {
+        "id": "7QQ56rCZLsex"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install openqaoa-qiskit"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 20,
+      "id": "17552bd0",
+      "metadata": {
+        "id": "17552bd0"
+      },
+      "outputs": [],
+      "source": [
+        "%matplotlib notebook\n",
+        "\n",
+        "# Import external libraries to present an manipulate the data\n",
+        "import numpy as np\n",
+        "import matplotlib.pyplot as plt\n",
+        "import pandas as pd\n",
+        "\n",
+        "# Import docplex model to generate the problem to optimize\n",
+        "from docplex.mp.model import Model\n",
+        "\n",
+        "# Import the libraries needed to employ the QAOA quantum algorithm using OpenQAOA\n",
+        "from openqaoa import QAOA\n",
+        "\n",
+        "# method to covnert a docplex model to a qubo problem\n",
+        "from openqaoa.problems.converters import FromDocplex2IsingModel\n",
+        "from openqaoa.backends import create_device\n",
+        "\n",
+        "# method to find the corrects states for the QAOA boject\n",
+        "from openqaoa.utilities import ground_state_hamiltonian"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "c3672d85",
+      "metadata": {
+        "id": "c3672d85"
+      },
+      "source": [
+        "## 1) Tic Tac Toe Game\n",
+        "This problem can be solved by treating each cell as a variable, and our objective function aims to maximize the number of winning moves. For instance, if we want to address the following problem:\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "<div>\n",
+        "<p style = 'text-align:center;'>\n",
+        "<img src=\"../Images/image10.png\" alt=\"JuveYell\" width=\"300px\">\n",
+        "</p>\n",
+        "</div>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n",
+        "So, for x_0, we observe it has 2 winning possibilities. On the other hand, x_1 has only one, x_2 has 0 winning possibilities, and x_3 has only 1 winning option. Therefore, our objective function is formulated as follows:\n",
+        "$$f_1(\\textbf{x}) = 2*x_0 + 1*x_1 + 0*x_2 + 1*x_3$$\n",
+        "\n",
+        "This objective function is subject to an equality constraint, as when the game starts with 0's, there should be a total of 4 X's played. This forms our constraint, but in this case, given an initial configuration, we subtract 2 X's:\n",
+        "\n",
+        "$$x_0 + x_1 + x_2 + x_3 = 2$$\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 95,
+      "id": "inv3grH1qNBI",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 481
+        },
+        "id": "inv3grH1qNBI",
+        "outputId": "4bd182b2-18a5-4ec6-8f97-87c20bb26cc3"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "// This file has been generated by DOcplex\n",
+            "// model name is: Basic Problem using minimize\n",
+            "// var contrainer section\n",
+            "dvar bool x[4];\n",
+            "\n",
+            "maximize\n",
+            " 2 x_0 + x_1 + x_3;\n",
+            " \n",
+            "subject to {\n",
+            " x_0 + x_1 + x_2 + x_3 == 2;\n",
+            "\n",
+            "}\n",
+            "None\n",
+            "Warning: Model name contains whitespaces: |Basic Problem using minimize|\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "\n",
+              "  <div id=\"df-86eca371-f92f-495c-8292-2d2b67d8290c\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>solutions_bitstrings</th>\n",
+              "      <th>bitstrings_energies</th>\n",
+              "      <th>probabilities</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>1001</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>1100</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>0101</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>1010</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>0110</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>0011</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-86eca371-f92f-495c-8292-2d2b67d8290c')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-86eca371-f92f-495c-8292-2d2b67d8290c button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-86eca371-f92f-495c-8292-2d2b67d8290c');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-9e57aac3-d968-4ec9-b6ab-4d2a64476bc5\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-9e57aac3-d968-4ec9-b6ab-4d2a64476bc5')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-9e57aac3-d968-4ec9-b6ab-4d2a64476bc5 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "text/plain": [
+              "  solutions_bitstrings  bitstrings_energies  probabilities\n",
+              "0                 1001                 -3.0           0.10\n",
+              "1                 1100                 -3.0           0.10\n",
+              "2                 0101                 -2.0           0.05\n",
+              "3                 1010                 -2.0           0.10\n",
+              "4                 0110                 -1.0           0.10\n",
+              "5                 0011                 -1.0           0.10"
+            ]
+          },
+          "execution_count": 95,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "#Specific the Model and put a name\n",
+        "mdl = Model(\"Basic Problem using maximize\")\n",
+        "# Number of variables\n",
+        "n_vars = 4\n",
+        "\n",
+        "# Using binary variables for this model\n",
+        "x = mdl.binary_var_list(n_vars, name=\"x\")\n",
+        "obj_func = 2*x[0] + x[1] + 0*x[2] + 1*x[3]\n",
+        "#obj_func = 2*x[0] + x[1] + 1*x[2] + 0*x[3] + 1*x[4]\n",
+        "mdl.maximize(obj_func)\n",
+        "mdl.add_constraint(x[0] + x[1] + x[2] + x[3] == 2)\n",
+        "\n",
+        "print(mdl.prettyprint())\n",
+        "# Converting the Docplex model into its qubo representation\n",
+        "qubo = FromDocplex2IsingModel(mdl)\n",
+        "\n",
+        "# Ising encoding of the QUBO problem\n",
+        "ising_encoding = qubo.ising_model\n",
+        "\n",
+        "# Print in a df the ising encoding (we need to remove keys: 'problem_instance' and 'metadata'))\n",
+        "ising_encoding_dict = ising_encoding.asdict(exclude_keys=['problem_instance', 'metadata'])\n",
+        "#pd.DataFrame(ising_encoding_dict)\n",
+        "#Specific local device usign qiskit backend\n",
+        "device = create_device(\"local\", 'qiskit.qasm_simulator')\n",
+        "#Is possible check the devices using qaoa.local_simulators, qaoa.cloud_provider\n",
+        "qaoa = QAOA(device)\n",
+        "\n",
+        "#Indicate the properties to the QAOA quantum algorithm,shots,seed\n",
+        "qaoa.set_backend_properties(n_shots=20, seed_simulator=1)\n",
+        "#check the p value and the variational init params\n",
+        "qaoa.set_circuit_properties(p=2, init_type=\"custom\", variational_params_dict={\"betas\":2*[0.01*np.pi],\"gammas\":2*[0.01*np.pi]})\n",
+        "\n",
+        "#Indicate the ising e ncoding model from docplex\n",
+        "qaoa.compile(ising_encoding)\n",
+        "\n",
+        "#Optimize the quantum algorithm\n",
+        "qaoa.optimize()\n",
+        "#Print in a df the best 10 solutions\n",
+        "results = pd.DataFrame(qaoa.result.lowest_cost_bitstrings(10))\n",
+        "results = results[results[\"bitstrings_energies\"]<0]\n",
+        "results"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n",
+        "From the results, we observe that for the lowest bitstrings_energy (-3), we have the states 1001 and 1100. These happen to be the only 2 options where X's can win in this case.\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Additionally, we can also solve the bonus problem."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "<div>\n",
+        "<p style = 'text-align:center;'>\n",
+        "<img src=\"../Images/image11.png\" alt=\"JuveYell\" width=\"300px\">\n",
+        "</p>\n",
+        "</div>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "So, for x_0, we observe it has 2 winning possibilities. On the other hand, x_1 has only one, x_2 has only one too, x_3 has 0 winning possibilities, and x_4 has only 1 winning option. Therefore, our objective function is formulated as follows:\n",
+        "$$f_1(\\textbf{x}) = 2*x_0 + 1*x_1 + 1*x_2 + 0*x_3 + 1*x_4$$\n",
+        "\n",
+        "This objective function is subject to an equality constraint, as when the game starts with 0's, there should be a total of 4 X's played. This forms our constraint, but in this case, given an initial configuration, we subtract 2 X's:\n",
+        "\n",
+        "$$x_0 + x_1 + x_2 + x_3 + x_4= 2$$"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 94,
+      "id": "ed3023be",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 575
+        },
+        "id": "ed3023be",
+        "outputId": "699a3f4d-02d4-458d-8d34-a396229fb0ab"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "// This file has been generated by DOcplex\n",
+            "// model name is: Basic Problem using minimize\n",
+            "// var contrainer section\n",
+            "dvar bool x[5];\n",
+            "\n",
+            "maximize\n",
+            " 2 x_0 + x_1 + x_2 + x_4;\n",
+            " \n",
+            "subject to {\n",
+            " x_0 + x_1 + x_2 + x_3 + x_4 == 2;\n",
+            "\n",
+            "}\n",
+            "None\n",
+            "Warning: Model name contains whitespaces: |Basic Problem using minimize|\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "\n",
+              "  <div id=\"df-e2b1115d-644b-4a24-b6a5-2e0c601edba6\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>solutions_bitstrings</th>\n",
+              "      <th>bitstrings_energies</th>\n",
+              "      <th>probabilities</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>10001</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>10100</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>11000</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.20</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>10010</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>00101</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>01100</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.15</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>00011</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7</th>\n",
+              "      <td>00110</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8</th>\n",
+              "      <td>01010</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.15</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e2b1115d-644b-4a24-b6a5-2e0c601edba6')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
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+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-e2b1115d-644b-4a24-b6a5-2e0c601edba6 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-e2b1115d-644b-4a24-b6a5-2e0c601edba6');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-9531382f-27d2-4c5d-af22-985a036e4dd6\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-9531382f-27d2-4c5d-af22-985a036e4dd6')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-9531382f-27d2-4c5d-af22-985a036e4dd6 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "text/plain": [
+              "  solutions_bitstrings  bitstrings_energies  probabilities\n",
+              "0                10001                 -3.0           0.05\n",
+              "1                10100                 -3.0           0.05\n",
+              "2                11000                 -3.0           0.20\n",
+              "3                10010                 -2.0           0.10\n",
+              "4                00101                 -2.0           0.10\n",
+              "5                01100                 -2.0           0.15\n",
+              "6                00011                 -1.0           0.05\n",
+              "7                00110                 -1.0           0.10\n",
+              "8                01010                 -1.0           0.15"
+            ]
+          },
+          "execution_count": 94,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "#Specific the Model and put a name\n",
+        "mdl = Model(\"Basic Problem using minimize\")\n",
+        "# Number of variables\n",
+        "n_vars = 5\n",
+        "\n",
+        "# Using binary variables for this model\n",
+        "x = mdl.binary_var_list(n_vars, name=\"x\")\n",
+        "obj_func = 2*x[0] + x[1] + 1*x[2] + 0*x[3] + 1*x[4]\n",
+        "\n",
+        "mdl.maximize(obj_func)\n",
+        "mdl.add_constraint(x[0] + x[1] + x[2] + x[3] + x[4] == 2)\n",
+        "print(mdl.prettyprint())\n",
+        "# Converting the Docplex model into its qubo representation\n",
+        "qubo = FromDocplex2IsingModel(mdl)\n",
+        "\n",
+        "# Ising encoding of the QUBO problem\n",
+        "ising_encoding = qubo.ising_model\n",
+        "\n",
+        "# Print in a df the ising encoding (we need to remove keys: 'problem_instance' and 'metadata'))\n",
+        "ising_encoding_dict = ising_encoding.asdict(exclude_keys=['problem_instance', 'metadata'])\n",
+        "\n",
+        "#Specific local device usign qiskit backend\n",
+        "device = create_device(\"local\", 'qiskit.qasm_simulator')\n",
+        "#Is possible check the devices using qaoa.local_simulators, qaoa.cloud_provider\n",
+        "qaoa = QAOA(device)\n",
+        "\n",
+        "#Indicate the properties to the QAOA quantum algorithm,shots,seed\n",
+        "qaoa.set_backend_properties(n_shots=20, seed_simulator=1)\n",
+        "#check the p value and the variational init params\n",
+        "qaoa.set_circuit_properties(p=2, init_type=\"custom\", variational_params_dict={\"betas\":2*[0.01*np.pi],\"gammas\":2*[0.01*np.pi]})\n",
+        "\n",
+        "#Indicate the ising e ncoding model from docplex\n",
+        "qaoa.compile(ising_encoding)\n",
+        "\n",
+        "#Optimize the quantum algorithm\n",
+        "qaoa.optimize()\n",
+        "#Print in a df the best 10 solutions\n",
+        "results = pd.DataFrame(qaoa.result.lowest_cost_bitstrings(10))\n",
+        "results = results[results[\"bitstrings_energies\"]<0]\n",
+        "results"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.10.6"
+    },
+    "vscode": {
+      "interpreter": {
+        "hash": "d2582286b70c3b030a2fde61b871db03dec7fee33191883f4394b540a2eb90c7"
+      }
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 5
+}
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new file mode 100644
index 0000000..af23e76
--- /dev/null
+++ b/challenges/PIQUE challenge/QuantumVoyagers/pkg/general_utils.py	
@@ -0,0 +1,162 @@
+import random
+
+
+def initialize_board():
+    """
+    Initializes a Tic Tac Toe board with empty spaces.
+
+    Returns:
+    - board (list): A 3x3 grid representing the Tic Tac Toe board.
+    """
+    board = [[' ' for _ in range(3)] for _ in range(3)]
+    return board
+
+
+def make_move(board, player, row, column):
+    """
+    Makes a move on the Tic Tac Toe board for the specified player.
+
+    Parameters:
+    - board (list): The Tic Tac Toe board.
+    - player (str): The player making the move ('O' or 'X').
+    - row (int): The row where the move is made.
+    - column (int): The column where the move is made.
+
+    Returns:
+    - success (bool): True if the move is successful, False if the chosen position is already occupied.
+    """
+    if board[row][column] == ' ':
+        board[row][column] = player
+        return True
+    else:
+        return False
+
+
+def check_winner(board):
+    """
+    Checks if there is a winner on the Tic Tac Toe board.
+
+    Parameters:
+    - board (list): The Tic Tac Toe board.
+
+    Returns:
+    - winner (bool): True if there is a winner, False otherwise.
+    """
+    # Check rows and columns
+    for i in range(3):
+        if board[i][0] == board[i][1] == board[i][2] != ' ' or board[0][i] == board[1][i] == board[2][i] != ' ':
+            return True
+
+    # Check diagonals
+    if board[0][0] == board[1][1] == board[2][2] != ' ' or board[0][2] == board[1][1] == board[2][0] != ' ':
+        return True
+
+    return False
+
+
+def generate_random_board(num_moves):
+    """
+    Generates a random Tic Tac Toe board after a specified number of moves.
+
+    Parameters:
+    - num_moves (int): The number of moves made on the board.
+
+    Returns:
+    - board (list): A 3x3 grid representing the generated Tic Tac Toe board.
+    """
+    players = ['O', 'X']
+
+    while True:
+        board = initialize_board()
+        moves_made = 0
+
+        while moves_made < num_moves:
+            current_player = players[moves_made % 2]
+            row = random.randint(0, 2)
+            column = random.randint(0, 2)
+
+            if make_move(board, current_player, row, column):
+                moves_made += 1
+
+        if not check_winner(board):
+            return board
+
+
+def display_board(board):
+    """
+    Displays the Tic Tac Toe board.
+
+    Parameters:
+    - board (list): The Tic Tac Toe board.
+    """
+    for row in board:
+        print(" | ".join(row))
+        print("-" * 9)
+
+
+def complete_lists_with_dictionary(lists, dictionary):
+    """
+    Completes lists with characters from a dictionary.
+
+    Parameters:
+    - lists (list): A list of lists to be completed.
+    - dictionary (dict): A dictionary where keys are binary strings and values are probabilities.
+
+    Returns:
+    - result (list): A list of lists with characters filled in from the dictionary.
+    """
+    result = []
+
+    for key, value in dictionary.items():
+        # Create a copy of the original list
+        new_list = [list(row) for row in lists]
+
+        # Convert the binary value of the key into a list of characters 'O' and 'X'
+        characters = ['O' if bit == '0' else 'X' for bit in key]
+
+        # Fill in the empty spaces in the new list with the corresponding characters
+        index = 0
+        for i in range(len(new_list)):
+            for j in range(len(new_list[i])):
+                if new_list[i][j] == ' ':
+                    new_list[i][j] = characters[index]
+                    index += 1
+
+        result.append(new_list)
+
+    return result
+
+
+def filter_values_above_average(dictionary):
+    """
+    Filters values above the average from a dictionary.
+
+    Parameters:
+    - dictionary (dict): A dictionary where keys are binary strings and values are probabilities.
+
+    Returns:
+    - filtered_dictionary (dict): A dictionary with values above the average.
+    """
+    values = list(dictionary.values())
+    average = sum(values) / len(values)
+
+    # Calculate the difference between the maximum and minimum values
+    max_min_difference = max(values) - min(values)
+
+    # Check if the difference is small compared to the average
+    if max_min_difference < 0.1 * average:
+        return dictionary
+
+    # Filter values above the average
+    filtered_dictionary = {key: value for key,
+                           value in dictionary.items() if value > average}
+    return filtered_dictionary
+
+
+if __name__ == '__main__':
+    # Example of usage
+    num_moves = 5
+    random_board = generate_random_board(num_moves)
+    print(random_board)
+    print('Board:')
+    display_board(random_board)
diff --git a/challenges/PIQUE challenge/QuantumVoyagers/pkg/quantum_utils.py b/challenges/PIQUE challenge/QuantumVoyagers/pkg/quantum_utils.py
new file mode 100644
index 0000000..b3ac2a5
--- /dev/null
+++ b/challenges/PIQUE challenge/QuantumVoyagers/pkg/quantum_utils.py	
@@ -0,0 +1,292 @@
+from qiskit import QuantumCircuit, ClassicalRegister, QuantumRegister, execute, Aer
+from qiskit.circuit.library import XGate
+
+
+def setting_initial_configuration(board):
+    """
+    Initializes a quantum circuit with the given Tic Tac Toe board configuration.
+
+    Args:
+        board (list of lists): Represents the Tic Tac Toe board.
+
+    Returns:
+        QuantumCircuit: Quantum circuit with the specified initial configuration.
+    """
+    n_qubits = 9
+    counter_aux_qubits = 4
+    aux_conditions_qubits = 8
+    oracle_qubit = 1
+    empty_spaces = sum(row.count(' ') for row in board)
+
+    qreg_q = QuantumRegister(
+        n_qubits + counter_aux_qubits + aux_conditions_qubits + oracle_qubit, 'q')
+
+    creg_c = ClassicalRegister(empty_spaces, 'c')
+
+    qc = QuantumCircuit(qreg_q, creg_c)
+
+    counter = 0
+    for row in board:
+        for elem in row:
+            if elem == 'O':
+                qc.i(qreg_q[counter])
+            elif elem == 'X':
+                qc.x(qreg_q[counter])
+            else:
+                qc.h(qreg_q[counter])
+            counter += 1
+
+    return qc
+
+
+
+def conditions_and_counter():
+    """
+    Creates a quantum circuit to apply conditions and count the number of 'X's on the board.
+
+    Returns:
+        QuantumCircuit: Quantum circuit for conditions and counting.
+    """
+    n_qubits = 9
+    counter_aux_qubits = 4
+    aux_conditions_qubits = 8
+    oracle_qubit = 1
+
+    qreg_q = QuantumRegister(
+        n_qubits + counter_aux_qubits + aux_conditions_qubits + oracle_qubit, 'q')
+
+    mcx = XGate().control(3)
+
+    qc = QuantumCircuit(qreg_q)
+
+    # 8 possible ways for 'X' to win the game
+    qc.barrier()
+    qc.mct([0, 3, 6], 13)
+    qc.mct([0, 4, 8], 14)
+    qc.mct([3, 4, 5], 15)
+    qc.mct([1, 4, 7], 16)
+    qc.mct([0, 1, 2], 17)
+    qc.mct([2, 5, 8], 18)
+    qc.mct([6, 7, 8], 19)
+    qc.mct([2, 4, 6], 20)
+    qc.barrier()
+
+    # Bit adder, counting the number of 'X's on the board
+    qc.cx(qreg_q[0], qreg_q[9])
+    qc.barrier()
+
+    qc.ccx(qreg_q[1], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[1], qreg_q[9])
+    qc.barrier()
+
+    qc.ccx(qreg_q[2], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[2], qreg_q[9])
+    qc.barrier()
+
+    qc.append(mcx, [3, 9, 10, 11])
+    qc.ccx(qreg_q[3], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[3], qreg_q[9])
+    qc.barrier()
+
+    qc.append(mcx, [4, 9, 10, 11])
+    qc.ccx(qreg_q[4], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[4], qreg_q[9])
+    qc.barrier()
+
+    qc.append(mcx, [5, 9, 10, 11])
+    qc.ccx(qreg_q[5], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[5], qreg_q[9])
+    qc.barrier()
+
+    qc.append(mcx, [6, 9, 10, 11])
+    qc.ccx(qreg_q[6], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[6], qreg_q[9])
+    qc.barrier()
+
+    qc.append(mcx, [7, 9, 10, 11])
+    qc.ccx(qreg_q[7], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[7], qreg_q[9])
+    qc.barrier()
+
+    qc.append(mcx, [8, 9, 10, 11])
+    qc.ccx(qreg_q[8], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[8], qreg_q[9])
+    qc.barrier()
+
+    qc.x(qreg_q[9])
+    qc.x(qreg_q[10])
+
+    qc.mct([9, 10, 11], 12)
+
+    qc.barrier()
+
+    return qc
+
+def oracle():
+    """
+    Creates a quantum circuit for the oracle part of the algorithm.
+
+    Returns:
+        QuantumCircuit: Quantum circuit for the oracle.
+    """
+    n_qubits = 9
+    counter_aux_qubits = 4
+    aux_conditions_qubits = 8
+    oracle_qubit = 1
+
+    qreg_q = QuantumRegister(
+        n_qubits + counter_aux_qubits + aux_conditions_qubits + oracle_qubit, 'q')
+
+    qc = QuantumCircuit(qreg_q)
+
+    qc = qc.compose(conditions_and_counter())
+
+    qc.barrier()
+    qc.x(21)
+    qc.h(21)
+    qc.barrier()
+
+    # Oracle
+    qc.mct([12, 13], 21)
+    qc.mct([12, 14], 21)
+    qc.mct([12, 15], 21)
+    qc.mct([12, 16], 21)
+    qc.mct([12, 17], 21)
+    qc.mct([12, 18], 21)
+    qc.mct([12, 19], 21)
+    qc.mct([12, 20], 21)
+
+    qc.barrier()
+    qc = qc.compose(conditions_and_counter().inverse())
+
+    return qc
+
+
+def diffuser(board):
+    """
+    Creates a quantum circuit for the Grover Diffuser.
+
+    Args:
+        board (list): The Tic Tac Toe board.
+
+    Returns:
+        QuantumCircuit: Quantum circuit representing the Grover Diffuser.
+    """
+    n_qubits = 9
+    one_dimensional_list = [value for row in board for value in row]
+    index_empty_spaces = [i for i, value in enumerate(
+        one_dimensional_list) if value == ' ']
+
+    qreg_q = QuantumRegister(n_qubits, 'q')
+
+    qc = QuantumCircuit(qreg_q)
+
+    for qubit in index_empty_spaces:
+        qc.h(qubit)
+    # Apply transformation |00..0> -> |11..1> (X-gates)
+    for qubit in index_empty_spaces:
+        qc.x(qubit)
+
+    qc.barrier()
+    # Apply multiple controlled Z-gates
+    qc.h(index_empty_spaces[-1])
+    # Toffoli with multicontrol
+    qc.mct(index_empty_spaces[:-1], index_empty_spaces[-1])
+    qc.h(index_empty_spaces[-1])
+    qc.barrier()
+    # Apply transformation |11..1> -> |00..0>
+    for qubit in index_empty_spaces:
+        qc.x(qubit)
+    # Apply transformation |00..0> -> |s>
+    for qubit in index_empty_spaces:
+        qc.h(qubit)
+
+    # qc.measure([4,5,7,8],creg_c)
+
+    return qc
+
+
+def measurement(qc, board):
+    """
+    Adds the measurement operation to the quantum circuit.
+
+    Args:
+        qc (QuantumCircuit): Quantum circuit.
+        board (list): The Tic Tac Toe board.
+
+    Returns:
+        QuantumCircuit: Quantum circuit with measurement operation.
+    """
+    one_dimensional_list = [value for row in board for value in row]
+    index_empty_spaces = [i for i, value in enumerate(
+        one_dimensional_list) if value == ' ']
+
+    qc.measure(index_empty_spaces, qc.clbits)
+    return qc
+
+
+
+def grover_algorithm(board, rep=1):
+    """
+    Executes the Grover's algorithm for Tic Tac Toe.
+
+    Args:
+        board (list): The initial state of the Tic Tac Toe board.
+        rep (int): Number of iterations of the algorithm.
+
+    Returns:
+        QuantumCircuit: Quantum circuit representing the Grover's algorithm.
+    """
+    qc = setting_initial_configuration(board)
+    qc.barrier()
+
+    for _ in range(rep):
+        # Oracle
+        qc = qc.compose(oracle())
+        qc.barrier()
+        # Diffuser
+        qc = qc.compose(diffuser(board))
+        qc.barrier()
+
+    # Measurement
+    qc = measurement(qc, board)
+    qc.barrier()
+
+    return qc
+
+
+def circuit_execute(qc, shots=10000):
+    """
+    Executes the quantum circuit on a simulator.
+
+    Args:
+        qc (QuantumCircuit): Quantum circuit.
+        shots (int): Number of shots for the simulation.
+
+    Returns:
+        dict: Counts of the measurement outcomes.
+    """
+    simulator = Aer.get_backend('qasm_simulator')
+    job = execute(qc, simulator, shots=shots)
+    result = job.result()
+    # Returns counts
+    counts = result.get_counts(qc)
+
+    counts_without_qiskit_convention = {
+        key[::-1]: value for key, value in counts.items()}
+
+    return counts_without_qiskit_convention
+
+if __name__ == '__main__':
+    # Example of usage
+    from general_utils import generate_random_board
+
+    num_moves = 5
+    board = generate_random_board(num_moves)
+    # print(board)
+    qc_init = setting_initial_configuration(board)
+    print(qc_init)
+
+    # Oracle
+    print(oracle())
+    # print(diffuser(board))
diff --git a/challenges/QOSF challenge/QuantumVoyagers/README.md b/challenges/QOSF challenge/QuantumVoyagers/README.md
new file mode 100644
index 0000000..3c57f68
--- /dev/null
+++ b/challenges/QOSF challenge/QuantumVoyagers/README.md	
@@ -0,0 +1,56 @@
+# Quantum Algorithms for Tic Tac Toe
+
+This repository contains Python code and Jupyter Notebooks implementing quantum algorithms, specifically Grover's algorithm and Quantum Approximate Optimization Algorithm (QAOA), to solve the Tic Tac Toe game.
+
+## Table of Contents
+
+- [Grover's Algorithm](#grovers-algorithm)
+
+  - [General Solution](./app/grover/general_solution.ipynb)
+  - [Grover Circuit Complete Image](./app/grover/grover_circuit_complete_image)
+  - [Solution Notebook](./app/grover/solution.ipynb)
+
+- [QAOA](./app/qaoa/qaoa.ipynb)
+
+- [Images](./app/Images)
+
+  - [Best Play - Regular](./app/Images/best_play.png)
+  - [Best Play - Bonus](./app/Images/best_play_bonus.png)
+  - [Parts Oracle Grover](./app/Images/parts_oracle_grover.jpg)
+  - [Tic Tac Toe Image](./app/Images/tic-tac-toe-1777880_1280.jpg)
+
+- [Package](./pkg)
+  - [General Utilities](./pkg/general_utils.py)
+  - [Quantum Utilities](./pkg/quantum_utils.py)
+
+## Grover's Algorithm
+
+### General Solution
+
+The [General Solution](./app/grover/general_solution.ipynb) notebook contains the Python code for Grover's algorithm, focusing on solving Tic Tac Toe.
+
+### Grover Circuit Complete Image
+
+The [Grover Circuit Complete Image](./app/grover/grover_circuit_complete_image) directory includes the LaTeX file (`file.tex`) and the complete Grover circuit in PDF format (`grover_circuit.pdf`).
+
+### Solution Notebook
+
+The [Solution Notebook](./app/grover/solution.ipynb) provides detailed information on the solution implemented using Grover's algorithm.
+
+## QAOA
+
+The [QAOA Notebook](./app/qaoa/qaoa.ipynb) contains the Python code for Quantum Approximate Optimization Algorithm applied to Tic Tac Toe.
+
+## Images
+
+Various images related to Tic Tac Toe and the algorithms used, such as best plays and the Tic Tac Toe game itself.
+
+## Package
+
+### General Utilities
+
+The [General Utilities](./pkg/general_utils.py) module includes Python functions used for Tic Tac Toe and algorithm implementations.
+
+### Quantum Utilities
+
+The [Quantum Utilities](./pkg/quantum_utils.py) module contains Python functions specific to quantum operations in the Tic Tac Toe algorithms.
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new file mode 100644
index 0000000..624ac9f
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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qiskit.visualization import plot_histogram\n",
+    "\n",
+    "import sys\n",
+    "sys.path.append('../../')\n",
+    "from pkg.general_utils import display_board, generate_random_board, complete_lists_with_dictionary, filter_values_above_average\n",
+    "from pkg.quantum_utils import grover_algorithm, circuit_execute"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[['O', 'X', ' '], [' ', ' ', 'O'], [' ', ' ', 'X']]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "challenge = generate_random_board(num_moves=4)\n",
+    "challenge"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "O | X |  \n",
+      "---------\n",
+      "  |   | O\n",
+      "---------\n",
+      "  |   | X\n",
+      "---------\n"
+     ]
+    }
+   ],
+   "source": [
+    "display_board(challenge)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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A2Sfss88+SXZukF166aU56KCD8rd/+7eZNm1a7rrrrnzsYx/LT3/60/zsZz9LU5NeJLD3mjFjRr7yla9UHUZlSh7/9sc7s3nT2qrDqFTTwrel+xe3puvLX0nT/b9N/Tf3pumsP09t+rSqQxtSJedBSTrWJW2/7ts699+SHDgzqdUGJyaGh5JrQOnzgHOBHo2WAy9/+ctzySWX7Pj6/PPPz2c/+9l+b2/s2LH50z/904x4UtN49OjRee1rX5vbbrvt2YQKMGw02lwAaJA9xU033ZQkOf744592mdbW1iQ7N8i+//3v58ADD9zx9Stf+coceOCBWbhwYX7+85/veDAtwN6oq6srmzdvzj777LPTD72lKHn8v7z6I/nl1R+pOoxK1UaOzMgL/jLb/+f/Sve116V2+Lw0/ekbqg5ryJWcByVpvbvv63T8IdnQmjxn+sDHw/BRcg0ofR5wLtCjkXJg7Nix+Yd/+IcdX3/4wx9+Vs2xlpaWXH/99Tt+7/HYY49l7NixGTlyZD784Q/nmmuuyT333PNswwaoXCPNBUAPlzXt4oEHHkjS83DZ3dm+fXuWLFmSZOcG2ZObY0948YtfnCRZs2bNQIcJMKRWrFiRY445JitWrKg6lEqUPP7Djz8rb/z//Wi3H0VpaUlGjUqS1I55cWoFXhlech6U5Pf3Du167D2KrwEFzwPOBXo0Ug586EMfysyZM5MkP//5z/N//s//6fe2dm2OrVu3Lq961at2XJ02evTofPnLX372QQMMA400FwA9XEG2i46OjiTJ5s2bd/v6VVddlbVr12b8+PE55JBDnnFbN998c5Jk7ty5/Y5n1qxZw+L2jJ8+87ZMHD8lbW1tmTbtmKrDYYj5/2/M9+CMM87o9bJtbW1Jkuuvv75PzxC44oor+hjV0GnU8Y8YtU/eeNF9A7a9/SbPykGHnzBg29ud2bNmpWvb7ufdvqqPHp1c/sUB2daObdbr6frUZ5Lt25KDpqf7m/+Sple+IrXnTRmQ7c+eNTu1xx8fkG31RV9yIOlfHgznGsDuXf7+ezNm1Ng+r/etK/81l7/rfw5CRAymRp0LB3ou2NvmgdLPBfqiUXOgu7v7aV8bO3Zs3ve+9yVJtmzZkne/+93PuPwz2V1z7IQTTsidd96ZpUuX5g1veEMOO+yw/NEf/VH++I//OL/85S+fdlvD5XcfQFn8TASNYfLkybn99tv7ta4G2S4mT56c9evX54477shxxx2302ttbW254IILkiTz589P7RketLBmzZp86EMfyoknnpijjjqq3/E8UXir9sSDdru6ulwRVyD//435HnR2dvZ62S1btuz43Jf1hvN71ajjHzmm77/YrtrDbQ9n+9bev6/PqHlMRg3Mlnbo/u41qd/9qzT92bvSdNwfZ/v7/2e6PvWZjLj04mc8F+ith9seTrZsHYBI+6Yvx3LSvzwYzjWA3du6bUu/GmQbHlvn/3sv1Khz4UDPBXvbPFD8uUAfNGwOPIPTTz89++23X5KeZ7Dfd1//mqnP1BxLkscffzwXX3xx/vEf/zFJcvbZZz9jg2y4/O4DKIufiQANsl2ccMIJWb58eS6++OK85jWvyezZs5Mkt912W97xjndk7dqehxM/U9Orvb09p556akaPHp2vfe1rzyqeKVOmDIu/onrivrojRozI1KlTK46Goeb/vzHfg7Fje//Lk+bm5h2f+7LecH6vGnX8I0btM+T7fLaeN+V5A3oF2aMDsqX/2t6aNen+2hWpvWB2mt5yWmojRqTp7QvT/Q//mO7vXpMRbzz1We/jeVOeV8kVZH05lpP+5cFwrgHs3iPrV2bfscf2eb2NW9b4/94LNepcOJBzwd44D5R+LtAXjZoD3d3dT9twete73rXj33/3d3/Xr+3vqTn2hG9961v59Kc/nf333z9vectb8t73vvdp79YzXH73AZTFz0TQGCZPntzvdTXIdrFo0aJ885vfzEMPPZR58+Zlzpw52bJlS1auXJmTTjopM2bMyA9/+MOdnj/2ZJs3b86CBQuyatWq3HLLLZky5dndduO+++5LS0vLs9rGQLjl75Ot7T0nra2trVWHwxDz/9+Y70Ff7pm9dOnSfO1rX8vrXve6zJs3r9frXXTRRf0JbUg06vi3bk8uvGrId/us3HvffRkzQGckHV3b85ybBuaZKPXu7nR98tNJd3dGXPCXqf1Xo7zpLaelvuTf0/21K9L0R8c+61ts3XvfvWkZMfSnZH29b35/8mA41wB2r21ZsvT6vq3TNCL5u3/5cEaP/fDgBMWgadS5cKDmgr11Hij9XKAvGjYHOjoybty4p3x/xIgRO56Vfv/99/frVkS9bY4lPVdYfPe7382ZZ56ZMWPG5Mgjj3zaq8iGy+8+gLL4mQjw5zm7mDZtWm655ZacfPLJaW5uzurVqzNx4sRcfvnlue6663LvvT1PIN9dg2zbtm057bTTcvvtt+cHP/hBDjvssKEOH2BQzJ49O0uWLNlxVW1pSh9/qboXfyf1ZcvT9K63p3bQQTu+XxsxIiP+6i+T7q50feozqdfrFUY5dORBGZ47Oxndx7uzTZrT93XY+5RYA8wDPFkj5MCcOXN2XPEw2M2xJzx5P0cffXSf9wkwnDTCXADsTINsN+bOnZtrr702mzZtyqZNm3LrrbfmrLPOSkdHR1avXp2mpqYcfvjhO63T3d2dhQsX5sc//nG+973v5dhj+35rGoDhatSoUZk4cWJGjRropzvtHUoff4nqDz6Y7n/8p9TmzknTm/70Ka/XZhycprcvTP2eX6f7u9dUEOHQkwdlGDEyOWJBUhvRu+VbJiazjx/cmBgeSqsB5gF21Qg58OTfYzxTU2t3+tMc23U/RxxxRJ/2CTDcNMJcAOxMg6wPli5dmnq9nlmzZj3lPrPvf//78+1vfzvnn39+xo4dm1/+8pc7Ph59dCCfhgIw9B588MGcffbZefDBB6sOpRIljn/aYa/Kef9cz9En/9XTLnPeP9dz6l9dO4RRDZ3aQQdl1HXfy8jPfXrHLbV2NeJtb82of7t+QJ4/szcoMQ9K9ZzpyQvflIwc88zL7Ts5edFbk1HNQxMX1SqtBpgHnAvsqhFy4Mm3XezL7yn62xzbdT+7u+0jwN6kEeYCYGcaZH1wzz33JNn97RV/8IMfJEk+8YlP5Ljjjtvp47rrrhvSOAEG2qZNm3LzzTdn06ZNVYdSidLHD4k8KM3Eg5KXnZW84E+Slv13fu2A5ydH/WlyzMJkjMfFFEMNoHSNkANf/epXM2rUqIwfPz7//M//3Ov1Ro8evaO51ZfmWJKsXr06++23X8aMGZO3v/3t/YobYLhohLkA2FkFj8Hdez1Tg2z16tVDHA0AAAyekWOS6S/s+fjZ/00e70hGt/Q0xwDYO23fvj3t7e19Wmf9+vU54YQT8q1vfSuLFi3q0+0Zu7u7s3Hjxr6GCQAwJDTI+uCZGmQAANCoarWdPwNQlvXr1+c1r3lN1WEAAAwoDbI+uOmmm6oOAQAAAAAAgGfJM8gA2KNJkyblwgsvzKRJk6oOpRKljx8SeQClUwMonRwAwFwAjccVZADs0QEHHJAzzjij6jAqU/r4IZEHUDo1gNLJAQDMBdB4XEEGwB5t3LgxN9xwQ7EP2C59/JDIAyidGkDp5AAA5gJoPBpkAOxRa2trzj///LS2tlYdSiVKHz8k8gBKpwZQOjkAgLkAGo8GGQAAAAAAAEXRIAMAAAAAAKAoGmQAAAAAAAAURYMMgD1qbm7O3Llz09zcXHUolSh9/JDIAyidGkDp5AAA5gJoPCOrDgCA4W/mzJn5zne+U3UYlSl9/JDIAyidGkDp5AAA5gJoPK4gAwAAAAAAoCgaZADs0bJlyzJ//vwsW7as6lAqUfr4IZEHUDo1gNLJAQDMBdB4NMgA2KN6vZ5t27alXq9XHUolSh8/JPIASqcGUDo5AIC5ABqPZ5ABQAMZPSK5+K1VR9E3o0cM3LbGNo3I+le/ZuA2OATGNg3gGwDAXjcXDPQ8UPq5AMnYsWPT3t4+YNv75OX/ksc6OrNvy9hc8N7Tn/L1QBg7duyAbAcAoC80yACggdRqyZiCZ/darZaWEQW/AQAUPxeUfi7Af+VAS8uAbW/0mOaM3taV0WOa09LS8pSvAQD2Vm6xCAAAAAAAQFH8XRkAezRz5sxcc801mT59etWhVKL08UMiD6B0agClkwMAmAug8WiQAbBHzc3NmTVrVtVhVKb08UMiD6B0agClkwMAmAug8bjFIgB7tGbNmnzwgx/MmjVrqg6lEqWPHxJ5AKVTAyidHADAXACNR4MMgD3asGFDrr766mzYsKHqUCpR+vghkQdQOjWA0skBAMwF0Hg0yAAAAAAAACiKBhkAAAAAAABF0SADAAAAAACgKBpkAOxRU1NTjjnmmDQ1lTltlD5+SOQBlE4NoHRyAABzATQe2QzAHnV3d+e2225Ld3d31aFUovTxQyIPoHRqAKWTAwCYC6DxaJABAAAAAABQFA0yAAAAAAAAiqJBBgAAAAAAQFE0yADYowkTJmTBggWZMGFC1aFUovTxQyIPoHRqAKWTAwCYC6DxjKw6AACGv2nTpuWSSy6pOozKlD5+SOQBlE4NoHRyAABzATQeV5ABsEdbt27NAw88kK1bt1YdSiVKHz8k8gBKpwZQOjkAgLkAGo8GGQB7tHLlypx44olZuXJl1aFUovTxQyIPoHRqAKWTAwCYC6DxuMUiADSQej15vKvqKPpm9IikVhuYbdXr9XR2711vwNimEakN1BsAwF43Fwz0PFD6uQDU6/V0dnZWHUafjB071vkgAFRAgwwAGsjjXcmFV1UdRd9c/NZkzACdkXR2d+U5N/1oYDY2RNa/+jVpGeGUDGCg7G1zwUDPA6WfC0BnZ2fGjRtXdRh90t7enpaWlqrDAIDiuMUiAAAAAAAARdEgAwAAAAAAoChuYgDAHs2bNy/Lly+vOozKlD5+SOQBlE4NoHRyAABzATQeV5ABAAAAAABQFA0yAPZo1apVOf3007Nq1aqqQ6lE6eOHRB5A6dQASicHADAXQOPRIANgjzo7O3P33Xens7Oz6lAqUfr4IZEHUDo1gNLJAQDMBdB4NMgAAAAAAAAoigYZAAAAAAAARdEgAwAAAAAAoCgaZADs0dSpU3PxxRdn6tSpVYdSidLHD4k8gNKpAZRODgBgLoDGM7LqAAAY/vbbb7+8/vWvrzqMypQ+fkjkAZRODaB0coBnY5999snmzZurDgN4lswF0HhcQQbAHq1bty7f+MY3sm7duqpDqUTp44dEHkDp1ABKJwfKM3LkyBx55JF597vfnU996lO5/PLL86UvfSmf/vSnc+aZZ+aoo47KqFGj9ridWbNmZcWKFVm4cOEQRA0MJnMBNB5XkAGwR21tbbnoooty1FFHZeLEiVWHM+RKHz8k8gBKpwZQOjlQjhe+8IU5++yz87a3vS0tLS3PuGxnZ2euvPLK/N3f/V3uuOOOp7w+a9as3HzzzZk6dWr+8R//MY899li+//3vD1bowCAzF0DjcQXZM1i7dm0WLVqUQw89NM3NzZk+fXrOO++8dHR05Mwzz0ytVstll11WdZgMsm1bko4/JJ3rk+2PVx0NVdjannR39/y7Xq82Fhgqrct+ks+9vZb/vO7Sp13mc2+v5XuXnjKEUQ2trq9dkW2vfV26b/i3p7xWr9ez/a8uzLaTX5/6qtVDHxwMoe6upP7EPNhtLqQcpc8DzgUozZw5c/LTn/40d9xxR/78z/98j82xJBk7dmzOPPPM/Od//md+9rOfZe7cuTtee3JzLEl+/etf59///d8HLX4AoO9cQfY07rrrrpx00kl55JFH0tLSksMOOywPP/xwPv/5z+f+++/fcSntUUcdVW2gDIp6PfnD6qT1rmTt/f/9/aYRyaQ5ybSjkglTKgqOIdG1Lfndip5j4LHf/ff3H+9IVv4smXpkss+EysIDhkDTOxam+5e3puvyL6d29ItSO/CAHa91f+e7qf/qnjS9+4zUDplRXZAwiLY8lrTenTx8T/J4Z8/3Hu9M/uOfkmkvTCbPSUbs+c5SsNcyD0AZRowYkQ984AP52Mc+lubm5h3f37hxY66//vrcdtttufPOO7N27dokyQEHHJAXvvCFefGLX5yTTz45Eyb0/GD48pe/PHfeeWc+8pGP5Hvf+15uvPHGHc2xu+++O3/yJ3+SP/zhD0M/QADgaWmQ7cbatWuzYMGCPPLII/nABz6Qj3zkIxk/fnyS5JJLLsmFF16YkSNHplarZf78+RVHy0Dr2pbcc+3OjbEndHclbUt7PqYfncx+VVKrDXmIDLLNG5I7v5N0Ps0tpVf/R/LA7cm8k5LJc3e/DLD3q40alZEXfCDbzz0/XZ/+bEZ+/KIkSf2h1nRf8fXU5rwgTW9+U8VRwuD43Ypk6Q96zn12ten3yfIfJg/8R3LUnyZjnzP08cFQMA9A4xszZkyuuuqqnHrqqTu+d9999+WTn/xkvvnNb6ajo2O36/3kJz9J0nMF2dve9rZccMEFecELXpAxY8bkE5/4RD7ykY9kn332SaI5BgDDmVss7sa5556b1tbWnHPOObn00kt3NMeSZNGiRTnyyCOzffv2zJgxI/vuu2+FkTLQuruTX31v982xXT30n8m9Nw9+TAytrR3Jf37r6ZtjT6h3J7++Lvndb4Ymrqq1tLTkpS99aa9uM9KISh9/yWqzDk3T6W9J/T/vSPd1P0i9qytdl1ya1OsZccEHUhsxouoQh4w8KMfv7+v5Y6HdNceerHN9z5y5ZdPQxEW1Sq0B5gGeUGoONLJRo0blO9/5zo7mWHd3dz75yU9m/vz5+fKXv/y0zbEn6+zszFe/+tUceeSRufjii9PV1TN5PtEc+9WvfqU5Bg3EXACNxxVku1i+fHmuuuqqHHDAAfn4xz++22WOPvro3H333TnyyCN3fO+WW27Jxz72sSxdujTr1q3LgQcemJe+9KX56Ec/utM9qBneHv5Vz60Ve+uhO5LnzkqeM33QQmKI3Xtzzy2lemvZDcn+M5KRYwYtpGFhxowZ+cpXvlJ1GJUpefzbH+/M5k1rqw6jUk0L35buX9yari9/JU33/zb139ybprP+PLXp06oObUiVnAcl2f54z5VjvbV1U8/cOf/1gxcTw0PJNaD0ecC5QI+Sc6BRfe5zn8vrXve6JEl7e3ve+MY35sYbb+zXtrZu3ZqvfvWrOfPMM3PAAf99O9Y777xTcwwaiLkAGo8G2S6uvPLKdHd3Z+HChRk3btxul3niL4Ge3CBbv359jjjiiLz3ve/Nc5/73LS2tubjH/94jjvuuPz617/OtGll/PC0N6vXk4fu6vt6rXdpkDWKrR3J7+/t2zpd25K2Zcn0Fw5OTMNFV1dXNm/enH322ScjCvxL6ZLH/8urP5JfXv2RqsOoVG3kyIy84C+z/X/+r3Rfe11qh89L05++oeqwhlzJeVCSR5YnXY/3bZ1H70u2tidjdn/qTIMouQaUPg84F+hRcg40ohNOOCF/8Rd/kSTZvHlzXve61+WWW27p9/ZmzZqVm2++eUdzrLu7O01NTXnXu96VK6+8Mj/84Q8HJG6gWuYCaDwaZLu46aabkiTHH3/80y7T2tqaZOcG2etf//q8/vU7/+nsMccckxe84AW5+uqrc9555w1CtAykx9qSjn78YeTv7+t5YP3osQMfE0OrbWnPrRP7as2vGr9BtmLFipx22mlZvHhx5s2bV3U4Q67k8R9+/FmZ9Udv3u1r//qJ1wxxNBVqaUlGjUq2b0/tmBen1lTeXapLzoOSPPyrvq9TrycP/zo55I8HPh6Gj+JrQMHzgHOBHsXnQAMZN25cvvrVr+74+i//8i8HpDk2derUJD3PHLviiivymc98Jkny5S9/OYcffngee6wPtyoBhiVzATQeDbJdPPDAA0mSgw8+eLevb9++PUuWLEmyc4Nsd/bff/8kyciR/X+bZ82alaZh8MPXp8+8LRPHT0lbW1umTTum6nAGxUvmvClnnfi5Pq9X706Of+mJeeDRXw9CVMNDCf//SXLGn1ycVx2xsM/r/eHhzkybNnsQIhpcZ5xxRq+XbWtrS5Jcf/31ufPOO3u93hVXXNHHqIZOo45/xKh98saL7huw7e03eVYOOvyEAdve7syeNStd2zYPyLbqo0cnl39xQLa1Y5v1ero+9Zlk+7bkoOnp/ua/pOmVr0jteVMGZPuzZ81O7fE+XrIzAPqSA0n/8mA41wB27+/+YmnGjpnQ5/WuuPyqfPW0DwxCRAymRp0LB3ou2NvmgdLPBfqiUXNgoL3xz/5XWsbtm7ZH2jJt2rSnfD3cdHc/8189vvvd785BBx2UJPnxj3+cyy+/vN/72l1z7Ilnjp100kl57Wtfm+nTp+fMM8/c0TB7uu0Mh9/9QGn8TASNYfLkybn99tv7ta4G2S6eeAjr5s27Pzm/6qqrsnbt2owfPz6HHHLIU17v6upKd3d3Hnjggfy//+//m8mTJ+ctb3lLv+N5ovBW7YkHzXZ1dWXNmjUVRzM4HpvS/7/mWveH9Q37viRl/P8nyZbNW/u1XlNt5F75vnR2dvZ62S1btuz43Jf1hvP70qjjHzlm77uc9eG2h7N9a+/f12fUPCajBmZLO3R/95rU7/5Vmv7sXWk67o+z/f3/M12f+kxGXHpxarXas97+w20PJ1v6V3+ejb4cy0n/8mA41wB2r5b+3Spm69Zt/r/3Qo06Fw70XLC3zQPFnwv0QcPmwADr/q+fB7v/6+fBXb/e25x99tk7/v0//+f/TL1e79d2nqk59sS2f/Ob3yRJ/uIv/iKf/exnn3Zfw+V3P1AaPxMBGmS7mDx5ctavX5877rgjxx133E6vtbW15YILLkiSzJ8/f7c/DL3yla/ccYXZoYcemptuuikHHnhgv+OZMmXKsPgroifuqztixIgdJ3+NpmlMV5/XqdfrqdVqGTOu1rDvS1LG/3+SbK/174fyxzav3Svfl7Fje//Lk+bm5h2f+7LecH5fGnX8I0btM+T7fLaeN+V5A3oF2aMDsqX/2t6aNen+2hWpvWB2mt5yWmojRqTp7QvT/Q//mO7vXpMRbzz1We/jeVOeV8kVZH05lpP+5cFwrgHs3qbNa7NPPx4mtr3e4f97L9Soc+FAzgV74zxQ+rlAXzRqDgy0pv/6ebDpv34e3PXr4aa7u/tpG07HH398XvCCFyRJbr755ixfvrxf+9hTcyxJ7r333tx444054YQTMmvWrPzJn/xJbrzxxt1ub7j87gdK42ciaAyTJ0/u97oaZLs44YQTsnz58lx88cV5zWtek9mze26bdtttt+Ud73hH1q7teUjVUUcdtdv1v/rVr2bDhg1ZtWpVPvnJT+a1r31tlixZsuPy/b6677770tLS0q91B9Itf9/z8PUpU6bseAZbo+nentxyedKXn8tqtVomTEnuWvbLwQtsGCjh/z9JNv0+ufXrfV/vRa9+Xlo/tve9LytWrOj1skuXLs3Xvva1vO51r+vTfbYvuuii/oQ2JBp1/Fu3JxdeNeS7fVbuve++jBmgM5KOru15zk0/GpBt1bu70/XJTyfd3RlxwV+m9sQvg95yWupL/j3dX7siTX907LO+xda9992blhFDf0rWlxxI+pcHw7kGsHsrf56s7sdpzYc/895cOvm9Ax8Qg6pR58KBmgv21nmg9HOBvmjUHBhof/vFb+Sx9o5Mmdzz8+CuXw83HR0dGTdu93/s8Sd/8ic7/v2Vr3ylX9vvTXPsCV/+8pdzwgk9tyh99atf/bQNsuHyux8ojZ+JAH+esotFixZl//33z0MPPZR58+bliCOOyKxZs3Lsscfm+c9/fl796lcnefrnj73gBS/IH/3RH+X000/Pj3/842zatCmXXHLJUA6BfmoamUw9ou/rTTtqwEOhIuOfm0zoxx/2TH3mxxE2hNmzZ2fJkiU7/migNKWPv1Tdi7+T+rLlaXrX21N70h+61EaMyIi/+sukuytdn/pMv2/Ls7eRB2WYNj9JH+8Yt+/kng8aW4k1wDzAk5WYA43o6KOP3vHvW265pc/r96U5liQ///nPd7tvYO9kLoDGo0G2i2nTpuWWW27JySefnObm5qxevToTJ07M5Zdfnuuuuy733ntvkqdvkD3Zfvvtl0MPPTQrV64c7LAZINOPTprH9375CVOSSS8YvHgYerNentT68PiV6S9Kxu43aOEMG6NGjcrEiRMzatRAP91p71D6+EtUf/DBdP/jP6U2d06a3vSnT3m9NuPgNL19Yer3/Drd372mggiHnjwoQ/O+ycF9+P1drSk59BWDFw/DR2k1wDzArkrLgUb1ohe9KEny6KOP5qGHHurTun1tjiXJww8/nEceeSSJBhk0AnMBNB4Nst2YO3durr322mzatCmbNm3KrbfemrPOOisdHR1ZvXp1mpqacvjhh+9xO7///e/zm9/8JjNnzhyCqBkIY1qSF56WjOlFk2z8pOTIN/ZceUbj2G9acsQpSVMvmmRT5iWzXzXoIQ0LDz74YM4+++w8+OCDVYdSiRLHP+2wV+W8f67n6JP/6mmXOe+f6zn1r64dwqiGTu2ggzLquu9l5Oc+veOWWrsa8ba3ZtS/XT8gz5/ZG5SYB6U69JXJ83pxVX1tRHL4ycnE/t1JnL1MaTXAPOBcYFel5UCjeu5zn5skuf/++/u0Xn+aY094Yl/777+/54zBXs5cAI3HzNwHS5cuTb1ez6xZs57yIMa3v/3t+ehHP5rvfve7+clPfpIvf/nLedWrXpWRI0fm/PPPryhi+qNl/+TYhT1Xk40c89TXx4xLnv+S5MVvTUb37Vme7CWeOyt58f/Tc3VgbTdVctxzk8NO7PnY3euNaNOmTbn55puzadOmqkOpROnjh0QelKRWS+a+NjnspJ4/CNrd68+dnRzzNlfSl0QNoHRyYO/X1NSUM888M+ecc04++9nP9mndT3/60/1qjiXJ5z73uZxzzjn58z//89RqfbyPMTCsmAug8bj2pQ/uueeeJLu/veIf//Ef5+tf/3o+97nPZcuWLZk+fXqOP/74/O///b9z8MEHD3WoPEtjxiUvOD459KXJ2t8my/4t6Xo8GdmcvPSsxB99Nb59JyVHLEi2tid/WJX85uaeY2DUPskfvaPnl4MA0KhqteR585IphyWPPZLcuTjZvrXnj4eO+7OecyUA2Jt0d3fna1/7Wr/Wfec735kbb7wxI0aM6FNzLEm+/e1v92ufAMDg0yDrg2dqkJ1zzjk555xzhjokBtmI0cmkOcm9P+lpjowYqTlWmjHjem4zdf+SnmOgaYTmGADlqNV6nrk6YlRPg2zEKM0xAMqzfv36nHDCCWlqaupTcwwAGN40yPrgmRpkAAAAADSm9evXVx0CADDANMj64Kabbqo6BIBKTJo0KRdeeGEmTdrNw2gKUPr4IZEHUDo1gNLJAQDMBdB4NMgA2KMDDjggZ5xxRtVhVKb08UMiD6B0agClkwMAmAug8XiaEgB7tHHjxtxwww3ZuHFj1aFUovTxQyIPoHRqAKWTAwCYC6DxaJABsEetra05//zz09raWnUolSh9/JDIAyidGkDp5AAA5gJoPBpkAAAAAAAAFEWDDAAAAAAAgKJokAEAAAAAAFAUDTIA9qi5uTlz585Nc3Nz1aFUovTxQyIPoHRqAKWTAwCYC6DxjKw6AACGv5kzZ+Y73/lO1WFUpvTxQyIPoHRqAKWTAwCYC6DxuIIMAAAAAACAomiQAbBHy5Yty/z587Ns2bKqQ6lE6eOHRB5A6dQASicHADAXQOPRIANgj+r1erZt25Z6vV51KJUoffyQyAMonRpA6eQAAOYCaDyeQQYADWT0iOTit1YdRd+MHjFw2xrbNCLrX/2agdvgEBjbNIBvAAB73Vww0PNA6ecCMHbs2LS3tw/Y9j55+b/ksY7O7NsyNhe89/SnfD0Qxo4dOyDbAQD6RoMMABpIrZaMKXh2r9VqaRlR8BsAQPFzQennAlCr1dLS0jJg2xs9pjmjt3Vl9JjmtLS0POVrAGDv5RaLAAAAAAAAFMXflQGwRzNnzsw111yT6dOnVx1KJUofPyTyAEqnBlA6OQCAuQAajwYZAHvU3NycWbNmVR1GZUofPyTyAEqnBlA6OQCAuQAaj1ssArBHa9asyQc/+MGsWbOm6lAqUfr4IZEHUDo1gNLJAQDMBdB4NMgA2KMNGzbk6quvzoYNG6oOpRKljx8SeQClUwMonRwAwFwAjUeDDAAAAAAAgKJokAEAAAAAAFAUDTIAAAAAAACKokEGwB41NTXlmGOOSVNTmdNG6eOHRB5A6dQASicHADAXQOORzQDsUXd3d2677bZ0d3dXHUolSh8/JPIASqcGUDo5AIC5ABqPBhkAAAAAAABF0SADAAAAAACgKBpkAAAAAAAAFEWDDIA9mjBhQhYsWJAJEyZUHUolSh8/JPIASqcGUDo5AIC5ABrPyKoDAGD4mzZtWi655JKqw6hM6eOHRB5A6dQASicHADAXQONxBRkAe7R169Y88MAD2bp1a9WhVKL08UMiD6B0agClkwMAmAug8WiQAbBHK1euzIknnpiVK1dWHUolSh8/JPIASqcGUDo5AIC5ABqPBhkAAAAAAABF8QwyAGgg9XryeFfVUfTN6BFJrTYw26rX6+ns3rvegLFNI1IbqDcAgL1uLhjoeaD0cwEoXb1eT2dnZ9Vh9MnYsWOdDwNQCQ0yAGggj3clF15VdRR9c/FbkzEDdEbS2d2V59z0o4HZ2BBZ/+rXpGWEUzKAgbK3zQUDPQ+Ufi4Apevs7My4ceOqDqNP2tvb09LSUnUYABTILRYBAAAAAAAoir/RAmCP5s2bl+XLl1cdRmVKHz8k8gBKpwZQOjkAgLkAGo8ryAAAAAAAACiKBhkAe7Rq1aqcfvrpWbVqVdWhVKL08UMiD6B0agClkwMAmAug8WiQAbBHnZ2dufvuu9PZ2Vl1KJUoffyQyAMonRpA6eQAAOYCaDwaZAAAAAAAABRFgwwAAAAAAICiaJABAAAAAABQFA0yAPZo6tSpufjiizN16tSqQ6lE6eOHRB5A6dQASicHADAXQOMZWXUAAAx/++23X17/+tdXHUZlSh8/JPIASqcGUDo5AIC5ABqPK8gA2KN169blG9/4RtatW1d1KJUoffyQyAMonRpA6eQAJZsxY0aOOeaYvOQlL8nRRx+dAw88sE/rL1iwIAsXLhyk6GDomAug8biCDIA9amtry0UXXZSjjjoqEydOrDqcIVf6+CGRB1A6NYDSyQFKMmnSpLz73e/O8cf//9m7+/io6jP//++ZSWDIEMAYS2ISiIVEIJhQKd7UrtUWuqKCN9WCRSou9Y66oEsJv21t7SpbGqS69YvdoqxLt0VKBbQIFqsLWpa2FORGJEEIC4SEiSWFhJA7ksz8/ghkIQQmEybzmZzP6/l48IiTOefkusZc5zozV845N2vkyJHt/s4fOnRIH374oVavXq2lS5eqtra23W2NGzdOy5cvV1xcy0eQS5Ys6dLYga5ELwCchzPIzqOiokL5+fkaPHiwvF6vMjIyNGPGDNXU1Gjq1KlyuVxasGCB6TABAAAAAACAi3bVVVdp6dKlOnTokH70ox9pzJgx5x0CZGRk6M4779SiRYtUVlamF154QZ/5zGfOWub0cKxHjx5yu90aM2ZMNNIAAKDDGJC1Y/v27brqqqv03HPPqby8XMOGDVNjY6NefPFFTZgwQUVFRZKkESNGmA20i52skfZvkra+Lp089YdATQ1SfbXZuKIlEJD+ulf66Lf/l39jvXTskBQMmo0tWmr+Jn2y7oz866TSHVLTSbNxAeh6pYXv66f3u/ThmvnnXean97v02/m3RzGq6Gp+dbEav3qrAmt/f85zwWBQTd+Zrcbbxiu4/0D0gwOipPaYtOd96WRdy+OTddKhrS3HhIDT2d4HOBYA7BEXF6cf/OAH+vDDDzVx4kTFx8e3Puf3+7V69Wr9v//3//T888/r3//93/X+++/r+PHjrcv069dPTzzxhHbt2qUJEyZIOns4Jkm/+tWv9A//8A/RTQwAgBC4xGIbFRUVGjdunMrLyzVz5kw9/fTTSkxMlCTNmzdPs2fPVlxcnFwul3Jzcw1H2zUCTdIn66XDO6Vg4OznmhuljS9L/YdIQ8ZIcT3MxNjVPt0j7VkvNbQZBgaapA+XSb5LpWF/L/W93Ex8Xa2+WipcKx09ePb3A83S7nelvR9IA0dJV1wnuVxmYgSAruaePEmBP29S88JX5Bp5tVyXJbc+F1j5poIf7ZT7H6bIdUWmuSCBLnKyRtq1Vvrb/rO/H2xu+eOZ4g3SgJHSZ2/gWADORR8AYIPU1FS99dZbGjlyZOv3/vrXv2rRokVatGiR9u/f3+56LpdLI0eO1GOPPab77rtPvXr1UnJysn7961/rscce0/XXX3/WcOyBBx5QIBBod1sAAJjCGWRtTJ8+XaWlpXr88cc1f/781uGYJOXn5ysvL09NTU3KzMxUnz59DEbaNQJN0raVUtmOc4djpwWDUnmRtPU3zjyTqOwjaeeqc4djZ6r5m/Thb6SjJdGLK1rqqqTNr507HDtT80npfze2DMtsOZvOdj6fTzfccIN8Pp/pUIywPX9bueLjFTdrplRfr+bn/631+8FDpQos/i+5hlwp971fMxdglFEH9mg4IW1eeu5w7EzNjdL+P0u7fsexgC1s3AfQB3AmG2sAzpeRkaH/+Z//aR2ONTU16dlnn9WAAQP0ve9977zDManlTNotW7Zo6tSpGjhwoH7zm9+0PvelL32J4RgciV4AOA8DsjMUFRVp2bJlSk5O1ty5c9td5vRBQ15e3nm3M3bsWLlcLv3whz/sijC71J710rEODn2Ol0tF73RtPNFWeVgqerdjywaapB1vOuuSk8FgS04XGg6eqewjqXRbl4aEGJGZmalFixYpMzPTdChG2J6/zVxZg+We+HUFP9yqwJr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+      "text/plain": [
+       "<Figure size 2228.78x9983.17 with 1 Axes>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qc = grover_algorithm(challenge, rep=1)\n",
+    "qc.draw('mpl')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'01110': 389, '01101': 352, '01001': 333, '01000': 365, '00011': 4738, '11100': 342, '11000': 377, '11010': 351, '10111': 326, '11001': 360, '10100': 355, '10010': 344, '01011': 383, '10001': 332, '10110': 350, '00110': 379, '00010': 330, '10011': 334, '00000': 380, '00001': 345, '11111': 354, '11011': 355, '10101': 353, '00101': 4615, '11101': 341, '01100': 347, '10000': 380, '00111': 329, '11110': 372, '01010': 348, '00100': 329, '01111': 412}\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "counts_without_qiskit_convention = circuit_execute(qc, shots=20000)\n",
+    "print(counts_without_qiskit_convention)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot_histogram(counts_without_qiskit_convention, color='midnightblue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'00011': 4738, '00101': 4615}\n"
+     ]
+    }
+   ],
+   "source": [
+    "possible_results = filter_values_above_average(counts_without_qiskit_convention)\n",
+    "\n",
+    "print(possible_results)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "List 1: [['O', 'X', 'O'], ['O', 'O', 'O'], ['X', 'X', 'X']]\n",
+      "List 2: [['O', 'X', 'O'], ['O', 'X', 'O'], ['O', 'X', 'X']]\n"
+     ]
+    }
+   ],
+   "source": [
+    "completed_lists = complete_lists_with_dictionary(challenge, possible_results)\n",
+    "\n",
+    "for i, lst in enumerate(completed_lists, start=1):\n",
+    "    print(f'List {i}: {lst}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Challenge:\n",
+      "O | X |  \n",
+      "---------\n",
+      "  |   | O\n",
+      "---------\n",
+      "  |   | X\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 1:\n",
+      "O | X | O\n",
+      "---------\n",
+      "O | O | O\n",
+      "---------\n",
+      "X | X | X\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 2:\n",
+      "O | X | O\n",
+      "---------\n",
+      "O | X | O\n",
+      "---------\n",
+      "O | X | X\n",
+      "---------\n",
+      "\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Challenge:')\n",
+    "display_board(challenge)\n",
+    "print('\\n')\n",
+    "\n",
+    "for index, lst in enumerate(completed_lists):\n",
+    "    print('Solution {}:'.format(index + 1))\n",
+    "    display_board(lst)\n",
+    "    print('\\n')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "WOMANIUM",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/challenges/QOSF challenge/QuantumVoyagers/app/grover/grover_circuit_complete_image/file.tex b/challenges/QOSF challenge/QuantumVoyagers/app/grover/grover_circuit_complete_image/file.tex
new file mode 100644
index 0000000..1122f84
--- /dev/null
+++ b/challenges/QOSF challenge/QuantumVoyagers/app/grover/grover_circuit_complete_image/file.tex	
@@ -0,0 +1,33 @@
+\documentclass[border=2px]{standalone}
+
+\usepackage[braket, qm]{qcircuit}
+\usepackage{graphicx}
+
+\begin{document}
+\scalebox{1.0}{
+\Qcircuit @C=1.0em @R=0.2em @!R { \\
+	 	\nghost{{q}_{0} :  } & \lstick{{q}_{0} :  } & \gate{\mathrm{X}} \barrier[0em]{21} & \qw \barrier[0em]{21} & \qw & \ctrl{3} & \ctrl{4} & \qw & \qw & \ctrl{1} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \ctrl{9} \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{21} & \qw \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \ctrl{9} \barrier[0em]{21} & \qw & \qw & \qw & \qw & \ctrl{1} & \qw & \qw & \ctrl{4} & \ctrl{3} \barrier[0em]{21} & \qw \barrier[0em]{21} & \qw & \qw & \qw \barrier[0em]{8} & \qw & \qw & \qw & \qw \barrier[0em]{8} & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw & \qw & \qw \barrier[0em]{21} & \qw & \qw & \qw\\
+	 	\nghost{{q}_{1} :  } & \lstick{{q}_{1} :  } & \gate{\mathrm{I}} & \qw & \qw & \qw & \qw & \qw & \ctrl{3} & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{8} & \ctrl{8} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{8} & \ctrl{8} & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \ctrl{3} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{2} :  } & \lstick{{q}_{2} :  } & \gate{\mathrm{I}} & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{15} & \ctrl{3} & \qw & \ctrl{2} & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{7} & \ctrl{7} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{7} & \ctrl{7} & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{2} & \qw & \ctrl{3} & \ctrl{15} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{3} :  } & \lstick{{q}_{3} :  } & \gate{\mathrm{X}} & \qw & \qw & \ctrl{3} & \qw & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{6} & \ctrl{6} & \ctrl{6} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{6} & \ctrl{6} & \ctrl{6} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \qw & \ctrl{3} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{4} :  } & \lstick{{q}_{4} :  } & \gate{\mathrm{H}} & \qw & \qw & \qw & \ctrl{4} & \ctrl{1} & \ctrl{3} & \qw & \qw & \qw & \ctrl{2} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{5} & \ctrl{5} & \ctrl{5} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{5} & \ctrl{5} & \ctrl{5} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{2} & \qw & \qw & \qw & \ctrl{3} & \ctrl{1} & \ctrl{4} & \qw & \qw & \qw & \gate{\mathrm{H}} & \gate{\mathrm{X}} & \qw & \qw & \ctrl{1} & \qw & \qw & \gate{\mathrm{X}} & \gate{\mathrm{H}} & \qw & \meter & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{5} :  } & \lstick{{q}_{5} :  } & \gate{\mathrm{H}} & \qw & \qw & \qw & \qw & \ctrl{10} & \qw & \qw & \ctrl{3} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{4} & \ctrl{4} & \ctrl{4} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{4} & \ctrl{4} & \ctrl{4} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{3} & \qw & \qw & \ctrl{10} & \qw & \qw & \qw & \qw & \gate{\mathrm{H}} & \gate{\mathrm{X}} & \qw & \qw & \ctrl{2} & \qw & \qw & \gate{\mathrm{X}} & \gate{\mathrm{H}} & \qw & \qw & \meter & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{6} :  } & \lstick{{q}_{6} :  } & \gate{\mathrm{I}} & \qw & \qw & \ctrl{7} & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \ctrl{14} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{3} & \ctrl{3} & \ctrl{3} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{3} & \ctrl{3} & \ctrl{3} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{14} & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \ctrl{7} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{7} :  } & \lstick{{q}_{7} :  } & \gate{\mathrm{H}} & \qw & \qw & \qw & \qw & \qw & \ctrl{9} & \qw & \qw & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{2} & \ctrl{2} & \ctrl{2} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{2} & \ctrl{2} & \ctrl{2} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \qw & \qw & \ctrl{9} & \qw & \qw & \qw & \qw & \qw & \gate{\mathrm{H}} & \gate{\mathrm{X}} & \qw & \qw & \ctrl{1} & \qw & \qw & \gate{\mathrm{X}} & \gate{\mathrm{H}} & \qw & \qw & \qw & \meter & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{8} :  } & \lstick{{q}_{8} :  } & \gate{\mathrm{H}} & \qw & \qw & \qw & \ctrl{6} & \qw & \qw & \qw & \ctrl{10} & \ctrl{11} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \ctrl{1} & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \ctrl{1} & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{11} & \ctrl{10} & \qw & \qw & \qw & \ctrl{6} & \qw & \qw & \qw & \gate{\mathrm{H}} & \gate{\mathrm{X}} & \qw & \gate{\mathrm{H}} & \targ & \gate{\mathrm{H}} & \qw & \gate{\mathrm{X}} & \gate{\mathrm{H}} & \qw & \qw & \qw & \qw & \meter & \qw & \qw & \qw\\
+	 	\nghost{{q}_{9} :  } & \lstick{{q}_{9} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \ctrl{1} & \targ & \qw & \ctrl{1} & \targ & \qw & \ctrl{1} & \ctrl{1} & \targ & \qw & \ctrl{1} & \ctrl{1} & \targ & \qw & \ctrl{1} & \ctrl{1} & \targ & \qw & \ctrl{1} & \ctrl{1} & \targ & \qw & \ctrl{1} & \ctrl{1} & \targ & \qw & \ctrl{1} & \ctrl{1} & \targ & \qw & \gate{\mathrm{X}} & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \gate{\mathrm{X}} & \qw & \targ & \ctrl{1} & \ctrl{1} & \qw & \targ & \ctrl{1} & \ctrl{1} & \qw & \targ & \ctrl{1} & \ctrl{1} & \qw & \targ & \ctrl{1} & \ctrl{1} & \qw & \targ & \ctrl{1} & \ctrl{1} & \qw & \targ & \ctrl{1} & \ctrl{1} & \qw & \targ & \ctrl{1} & \qw & \targ & \ctrl{1} & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{10} :  } & \lstick{{q}_{10} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \targ & \qw & \qw & \ctrl{1} & \targ & \qw & \qw & \ctrl{1} & \targ & \qw & \qw & \ctrl{1} & \targ & \qw & \qw & \ctrl{1} & \targ & \qw & \qw & \ctrl{1} & \targ & \qw & \qw & \ctrl{1} & \targ & \qw & \qw & \gate{\mathrm{X}} & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \gate{\mathrm{X}} & \qw & \qw & \targ & \ctrl{1} & \qw & \qw & \targ & \ctrl{1} & \qw & \qw & \targ & \ctrl{1} & \qw & \qw & \targ & \ctrl{1} & \qw & \qw & \targ & \ctrl{1} & \qw & \qw & \targ & \ctrl{1} & \qw & \qw & \targ & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{11} :  } & \lstick{{q}_{11} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{12} :  } & \lstick{{q}_{12} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \ctrl{2} & \ctrl{3} & \ctrl{4} & \ctrl{5} & \ctrl{6} & \ctrl{7} & \ctrl{8} & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{13} :  } & \lstick{{q}_{13} :  } & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{8} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{14} :  } & \lstick{{q}_{14} :  } & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{7} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{15} :  } & \lstick{{q}_{15} :  } & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{6} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{16} :  } & \lstick{{q}_{16} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{5} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{17} :  } & \lstick{{q}_{17} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{4} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{18} :  } & \lstick{{q}_{18} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{3} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{19} :  } & \lstick{{q}_{19} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{2} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{20} :  } & \lstick{{q}_{20} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \ctrl{1} & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{{q}_{21} :  } & \lstick{{q}_{21} :  } & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \gate{\mathrm{X}} & \gate{\mathrm{H}} & \qw & \targ & \targ & \targ & \targ & \targ & \targ & \targ & \targ & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw & \qw\\
+	 	\nghost{\mathrm{{c} :  }} & \lstick{\mathrm{{c} :  }} & \lstick{/_{_{4}}} \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \cw & \dstick{_{_{\hspace{0.0em}0}}} \cw \ar @{<=} [-18,0] & \dstick{_{_{\hspace{0.0em}1}}} \cw \ar @{<=} [-17,0] & \dstick{_{_{\hspace{0.0em}2}}} \cw \ar @{<=} [-15,0] & \dstick{_{_{\hspace{0.0em}3}}} \cw \ar @{<=} [-14,0] & \cw & \cw & \cw\\
+\\ }}
+\end{document}
\ No newline at end of file
diff --git a/challenges/QOSF challenge/QuantumVoyagers/app/grover/grover_circuit_complete_image/grover_circuit.pdf b/challenges/QOSF challenge/QuantumVoyagers/app/grover/grover_circuit_complete_image/grover_circuit.pdf
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diff --git a/challenges/QOSF challenge/QuantumVoyagers/app/grover/solution.ipynb b/challenges/QOSF challenge/QuantumVoyagers/app/grover/solution.ipynb
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@@ -0,0 +1,834 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Solving Tic Tac Toe with Quantum Computing\n",
+    "In this notebook, we will explore how to apply quantum algorithms to solve the game of Tic Tac Toe. We will use two popular quantum algorithms: the Grover algorithm and the Quantum Approximate Optimization Algorithm (QAOA)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1. Introduction"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 1.1 Overview of Tic Tac Toe\n",
+    "\n",
+    "Tic Tac Toe, also known as Noughts and Crosses, is a classic two-player game where players take turns marking spaces on a 3x3 grid. The grid is initially empty, and players alternate placing their symbols ('X' or 'O') in an attempt to form a horizontal, vertical, or diagonal line of three of their symbols. The game ends when one player achieves this goal, resulting in a win, or if the entire grid is filled without a winner, leading to a draw.\n",
+    "\n",
+    "#### Key Rules:\n",
+    "\n",
+    "1. **Players:** Two players, typically represented by 'X' and 'O'.\n",
+    "2. **Grid:** A 3x3 square grid.\n",
+    "3. **Objective:** Form a line of three of your symbols horizontally, vertically, or diagonally.\n",
+    "4. **Turns:** Players take turns to place their symbol in an empty grid space.\n",
+    "5. **Winning:** The game ends when a player forms a line of three symbols, declaring them the winner.\n",
+    "6. **Draw:** If the grid is fully occupied and no player has won, the game is a draw.\n",
+    "\n",
+    "Tic Tac Toe is a simple yet strategic game often used for educational purposes to teach basic game theory concepts. Now, let's explore how quantum algorithms can be applied to enhance the strategies involved in playing Tic Tac Toe.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div>\n",
+    "<p style = 'text-align:center;'>\n",
+    "<img src=\"../Images/tic-tac-toe-1777880_1280.jpg\" alt=\"JuveYell\" width=\"500px\">\n",
+    "</p>\n",
+    "</div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. Grover's Algorithm"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2.1 Explanation of Grover's Quantum Search Algorithm\n",
+    "\n",
+    "Grover's Quantum Search Algorithm, developed by Lov Grover in 1996, is a potent quantum algorithm designed to perform a quadratic speedup in searching an unsorted database compared to the best classical algorithms. This algorithm relies on the principles of amplitude amplification, enabling efficient solution discovery within a large solution space.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Key Concepts:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "1. **Amplitude Amplification:**\n",
+    "In the quest for a marked element in a quantum list, we start in a uniform superposition:\n",
+    "\n",
+    "   $$ \\ket{s} = \\frac{1}{\\sqrt{N}} \\sum_{x=0}^{N-1} \\ket{x} $$\n",
+    "\n",
+    "   When measured in the standard basis, the probability of finding the correct element is $ \\frac{1}{N} = \\frac{1}{2^n} $. Amplitude amplification improves this probability by extending the amplitude of the marked element and reducing others. The algorithm's geometric interpretation involves two reflections generating a rotation in a two-dimensional plane. Introducing an additional state $ \\ket{s'} $, perpendicular to $ \\ket{w} $, achieves this by eliminating $ \\ket{w} $ from $ \\ket{s} $ and adjusting the scale."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img width=\"800px\" 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+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<p ><a href=\"https://learn.qiskit.org/course/ch-algorithms/grovers-algorithm\" target=\"_blank\">Image obtained from the Qiskit Textbook</a></p>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "2. **Oracle:**\n",
+    "   In quantum algorithms like Grover's, an oracle designates specific states as solutions. In Tic Tac Toe, it flips the sign of the probability amplitude for correct states:\n",
+    "   $$U_\\omega\\ket{x}=\\begin{cases}\n",
+    "   \\ket{x},& \\text{si } x\\neq \\omega\\\\\n",
+    "   -\\ket{x},& \\text{si } x= \\omega\n",
+    "   \\end{cases}\n",
+    "   $$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img width=\"800px\" 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\"/>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<p ><a href=\"https://learn.qiskit.org/course/ch-algorithms/grovers-algorithm\" target=\"_blank\">Image obtained from the Qiskit Textbook</a></p>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "3. **Grover Diffusion Operator:**\n",
+    "   The Grover diffusion operator enhances the amplitudes of marked states and suppresses unmarked states. It involves a sequence of quantum gates:\n",
+    "   $$U_s=2\\ket{s}\\bra{s}-\\mathbb{1}$$\n",
+    "   This sequence concentrates probability amplitudes on marked states, contributing to the algorithm's efficiency."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img width=\"800px\" 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+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<p ><a href=\"https://learn.qiskit.org/course/ch-algorithms/grovers-algorithm\" target=\"_blank\">Image obtained from the Qiskit Textbook</a></p>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finally, Grover's algorithm looks like:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img width=\"700px\" 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+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<p ><a href=\"https://learn.qiskit.org/course/ch-algorithms/grovers-algorithm\" target=\"_blank\">Imagen obtenida del Qiskit Textbook</a></p>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "\n",
+    "#### Application in Tic Tac Toe:\n",
+    "\n",
+    "For Tic Tac Toe, Grover's algorithm can be applied to search for optimal moves on the game board. By defining the oracle to identify winning board configurations and implementing the Grover diffusion operator, we can efficiently determine the optimal moves that lead to victory.\n",
+    "\n",
+    "<div>\n",
+    "<p style = 'text-align:center;'>\n",
+    "<img src=\"../Images/image9.png\" alt=\"JuveYell\" width=\"800px\">\n",
+    "</p>\n",
+    "</div>\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The concept revolves around assigning a qubit to each box, such that when the qubit is in the state |1>, it represents 'X', and when in the state |0>, it represents 'O'. The empty spaces are filled with Hadamard gates, as these states are the ones sought by the Grover's algorithm.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For this case, our Oracle consists of two crucial components. First, there are the eight victory conditions detailed in the preceding figure. However, it is essential to filter only valid plays based on both logic and the rules established earlier. Therefore, the Oracle is composed of two parts:\n",
+    "\n",
+    "1. **Victory Conditions:**\n",
+    "   - The eight specific conditions determining a win in the game.\n",
+    "\n",
+    "2. **X's Counter:**\n",
+    "   - A mechanism to count the total number of 'X' on the board. Since in any game where 'O' starts, there must be a total of 5 'O' and 4 'X', our counter verifies the presence of exactly 4 'X'.\n",
+    "\n",
+    "Finally, it is imperative to mark the states that meet any of the eight winning conditions, always ensuring there are exactly 4 'X' throughout the game. For this reason, we implement eight controlled-NOT gates, one for each winning condition, targeting the oracle qubit. This approach ensures the validity of winning plays while adhering to the restriction of having 4 'X' in the game.\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div>\n",
+    "<p style = 'text-align:center;'>\n",
+    "<img src=\"../Images/parts_oracle_grover.jpg\" alt=\"JuveYell\" width=\"1200px\">\n",
+    "</p>\n",
+    "</div>\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the preceding image, we can identify the most crucial part of our circuit. Each number represents a component of the total circuit:\n",
+    "\n",
+    "1. **Tic Tac Toe Representation Circuit:**\n",
+    "   - This circuit represents the Tic Tac Toe game, where 'H' denotes empty spaces, NOT gates represent 'X's, and 'I's represent 'O's.\n",
+    "\n",
+    "2. **Oracle Sub-Circuit:**\n",
+    "   - This sub-circuit is part of the oracle and encompasses all possible winning scenarios (8 in total).\n",
+    "\n",
+    "3. **Counter:**\n",
+    "   - The counter activates a Multi-Controlled NOT gate only if the number of 'X's is equal to 4.\n",
+    "\n",
+    "4. **State | - >:**\n",
+    "   - This state, when the required conditions are met, changes sign, marking the desired state.\n",
+    "\n",
+    "5. **Toffoli Gates:**\n",
+    "   - Toffoli gates determine the sought-after states, activating when the necessary conditions are fulfilled.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The remainder of the circuit corresponds to the inverse of circuits 2 and 3 from the preceding figure, followed by the application of the diffuser. Finally, the qubits in the 'H' states are measured, as these are the ones sought based on the established conditions.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we will see the results of implementing Grover's algorithm for our specific problem."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qiskit.visualization import plot_histogram\n",
+    "\n",
+    "import sys\n",
+    "sys.path.append('../../')\n",
+    "from pkg.general_utils import display_board, complete_lists_with_dictionary, filter_values_above_average\n",
+    "from pkg.quantum_utils import grover_algorithm, circuit_execute"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Setting up the board the way it is asked to solve it"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "X | O | O\n",
+      "---------\n",
+      "X |   |  \n",
+      "---------\n",
+      "O |   |  \n",
+      "---------\n"
+     ]
+    }
+   ],
+   "source": [
+    "challenge = [['X', 'O', 'O'], ['X', ' ', ' '], ['O', ' ', ' ']]\n",
+    "display_board(challenge)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Building the complete circuit and graphing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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sXp10bXxlM2z3juTeL9Vr37Tjk1mL6/Oh2ZWyFjqU0scPcgBQBwB1AJqPBhmk/obw2oeSjseSXf34HbdjW/1r48pkwpHJCW+uv0HYMorPydz882T1D5Ntz772tnt662cVvfBMsupf6k2y179ldDcJdnYlP//XenP0tc6MqNXqZ1R0b046Hk2OnJ2c+MvJ0XMbEuqwqPXV5/+6H9fn9mvp7a43ETetSsa3J7OXJieckYwZxb9VtnXW58Dz/fggWN+eeq5sezZZ/W/JsfPrOdB+9PDHOVx270zW/DBZ/9Nkz87X3n77C/Wvzp/WGyUnnFFvmI7WRlmtVm8KrvlR0v3ca2+/e0e9mfz8muSp79c/MHHiWaP7AwPbX0iefiB57sl6TXg1tb5686xrY/3359FzkxPfkhz5uoaECgAAAHDYRvFbmTA0tq5Pln+7/sbgYOzYmqz8btK5Ill03uj7FP3uncmT9ySdywe3f9+e+tk2G59MTvm10fcGea1WP2PsyXsHf9m4rR3Jo7fU3yA/+dz6GXajSc/z9RzY1jm4/Xf1JD9/INm4Ijn1/GTqzKGNb7jt3VOPf+3D2e+Myf6q9dUbK5tWJfPOSY4/ffQ1yzevTlZ8p974HIzuTcmyu+oN5oXvTNomD218w623O1nxz8nmpwe3/57eenN548+She9Ips8b2viGW60vWfdI8vT9g7904kvNwuPfnMw7u7nOqAMAAACa0yh7Cw+GTq2WrHkwefimwTfHXm7b+vql1zauPPznapSu55If3jj45tjL7dlZf4P8p3eOnnvT7N2TPPGtenNoKO6p9OxPk3+7sd4sGC02rEge/NvBN8dermdL8tA36meTjBY7X0x+9He/iPkw7ynVtzd56gfJj/++3ngeDWq1enP4sVsH3xx7uedX12vK82sP/7kaZcu6et4Otjn2cr3dyWP/kPzse6PnHmV7epNHbqmfBTcUtXvdw/Wc6s+ZqAAAAABV0iCjX2bNmpVrr702s2bNqjqUIfP0/cmq+4b2Ofv2JE/ckTy7bGifdzi8uCH58c1D86b4y21cmTz+TyO/SbZ3T/L4P9QvJTaUeruSh2+u37tppFv/xC8amntfe9t+q9WbRD//1yF8zmGyY1u9Qd7z/NA+79aOem4deO+ukaZWq581tu7HQ/u8e3qTx26rX7Z1pHt+TT3W/lxSciCeeTRZdvfIb5Lt3llv6L6wbmift2dL8vD/Xb+fXzNpxrXQQJQ+fpADgDoAqAPQfFpqtZH+9k15enp6MmlS/WZO3d3daW9vH/JjrFw5/Kc5LViwYNiPMVhrH65/Wn7YtCRL3ztyL7O1fWvy0NeH9w38Gackp10wMi+3WKslP7k92fTU8B1j3ITkzA8mE6YO3zEOx3NPJT/5p+E9xim/nsx54/AeY7B270x+9L/ql0gdLlNnJqdfkrSOGb5jHI6nfjC8Z/u1jk1O/+2Re8nNFzfUmzjD2cyf86b6pWdHor69ySN/X7/M8HCZMDU544PJ+AnDd4zD0Yi1UDKy10OlrwdBDkDZrAUAawEYvYaqh+IMMvply5Yt+frXv54tW7ZUHcph69qUrPqXge1z5geTc/5j/Xu/1JLl30l2bR9weMOuVkuW3z2w5tiAx5/6vXiG4tKNw+HZJwbeHBvoa7B7R/3SjSPxIwi9PcmK/z2wfQYzB576/tCfnTVUnrxnYM2xwYx/W2ey+t8GHFpDbFk38ObYQF+Dvj31y67u3T3w+Ibb3j3JT+8aWHNsMHPgmUfqZ6mNRGt+NPDm2EBfgx3b6pebbBbNtBYajNLHD3IAUAcAdQCaT5ENss2bN+fqq6/OSSedlLa2tsyZMydXXnllenp6cvnll6elpSU33HBD1WGOKJ2dnfn85z+fzs4huFFRhfr2/qJp0Tew/ca3J22T69/7a9f25Gf3DOw4jfDMIwN/U3Qw40/qTYihvoTj4dr5YvLk9we+32BegxeeSdY/PvBjDadaLVn53YGfPTiY8fftTZYNIt+G26anB968HWwOrHlw5F1uc8+ueh0cqMG8BttfqF/OdqT5+QPJ9gH+f2awc2D5d4bmHodDqWvT4Jq3g3kNNq6sn7HaDJplLTRYpY8f5ACgDgDqADSf4hpkjz32WN7whjfkP//n/5wNGzbk1FNPze7du/OlL30pv/3bv50VK1YkSZYuXVptoAyLzmVJVwPfrN64cngvXzVQu3c29s3qPb0j783xVfcne3c17nhP/Uu9ITFSvPDM8F5a8kAvdo6sMwlrffXGbcOOV0uevLdxx+uPdQ/XG8UNO96P642ykWLHtvpldhultytZM4yXshyMp77f2Mb1k/ckfSOsUQ4AAABQVINs8+bNufDCC7Nhw4Z86lOfSmdnZx555JFs2LAh1157be6888489NBDaWlpyeLFi6sOlyFWqyXPPNr443Y81vhjHkrn8sZf7mzDynpjbiTYtb1+6cdG2rsr2TCCGkQdhefA82vqDZJG2tqRdG9q7DEPpW9vsv4njT9uxwg6k3L940kafOnTZ39Sf+1Hgp7nky1rG3vMnV3J5p839pgAAAAAr6WoBtkVV1yRjo6OfPKTn8z111+fyZMn73vs6quvzpIlS7Jnz57MnTs3U6ZMqTBShsO2Z6t5k3rjz5JdPY0/7oFqtWoaFX17kmd/2vjjHsyzTyS1Ct6k7nhsZNyLbGdXsmlV44/74ob610hQVbNupDSINj1dzWVPn/3pyLgXWd+eZP0TjT/uru0j5zKDVc3FkdQoBwAAAEgKapCtWLEiN998c6ZPn54vfOELB93m9NNPT5IsWbJk389uueWWvO9978sJJ5yQiRMnZsGCBfnDP/zDdHfv/w7jS423M888M0cccURaWlqGbzAVaG9vz9lnn5329gHefGUEqerNyVrfyPjkfM/zA7/nzlBp5CX9Xk1Vc6B7c7JjazXHfrnNT1fXqBsJzYG9u5PnV1dz7JEw/qS6XNyzM3mho5pjv9zW9QO//95Qee7Jao57oKrm4pY1I+tys4PRDGuhw1H6+EEOAOoAoA5A8xlbdQCNctNNN6Wvry+XXnppJk2adNBtJkyYkGT/Btn111+f448/Pn/2Z3+W2bNn57HHHsvnPve5/OAHP8i//Mu/pLW13mNctWpVbr311pxxxhkZP358HnjggeEfVAPNnTs3X/3qV6sO47A08t5jB3pxY/K6N1R3/KTa8Xc9V28UtlTYku/bW+1l7l7cmEw8qrrjvxRDVaqcf/ti2FRdg3BXT/3MrSMO/uunYaqeA9NPrO74SfXjr9qu7fV7olWla2Ny1Jzqjn+4mmEtdDhKHz/IAUAdANQBaD7FNMjuueeeJMm55557yG06Ouofb395g+xb3/pWjjnmmH1/f9vb3pZjjjkml156ae6///689a1vTZK89a1vTWdnZ5Lkj//4j5uuQbZ3797s2LEjEyZMyJgxY6oOZ8BqNW+MVjn+vbuT7S8k7UdXF0PP89XeA6hrY3LcguqO/1IMVXlxYz0Pqzy5tqviyzy+uDE5psIG2Z5d1Z1FmlRbg15SZQ7s2Fa/H+O4tupiqPrf4MVR3iAb7Wuhw1X6+EEOAOoAoA5A8ynmEotr19bvSH/CCScc9PE9e/bsa2q9vEH28ubYS9785jcnSdavX7/vZy+dSdasVq5cmTPOOCMrV66sOpRB2b0j2VvhpZ22b63u2C+p+hJ/pR9/RMyBbdUdu+ocTJLtFY4/qX4O7ix8/En1eVhlDibV/xtUffzDNdrXQoer9PGDHADUAUAdgOZTzBlkPT09SZIdOw5+85Gbb745mzdvzuTJk3Piia9+Dah77703SbJw4cKhDfIg5s+fPyzNt8suu2xA2790dtxdd92VRx99tF/73HjjjQOMavgcNWlm/tvvPXTIx8/8YDL+VS4ffET7v38/5z8eertdPcmP/tcrf/7i1q7Mnj388+XV/L9+8xs57YS3HvSxoRp/cujX4Pcu/495eNWd/Yx26P3SKRflD87/i4M+9lrjTw5/Dnz3f38v7/7ER/oZ7fD4H59clXFjD376ynDnQJIsfsPSvLh9cz+jHXofOvdP8+tLDv5v0Igc+NM/+ULufPjgc7ARTpyxJJ/9nYPnYCNyYNWTP8/7Zx+8BjXK5z/43cyefvBTORsxB95zwXuzqvPhfkY79H7jjR/N77ztswd9rBFz4Ov/66b8zWWf7me0w68Ra6FkZK2HDjSQ16AZxw9yAMpmLQCU9v4oNJO+vr59fz7nnHMG9Lv55YppkB133HF54YUX8sgjj+Sss87a77HOzs58+tP1N2wWL16clle5Btj69evzR3/0RznvvPOydOnS4Qx5X2zDYfv27QPafufOnfu+93ffl59hV7Xtk/e86uPj25O2ya/9PC2t/dvuQLv37Kr89di+o+eQjw33+JPkuc0bKn0NNh/93CEf6+/4k8G/Bt09XZXPgT1792TcIap+I+ZAR8e6dO14YXA7D4EXuw59+k4jxr/lhc2VzoG22ivPiH5JI3JgZ++OynOgd9fOQz7WiDmwYeOzlb4GW+Y+f8jHGjEHXuzaWvkceLlGrIWSkbUeOtBAxtGM4wc5AGWzFgBKe38UmtXGjYO/p0QxDbK3v/3tWbFiRa699tq84x3vyMknn5wkeeihh/KhD30omzfXz2p4taZXd3d3LrrooowfPz5f+9rXGhF2Zs6cOSxnkE2cOHFA27e1te373t99Z82aNeC4hsu4MW3pq/WlteXgr+WuQ/eOktQ/Ld/SmtT6kt5X2fZQz7Njd1flr8feHPqN4aEa/6s9V1v72EpfgyMmHvra0K81/uTw50BfS2/lc2B777ZMOOLgN8Ea7hzYs3d3jpo+NVP6BlZ7hlLL2EPfhK4ROTD2iGrrYvvk8Yd8rBE50Lu3u/Ic6N176MAbMQfapxxR6WtwiBNIkzRmDmTMnsrnwMs1Yi2UjKz10IEGMo5mHD/IASibtQBQ2vuj0Ez6+vr2nVw0Y8aMQT9PS61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+      "text/plain": [
+       "<Figure size 2228.78x9983.17 with 1 Axes>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qc = grover_algorithm(challenge, rep=1)\n",
+    "\n",
+    "qc.draw('mpl')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'\\\\documentclass[border=2px]{standalone}\\n\\n\\\\usepackage[braket, qm]{qcircuit}\\n\\\\usepackage{graphicx}\\n\\n\\\\begin{document}\\n\\\\scalebox{1.0}{\\n\\\\Qcircuit @C=1.0em @R=0.2em @!R { \\\\\\\\\\n\\t \\t\\\\nghost{{q}_{0} :  } & \\\\lstick{{q}_{0} :  } & \\\\gate{\\\\mathrm{X}} \\\\barrier[0em]{21} & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\ctrl{3} & \\\\ctrl{4} & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\ctrl{9} \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\ctrl{9} \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\ctrl{4} & \\\\ctrl{3} \\\\barrier[0em]{21} & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{8} & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{8} & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw \\\\barrier[0em]{21} & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{1} :  } & \\\\lstick{{q}_{1} :  } & \\\\gate{\\\\mathrm{I}} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{8} & \\\\ctrl{8} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{8} & \\\\ctrl{8} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{2} :  } & \\\\lstick{{q}_{2} :  } & \\\\gate{\\\\mathrm{I}} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{15} & \\\\ctrl{3} & \\\\qw & \\\\ctrl{2} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{7} & \\\\ctrl{7} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{7} & \\\\ctrl{7} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{2} & \\\\qw & \\\\ctrl{3} & \\\\ctrl{15} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{3} :  } & \\\\lstick{{q}_{3} :  } & \\\\gate{\\\\mathrm{X}} & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{6} & \\\\ctrl{6} & \\\\ctrl{6} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{6} & \\\\ctrl{6} & \\\\ctrl{6} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{4} :  } & \\\\lstick{{q}_{4} :  } & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{4} & \\\\ctrl{1} & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{2} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{5} & \\\\ctrl{5} & \\\\ctrl{5} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{5} & \\\\ctrl{5} & \\\\ctrl{5} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{2} & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\ctrl{1} & \\\\ctrl{4} & \\\\qw & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{H}} & \\\\gate{\\\\mathrm{X}} & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{X}} & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\meter & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{5} :  } & \\\\lstick{{q}_{5} :  } & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{10} & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{4} & \\\\ctrl{4} & \\\\ctrl{4} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{4} & \\\\ctrl{4} & \\\\ctrl{4} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\ctrl{10} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{H}} & \\\\gate{\\\\mathrm{X}} & \\\\qw & \\\\qw & \\\\ctrl{2} & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{X}} & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\qw & \\\\meter & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{6} :  } & \\\\lstick{{q}_{6} :  } & \\\\gate{\\\\mathrm{I}} & \\\\qw & \\\\qw & \\\\ctrl{7} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\ctrl{14} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\ctrl{3} & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\ctrl{3} & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{14} & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{7} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{7} :  } & \\\\lstick{{q}_{7} :  } & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{9} & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{2} & \\\\ctrl{2} & \\\\ctrl{2} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{2} & \\\\ctrl{2} & \\\\ctrl{2} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\ctrl{9} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{H}} & \\\\gate{\\\\mathrm{X}} & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{X}} & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\qw & \\\\qw & \\\\meter & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{8} :  } & \\\\lstick{{q}_{8} :  } & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{6} & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{10} & \\\\ctrl{11} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{11} & \\\\ctrl{10} & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{6} & \\\\qw & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{H}} & \\\\gate{\\\\mathrm{X}} & \\\\qw & \\\\gate{\\\\mathrm{H}} & \\\\targ & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\gate{\\\\mathrm{X}} & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\meter & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{9} :  } & \\\\lstick{{q}_{9} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\ctrl{1} & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\gate{\\\\mathrm{X}} & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\gate{\\\\mathrm{X}} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{10} :  } & \\\\lstick{{q}_{10} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\targ & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{X}} & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\gate{\\\\mathrm{X}} & \\\\qw & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\targ & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{11} :  } & \\\\lstick{{q}_{11} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{12} :  } & \\\\lstick{{q}_{12} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\ctrl{2} & \\\\ctrl{3} & \\\\ctrl{4} & \\\\ctrl{5} & \\\\ctrl{6} & \\\\ctrl{7} & \\\\ctrl{8} & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{13} :  } & \\\\lstick{{q}_{13} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{8} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{14} :  } & \\\\lstick{{q}_{14} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{7} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{15} :  } & \\\\lstick{{q}_{15} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{6} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{16} :  } & \\\\lstick{{q}_{16} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{5} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{17} :  } & \\\\lstick{{q}_{17} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{4} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{18} :  } & \\\\lstick{{q}_{18} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{3} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{19} :  } & \\\\lstick{{q}_{19} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{2} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{20} :  } & \\\\lstick{{q}_{20} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\ctrl{1} & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{{q}_{21} :  } & \\\\lstick{{q}_{21} :  } & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\gate{\\\\mathrm{X}} & \\\\gate{\\\\mathrm{H}} & \\\\qw & \\\\targ & \\\\targ & \\\\targ & \\\\targ & \\\\targ & \\\\targ & \\\\targ & \\\\targ & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw & \\\\qw\\\\\\\\\\n\\t \\t\\\\nghost{\\\\mathrm{{c} :  }} & \\\\lstick{\\\\mathrm{{c} :  }} & \\\\lstick{/_{_{4}}} \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\cw & \\\\dstick{_{_{\\\\hspace{0.0em}0}}} \\\\cw \\\\ar @{<=} [-18,0] & \\\\dstick{_{_{\\\\hspace{0.0em}1}}} \\\\cw \\\\ar @{<=} [-17,0] & \\\\dstick{_{_{\\\\hspace{0.0em}2}}} \\\\cw \\\\ar @{<=} [-15,0] & \\\\dstick{_{_{\\\\hspace{0.0em}3}}} \\\\cw \\\\ar @{<=} [-14,0] & \\\\cw & \\\\cw & \\\\cw\\\\\\\\\\n\\\\\\\\ }}\\n\\\\end{document}'"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qc.draw('latex_source', filename='./grover_circuit_complete_image/file.tex')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Running the complete circuit and graphing the results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'1011': 288, '0000': 293, '1000': 296, '0011': 317, '1101': 293, '1100': 7852, '1110': 315, '0111': 323, '1001': 7791, '1010': 319, '0010': 286, '1111': 329, '0101': 323, '0001': 298, '0110': 348, '0100': 329}\n"
+     ]
+    }
+   ],
+   "source": [
+    "counts_without_qiskit_convention = circuit_execute(qc, shots=20000)\n",
+    "print(counts_without_qiskit_convention)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot_histogram(counts_without_qiskit_convention, color='midnightblue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'1100': 7852, '1001': 7791}\n"
+     ]
+    }
+   ],
+   "source": [
+    "possible_results = filter_values_above_average(counts_without_qiskit_convention)\n",
+    "\n",
+    "print(possible_results)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "List 1: [['X', 'O', 'O'], ['X', 'X', 'X'], ['O', 'O', 'O']]\n",
+      "List 2: [['X', 'O', 'O'], ['X', 'X', 'O'], ['O', 'O', 'X']]\n"
+     ]
+    }
+   ],
+   "source": [
+    "completed_lists = complete_lists_with_dictionary(challenge, possible_results)\n",
+    "\n",
+    "for i, lst in enumerate(completed_lists, start=1):\n",
+    "    print(f'List {i}: {lst}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Printing all possible valid results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Challenge:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X |   |  \n",
+      "---------\n",
+      "O |   |  \n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 1:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | X | X\n",
+      "---------\n",
+      "O | O | O\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 2:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | X | O\n",
+      "---------\n",
+      "O | O | X\n",
+      "---------\n",
+      "\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Challenge:')\n",
+    "display_board(challenge)\n",
+    "print('\\n')\n",
+    "\n",
+    "for index, lst in enumerate(completed_lists):\n",
+    "    print('Solution {}:'.format(index + 1))\n",
+    "    display_board(lst)\n",
+    "    print('\\n')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Post quantum analysis"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It is evident for us that there are only two ways to win if we play as 'X'. The first is with the move |1100>, and the second is with the move |1001>, as shown in the results obtained by the implemented Grover's algorithm. Furthermore, we observe that for both winning plays, the 'X's played in the first available position. This implies that making this move increases the probability of winning, which makes sense since having this move with the 'X's provides two winning options in the next turn. However, if we analyze the 'O' move, meaning if 'O' plays in the third available position, then a guaranteed win is ensured, as the subsequent moves of 'X' become irrelevant.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div>\n",
+    "<p style = 'text-align:center;'>\n",
+    "<img src=\"../Images/best_play.png\" alt=\"JuveYell\" width=\"100px\">\n",
+    "</p>\n",
+    "</div>\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Bonus"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "X | O | O\n",
+      "---------\n",
+      "X |   |  \n",
+      "---------\n",
+      "  |   |  \n",
+      "---------\n"
+     ]
+    }
+   ],
+   "source": [
+    "challenge_bonus = [['X', 'O', 'O'], ['X', ' ', ' '], [' ', ' ', ' ']]\n",
+    "display_board(challenge_bonus)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2228.78x9983.17 with 1 Axes>"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qc_bonus = grover_algorithm(challenge_bonus, rep=1)\n",
+    "\n",
+    "qc_bonus.draw('mpl')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'10010': 40, '00011': 47, '01111': 34, '10101': 31, '01001': 41, '00111': 28, '11111': 30, '11011': 37, '00001': 39, '01011': 41, '10100': 3164, '10001': 3212, '11010': 38, '11101': 40, '00101': 3080, '11000': 3170, '11100': 36, '10110': 38, '10000': 36, '01100': 3189, '00110': 3183, '00010': 34, '10111': 31, '01101': 42, '11110': 39, '01010': 48, '01000': 45, '01110': 51, '00100': 43, '00000': 36, '10011': 40, '11001': 37}\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "counts_without_qiskit_convention = circuit_execute(qc_bonus, shots=20000)\n",
+    "print(counts_without_qiskit_convention)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot_histogram(counts_without_qiskit_convention, color='midnightblue')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'10100': 3164, '10001': 3212, '00101': 3080, '11000': 3170, '01100': 3189, '00110': 3183}\n"
+     ]
+    }
+   ],
+   "source": [
+    "possible_results = filter_values_above_average(counts_without_qiskit_convention)\n",
+    "\n",
+    "print(possible_results)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "List 1: [['X', 'O', 'O'], ['X', 'X', 'O'], ['O', 'X', 'O']]\n",
+      "List 2: [['X', 'O', 'O'], ['X', 'X', 'O'], ['O', 'O', 'O']]\n",
+      "List 3: [['X', 'O', 'O'], ['X', 'O', 'O'], ['O', 'X', 'O']]\n",
+      "List 4: [['X', 'O', 'O'], ['X', 'X', 'X'], ['O', 'O', 'O']]\n",
+      "List 5: [['X', 'O', 'O'], ['X', 'O', 'X'], ['O', 'X', 'O']]\n",
+      "List 6: [['X', 'O', 'O'], ['X', 'O', 'O'], ['O', 'X', 'X']]\n"
+     ]
+    }
+   ],
+   "source": [
+    "completed_lists = complete_lists_with_dictionary(challenge, possible_results)\n",
+    "\n",
+    "for i, lst in enumerate(completed_lists, start=1):\n",
+    "    print(f'List {i}: {lst}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Challenge:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X |   |  \n",
+      "---------\n",
+      "O |   |  \n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 1:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | X | O\n",
+      "---------\n",
+      "O | X | O\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 2:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | X | O\n",
+      "---------\n",
+      "O | O | O\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 3:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | O | O\n",
+      "---------\n",
+      "O | X | O\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 4:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | X | X\n",
+      "---------\n",
+      "O | O | O\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 5:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | O | X\n",
+      "---------\n",
+      "O | X | O\n",
+      "---------\n",
+      "\n",
+      "\n",
+      "Solution 6:\n",
+      "X | O | O\n",
+      "---------\n",
+      "X | O | O\n",
+      "---------\n",
+      "O | X | X\n",
+      "---------\n",
+      "\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Challenge:')\n",
+    "display_board(challenge)\n",
+    "print('\\n')\n",
+    "\n",
+    "for index, lst in enumerate(completed_lists):\n",
+    "    print('Solution {}:'.format(index + 1))\n",
+    "    display_board(lst)\n",
+    "    print('\\n')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Post quantum analysis"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Para este caso tambien podemos hacer el analisis post cuantico. Para saber que jugadas podrían darnos una mayor probabilidad de ganar:\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div>\n",
+    "<p style = 'text-align:center;'>\n",
+    "<img src=\"../Images/best_play_bonus.png\" alt=\"JuveYell\" width=\"200px\">\n",
+    "</p>\n",
+    "</div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can observe that the optimal move for 'X' is marking the third playable box (in red), which logically results in an automatic win. On the other hand, if 'O' plays in the fourth possible box (in blue), it also increases our chances of winning, as the displayed results are for 'X' winning scenarios. Finally, we can notice that the second-best move for 'X' after 'O' has played is to choose the first available box (in green).\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The file `general_solution.ipynb` includes a function that generates a random initial game configuration. Subsequently, the execution of the algorithm yields results where 'X' emerges victorious. In such instances, post-quantum analysis could be performed, although results may vary across each execution. Two specific cases are highlighted for a comprehensive understanding.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 3. Conclusion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "   - The flexibility of the oracle demonstrates Grover's versatility in addressing specific game conditions."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Grover provides an  adaptable quantum solution for Tic Tac Toe, though the outcomes are statistically variable due to the quantum nature of the algorithm.*"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "WOMANIUM",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/challenges/QOSF challenge/QuantumVoyagers/app/qaoa/qaoa.ipynb b/challenges/QOSF challenge/QuantumVoyagers/app/qaoa/qaoa.ipynb
new file mode 100644
index 0000000..4f72b06
--- /dev/null
+++ b/challenges/QOSF challenge/QuantumVoyagers/app/qaoa/qaoa.ipynb	
@@ -0,0 +1,955 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "clyv3IRsJNaG",
+      "metadata": {
+        "id": "clyv3IRsJNaG"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install h5py\n",
+        "!pip install typing-extensions\n",
+        "!pip install wheel"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "65DDjaGiFd_c",
+      "metadata": {
+        "id": "65DDjaGiFd_c"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install docplex\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "DM3iU9TvGGCo",
+      "metadata": {
+        "id": "DM3iU9TvGGCo"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install --upgrade azure-quantum\\[qiskit\\]\n",
+        "!pip install qiskit\n",
+        "!pip install cplex"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "7QQ56rCZLsex",
+      "metadata": {
+        "id": "7QQ56rCZLsex"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install openqaoa-qiskit"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 20,
+      "id": "17552bd0",
+      "metadata": {
+        "id": "17552bd0"
+      },
+      "outputs": [],
+      "source": [
+        "%matplotlib notebook\n",
+        "\n",
+        "# Import external libraries to present an manipulate the data\n",
+        "import numpy as np\n",
+        "import matplotlib.pyplot as plt\n",
+        "import pandas as pd\n",
+        "\n",
+        "# Import docplex model to generate the problem to optimize\n",
+        "from docplex.mp.model import Model\n",
+        "\n",
+        "# Import the libraries needed to employ the QAOA quantum algorithm using OpenQAOA\n",
+        "from openqaoa import QAOA\n",
+        "\n",
+        "# method to covnert a docplex model to a qubo problem\n",
+        "from openqaoa.problems.converters import FromDocplex2IsingModel\n",
+        "from openqaoa.backends import create_device\n",
+        "\n",
+        "# method to find the corrects states for the QAOA boject\n",
+        "from openqaoa.utilities import ground_state_hamiltonian"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "c3672d85",
+      "metadata": {
+        "id": "c3672d85"
+      },
+      "source": [
+        "## 1) Tic Tac Toe Game\n",
+        "This problem can be solved by treating each cell as a variable, and our objective function aims to maximize the number of winning moves. For instance, if we want to address the following problem:\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "<div>\n",
+        "<p style = 'text-align:center;'>\n",
+        "<img src=\"../Images/image10.png\" alt=\"JuveYell\" width=\"300px\">\n",
+        "</p>\n",
+        "</div>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n",
+        "So, for x_0, we observe it has 2 winning possibilities. On the other hand, x_1 has only one, x_2 has 0 winning possibilities, and x_3 has only 1 winning option. Therefore, our objective function is formulated as follows:\n",
+        "$$f_1(\\textbf{x}) = 2*x_0 + 1*x_1 + 0*x_2 + 1*x_3$$\n",
+        "\n",
+        "This objective function is subject to an equality constraint, as when the game starts with 0's, there should be a total of 4 X's played. This forms our constraint, but in this case, given an initial configuration, we subtract 2 X's:\n",
+        "\n",
+        "$$x_0 + x_1 + x_2 + x_3 = 2$$\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 95,
+      "id": "inv3grH1qNBI",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 481
+        },
+        "id": "inv3grH1qNBI",
+        "outputId": "4bd182b2-18a5-4ec6-8f97-87c20bb26cc3"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "// This file has been generated by DOcplex\n",
+            "// model name is: Basic Problem using minimize\n",
+            "// var contrainer section\n",
+            "dvar bool x[4];\n",
+            "\n",
+            "maximize\n",
+            " 2 x_0 + x_1 + x_3;\n",
+            " \n",
+            "subject to {\n",
+            " x_0 + x_1 + x_2 + x_3 == 2;\n",
+            "\n",
+            "}\n",
+            "None\n",
+            "Warning: Model name contains whitespaces: |Basic Problem using minimize|\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "\n",
+              "  <div id=\"df-86eca371-f92f-495c-8292-2d2b67d8290c\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>solutions_bitstrings</th>\n",
+              "      <th>bitstrings_energies</th>\n",
+              "      <th>probabilities</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>1001</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>1100</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>0101</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>1010</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>0110</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>0011</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-86eca371-f92f-495c-8292-2d2b67d8290c')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-86eca371-f92f-495c-8292-2d2b67d8290c button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-86eca371-f92f-495c-8292-2d2b67d8290c');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-9e57aac3-d968-4ec9-b6ab-4d2a64476bc5\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-9e57aac3-d968-4ec9-b6ab-4d2a64476bc5')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-9e57aac3-d968-4ec9-b6ab-4d2a64476bc5 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "text/plain": [
+              "  solutions_bitstrings  bitstrings_energies  probabilities\n",
+              "0                 1001                 -3.0           0.10\n",
+              "1                 1100                 -3.0           0.10\n",
+              "2                 0101                 -2.0           0.05\n",
+              "3                 1010                 -2.0           0.10\n",
+              "4                 0110                 -1.0           0.10\n",
+              "5                 0011                 -1.0           0.10"
+            ]
+          },
+          "execution_count": 95,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "#Specific the Model and put a name\n",
+        "mdl = Model(\"Basic Problem using maximize\")\n",
+        "# Number of variables\n",
+        "n_vars = 4\n",
+        "\n",
+        "# Using binary variables for this model\n",
+        "x = mdl.binary_var_list(n_vars, name=\"x\")\n",
+        "obj_func = 2*x[0] + x[1] + 0*x[2] + 1*x[3]\n",
+        "#obj_func = 2*x[0] + x[1] + 1*x[2] + 0*x[3] + 1*x[4]\n",
+        "mdl.maximize(obj_func)\n",
+        "mdl.add_constraint(x[0] + x[1] + x[2] + x[3] == 2)\n",
+        "\n",
+        "print(mdl.prettyprint())\n",
+        "# Converting the Docplex model into its qubo representation\n",
+        "qubo = FromDocplex2IsingModel(mdl)\n",
+        "\n",
+        "# Ising encoding of the QUBO problem\n",
+        "ising_encoding = qubo.ising_model\n",
+        "\n",
+        "# Print in a df the ising encoding (we need to remove keys: 'problem_instance' and 'metadata'))\n",
+        "ising_encoding_dict = ising_encoding.asdict(exclude_keys=['problem_instance', 'metadata'])\n",
+        "#pd.DataFrame(ising_encoding_dict)\n",
+        "#Specific local device usign qiskit backend\n",
+        "device = create_device(\"local\", 'qiskit.qasm_simulator')\n",
+        "#Is possible check the devices using qaoa.local_simulators, qaoa.cloud_provider\n",
+        "qaoa = QAOA(device)\n",
+        "\n",
+        "#Indicate the properties to the QAOA quantum algorithm,shots,seed\n",
+        "qaoa.set_backend_properties(n_shots=20, seed_simulator=1)\n",
+        "#check the p value and the variational init params\n",
+        "qaoa.set_circuit_properties(p=2, init_type=\"custom\", variational_params_dict={\"betas\":2*[0.01*np.pi],\"gammas\":2*[0.01*np.pi]})\n",
+        "\n",
+        "#Indicate the ising e ncoding model from docplex\n",
+        "qaoa.compile(ising_encoding)\n",
+        "\n",
+        "#Optimize the quantum algorithm\n",
+        "qaoa.optimize()\n",
+        "#Print in a df the best 10 solutions\n",
+        "results = pd.DataFrame(qaoa.result.lowest_cost_bitstrings(10))\n",
+        "results = results[results[\"bitstrings_energies\"]<0]\n",
+        "results"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n",
+        "From the results, we observe that for the lowest bitstrings_energy (-3), we have the states 1001 and 1100. These happen to be the only 2 options where X's can win in this case.\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Additionally, we can also solve the bonus problem."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "<div>\n",
+        "<p style = 'text-align:center;'>\n",
+        "<img src=\"../Images/image11.png\" alt=\"JuveYell\" width=\"300px\">\n",
+        "</p>\n",
+        "</div>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "So, for x_0, we observe it has 2 winning possibilities. On the other hand, x_1 has only one, x_2 has only one too, x_3 has 0 winning possibilities, and x_4 has only 1 winning option. Therefore, our objective function is formulated as follows:\n",
+        "$$f_1(\\textbf{x}) = 2*x_0 + 1*x_1 + 1*x_2 + 0*x_3 + 1*x_4$$\n",
+        "\n",
+        "This objective function is subject to an equality constraint, as when the game starts with 0's, there should be a total of 4 X's played. This forms our constraint, but in this case, given an initial configuration, we subtract 2 X's:\n",
+        "\n",
+        "$$x_0 + x_1 + x_2 + x_3 + x_4= 2$$"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 94,
+      "id": "ed3023be",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 575
+        },
+        "id": "ed3023be",
+        "outputId": "699a3f4d-02d4-458d-8d34-a396229fb0ab"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "// This file has been generated by DOcplex\n",
+            "// model name is: Basic Problem using minimize\n",
+            "// var contrainer section\n",
+            "dvar bool x[5];\n",
+            "\n",
+            "maximize\n",
+            " 2 x_0 + x_1 + x_2 + x_4;\n",
+            " \n",
+            "subject to {\n",
+            " x_0 + x_1 + x_2 + x_3 + x_4 == 2;\n",
+            "\n",
+            "}\n",
+            "None\n",
+            "Warning: Model name contains whitespaces: |Basic Problem using minimize|\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "\n",
+              "  <div id=\"df-e2b1115d-644b-4a24-b6a5-2e0c601edba6\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>solutions_bitstrings</th>\n",
+              "      <th>bitstrings_energies</th>\n",
+              "      <th>probabilities</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>10001</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>10100</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>11000</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.20</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>10010</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>00101</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>01100</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.15</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>00011</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7</th>\n",
+              "      <td>00110</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8</th>\n",
+              "      <td>01010</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.15</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e2b1115d-644b-4a24-b6a5-2e0c601edba6')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
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+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-e2b1115d-644b-4a24-b6a5-2e0c601edba6 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-e2b1115d-644b-4a24-b6a5-2e0c601edba6');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-9531382f-27d2-4c5d-af22-985a036e4dd6\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-9531382f-27d2-4c5d-af22-985a036e4dd6')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-9531382f-27d2-4c5d-af22-985a036e4dd6 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "text/plain": [
+              "  solutions_bitstrings  bitstrings_energies  probabilities\n",
+              "0                10001                 -3.0           0.05\n",
+              "1                10100                 -3.0           0.05\n",
+              "2                11000                 -3.0           0.20\n",
+              "3                10010                 -2.0           0.10\n",
+              "4                00101                 -2.0           0.10\n",
+              "5                01100                 -2.0           0.15\n",
+              "6                00011                 -1.0           0.05\n",
+              "7                00110                 -1.0           0.10\n",
+              "8                01010                 -1.0           0.15"
+            ]
+          },
+          "execution_count": 94,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "#Specific the Model and put a name\n",
+        "mdl = Model(\"Basic Problem using minimize\")\n",
+        "# Number of variables\n",
+        "n_vars = 5\n",
+        "\n",
+        "# Using binary variables for this model\n",
+        "x = mdl.binary_var_list(n_vars, name=\"x\")\n",
+        "obj_func = 2*x[0] + x[1] + 1*x[2] + 0*x[3] + 1*x[4]\n",
+        "\n",
+        "mdl.maximize(obj_func)\n",
+        "mdl.add_constraint(x[0] + x[1] + x[2] + x[3] + x[4] == 2)\n",
+        "print(mdl.prettyprint())\n",
+        "# Converting the Docplex model into its qubo representation\n",
+        "qubo = FromDocplex2IsingModel(mdl)\n",
+        "\n",
+        "# Ising encoding of the QUBO problem\n",
+        "ising_encoding = qubo.ising_model\n",
+        "\n",
+        "# Print in a df the ising encoding (we need to remove keys: 'problem_instance' and 'metadata'))\n",
+        "ising_encoding_dict = ising_encoding.asdict(exclude_keys=['problem_instance', 'metadata'])\n",
+        "\n",
+        "#Specific local device usign qiskit backend\n",
+        "device = create_device(\"local\", 'qiskit.qasm_simulator')\n",
+        "#Is possible check the devices using qaoa.local_simulators, qaoa.cloud_provider\n",
+        "qaoa = QAOA(device)\n",
+        "\n",
+        "#Indicate the properties to the QAOA quantum algorithm,shots,seed\n",
+        "qaoa.set_backend_properties(n_shots=20, seed_simulator=1)\n",
+        "#check the p value and the variational init params\n",
+        "qaoa.set_circuit_properties(p=2, init_type=\"custom\", variational_params_dict={\"betas\":2*[0.01*np.pi],\"gammas\":2*[0.01*np.pi]})\n",
+        "\n",
+        "#Indicate the ising e ncoding model from docplex\n",
+        "qaoa.compile(ising_encoding)\n",
+        "\n",
+        "#Optimize the quantum algorithm\n",
+        "qaoa.optimize()\n",
+        "#Print in a df the best 10 solutions\n",
+        "results = pd.DataFrame(qaoa.result.lowest_cost_bitstrings(10))\n",
+        "results = results[results[\"bitstrings_energies\"]<0]\n",
+        "results"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.10.6"
+    },
+    "vscode": {
+      "interpreter": {
+        "hash": "d2582286b70c3b030a2fde61b871db03dec7fee33191883f4394b540a2eb90c7"
+      }
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 5
+}
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new file mode 100644
index 0000000..af23e76
--- /dev/null
+++ b/challenges/QOSF challenge/QuantumVoyagers/pkg/general_utils.py	
@@ -0,0 +1,162 @@
+import random
+
+
+def initialize_board():
+    """
+    Initializes a Tic Tac Toe board with empty spaces.
+
+    Returns:
+    - board (list): A 3x3 grid representing the Tic Tac Toe board.
+    """
+    board = [[' ' for _ in range(3)] for _ in range(3)]
+    return board
+
+
+def make_move(board, player, row, column):
+    """
+    Makes a move on the Tic Tac Toe board for the specified player.
+
+    Parameters:
+    - board (list): The Tic Tac Toe board.
+    - player (str): The player making the move ('O' or 'X').
+    - row (int): The row where the move is made.
+    - column (int): The column where the move is made.
+
+    Returns:
+    - success (bool): True if the move is successful, False if the chosen position is already occupied.
+    """
+    if board[row][column] == ' ':
+        board[row][column] = player
+        return True
+    else:
+        return False
+
+
+def check_winner(board):
+    """
+    Checks if there is a winner on the Tic Tac Toe board.
+
+    Parameters:
+    - board (list): The Tic Tac Toe board.
+
+    Returns:
+    - winner (bool): True if there is a winner, False otherwise.
+    """
+    # Check rows and columns
+    for i in range(3):
+        if board[i][0] == board[i][1] == board[i][2] != ' ' or board[0][i] == board[1][i] == board[2][i] != ' ':
+            return True
+
+    # Check diagonals
+    if board[0][0] == board[1][1] == board[2][2] != ' ' or board[0][2] == board[1][1] == board[2][0] != ' ':
+        return True
+
+    return False
+
+
+def generate_random_board(num_moves):
+    """
+    Generates a random Tic Tac Toe board after a specified number of moves.
+
+    Parameters:
+    - num_moves (int): The number of moves made on the board.
+
+    Returns:
+    - board (list): A 3x3 grid representing the generated Tic Tac Toe board.
+    """
+    players = ['O', 'X']
+
+    while True:
+        board = initialize_board()
+        moves_made = 0
+
+        while moves_made < num_moves:
+            current_player = players[moves_made % 2]
+            row = random.randint(0, 2)
+            column = random.randint(0, 2)
+
+            if make_move(board, current_player, row, column):
+                moves_made += 1
+
+        if not check_winner(board):
+            return board
+
+
+def display_board(board):
+    """
+    Displays the Tic Tac Toe board.
+
+    Parameters:
+    - board (list): The Tic Tac Toe board.
+    """
+    for row in board:
+        print(" | ".join(row))
+        print("-" * 9)
+
+
+def complete_lists_with_dictionary(lists, dictionary):
+    """
+    Completes lists with characters from a dictionary.
+
+    Parameters:
+    - lists (list): A list of lists to be completed.
+    - dictionary (dict): A dictionary where keys are binary strings and values are probabilities.
+
+    Returns:
+    - result (list): A list of lists with characters filled in from the dictionary.
+    """
+    result = []
+
+    for key, value in dictionary.items():
+        # Create a copy of the original list
+        new_list = [list(row) for row in lists]
+
+        # Convert the binary value of the key into a list of characters 'O' and 'X'
+        characters = ['O' if bit == '0' else 'X' for bit in key]
+
+        # Fill in the empty spaces in the new list with the corresponding characters
+        index = 0
+        for i in range(len(new_list)):
+            for j in range(len(new_list[i])):
+                if new_list[i][j] == ' ':
+                    new_list[i][j] = characters[index]
+                    index += 1
+
+        result.append(new_list)
+
+    return result
+
+
+def filter_values_above_average(dictionary):
+    """
+    Filters values above the average from a dictionary.
+
+    Parameters:
+    - dictionary (dict): A dictionary where keys are binary strings and values are probabilities.
+
+    Returns:
+    - filtered_dictionary (dict): A dictionary with values above the average.
+    """
+    values = list(dictionary.values())
+    average = sum(values) / len(values)
+
+    # Calculate the difference between the maximum and minimum values
+    max_min_difference = max(values) - min(values)
+
+    # Check if the difference is small compared to the average
+    if max_min_difference < 0.1 * average:
+        return dictionary
+
+    # Filter values above the average
+    filtered_dictionary = {key: value for key,
+                           value in dictionary.items() if value > average}
+    return filtered_dictionary
+
+
+if __name__ == '__main__':
+    # Example of usage
+    num_moves = 5
+    random_board = generate_random_board(num_moves)
+    print(random_board)
+    print('Board:')
+    display_board(random_board)
diff --git a/challenges/QOSF challenge/QuantumVoyagers/pkg/quantum_utils.py b/challenges/QOSF challenge/QuantumVoyagers/pkg/quantum_utils.py
new file mode 100644
index 0000000..b3ac2a5
--- /dev/null
+++ b/challenges/QOSF challenge/QuantumVoyagers/pkg/quantum_utils.py	
@@ -0,0 +1,292 @@
+from qiskit import QuantumCircuit, ClassicalRegister, QuantumRegister, execute, Aer
+from qiskit.circuit.library import XGate
+
+
+def setting_initial_configuration(board):
+    """
+    Initializes a quantum circuit with the given Tic Tac Toe board configuration.
+
+    Args:
+        board (list of lists): Represents the Tic Tac Toe board.
+
+    Returns:
+        QuantumCircuit: Quantum circuit with the specified initial configuration.
+    """
+    n_qubits = 9
+    counter_aux_qubits = 4
+    aux_conditions_qubits = 8
+    oracle_qubit = 1
+    empty_spaces = sum(row.count(' ') for row in board)
+
+    qreg_q = QuantumRegister(
+        n_qubits + counter_aux_qubits + aux_conditions_qubits + oracle_qubit, 'q')
+
+    creg_c = ClassicalRegister(empty_spaces, 'c')
+
+    qc = QuantumCircuit(qreg_q, creg_c)
+
+    counter = 0
+    for row in board:
+        for elem in row:
+            if elem == 'O':
+                qc.i(qreg_q[counter])
+            elif elem == 'X':
+                qc.x(qreg_q[counter])
+            else:
+                qc.h(qreg_q[counter])
+            counter += 1
+
+    return qc
+
+
+
+def conditions_and_counter():
+    """
+    Creates a quantum circuit to apply conditions and count the number of 'X's on the board.
+
+    Returns:
+        QuantumCircuit: Quantum circuit for conditions and counting.
+    """
+    n_qubits = 9
+    counter_aux_qubits = 4
+    aux_conditions_qubits = 8
+    oracle_qubit = 1
+
+    qreg_q = QuantumRegister(
+        n_qubits + counter_aux_qubits + aux_conditions_qubits + oracle_qubit, 'q')
+
+    mcx = XGate().control(3)
+
+    qc = QuantumCircuit(qreg_q)
+
+    # 8 possible ways for 'X' to win the game
+    qc.barrier()
+    qc.mct([0, 3, 6], 13)
+    qc.mct([0, 4, 8], 14)
+    qc.mct([3, 4, 5], 15)
+    qc.mct([1, 4, 7], 16)
+    qc.mct([0, 1, 2], 17)
+    qc.mct([2, 5, 8], 18)
+    qc.mct([6, 7, 8], 19)
+    qc.mct([2, 4, 6], 20)
+    qc.barrier()
+
+    # Bit adder, counting the number of 'X's on the board
+    qc.cx(qreg_q[0], qreg_q[9])
+    qc.barrier()
+
+    qc.ccx(qreg_q[1], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[1], qreg_q[9])
+    qc.barrier()
+
+    qc.ccx(qreg_q[2], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[2], qreg_q[9])
+    qc.barrier()
+
+    qc.append(mcx, [3, 9, 10, 11])
+    qc.ccx(qreg_q[3], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[3], qreg_q[9])
+    qc.barrier()
+
+    qc.append(mcx, [4, 9, 10, 11])
+    qc.ccx(qreg_q[4], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[4], qreg_q[9])
+    qc.barrier()
+
+    qc.append(mcx, [5, 9, 10, 11])
+    qc.ccx(qreg_q[5], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[5], qreg_q[9])
+    qc.barrier()
+
+    qc.append(mcx, [6, 9, 10, 11])
+    qc.ccx(qreg_q[6], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[6], qreg_q[9])
+    qc.barrier()
+
+    qc.append(mcx, [7, 9, 10, 11])
+    qc.ccx(qreg_q[7], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[7], qreg_q[9])
+    qc.barrier()
+
+    qc.append(mcx, [8, 9, 10, 11])
+    qc.ccx(qreg_q[8], qreg_q[9], qreg_q[10])
+    qc.cx(qreg_q[8], qreg_q[9])
+    qc.barrier()
+
+    qc.x(qreg_q[9])
+    qc.x(qreg_q[10])
+
+    qc.mct([9, 10, 11], 12)
+
+    qc.barrier()
+
+    return qc
+
+def oracle():
+    """
+    Creates a quantum circuit for the oracle part of the algorithm.
+
+    Returns:
+        QuantumCircuit: Quantum circuit for the oracle.
+    """
+    n_qubits = 9
+    counter_aux_qubits = 4
+    aux_conditions_qubits = 8
+    oracle_qubit = 1
+
+    qreg_q = QuantumRegister(
+        n_qubits + counter_aux_qubits + aux_conditions_qubits + oracle_qubit, 'q')
+
+    qc = QuantumCircuit(qreg_q)
+
+    qc = qc.compose(conditions_and_counter())
+
+    qc.barrier()
+    qc.x(21)
+    qc.h(21)
+    qc.barrier()
+
+    # Oracle
+    qc.mct([12, 13], 21)
+    qc.mct([12, 14], 21)
+    qc.mct([12, 15], 21)
+    qc.mct([12, 16], 21)
+    qc.mct([12, 17], 21)
+    qc.mct([12, 18], 21)
+    qc.mct([12, 19], 21)
+    qc.mct([12, 20], 21)
+
+    qc.barrier()
+    qc = qc.compose(conditions_and_counter().inverse())
+
+    return qc
+
+
+def diffuser(board):
+    """
+    Creates a quantum circuit for the Grover Diffuser.
+
+    Args:
+        board (list): The Tic Tac Toe board.
+
+    Returns:
+        QuantumCircuit: Quantum circuit representing the Grover Diffuser.
+    """
+    n_qubits = 9
+    one_dimensional_list = [value for row in board for value in row]
+    index_empty_spaces = [i for i, value in enumerate(
+        one_dimensional_list) if value == ' ']
+
+    qreg_q = QuantumRegister(n_qubits, 'q')
+
+    qc = QuantumCircuit(qreg_q)
+
+    for qubit in index_empty_spaces:
+        qc.h(qubit)
+    # Apply transformation |00..0> -> |11..1> (X-gates)
+    for qubit in index_empty_spaces:
+        qc.x(qubit)
+
+    qc.barrier()
+    # Apply multiple controlled Z-gates
+    qc.h(index_empty_spaces[-1])
+    # Toffoli with multicontrol
+    qc.mct(index_empty_spaces[:-1], index_empty_spaces[-1])
+    qc.h(index_empty_spaces[-1])
+    qc.barrier()
+    # Apply transformation |11..1> -> |00..0>
+    for qubit in index_empty_spaces:
+        qc.x(qubit)
+    # Apply transformation |00..0> -> |s>
+    for qubit in index_empty_spaces:
+        qc.h(qubit)
+
+    # qc.measure([4,5,7,8],creg_c)
+
+    return qc
+
+
+def measurement(qc, board):
+    """
+    Adds the measurement operation to the quantum circuit.
+
+    Args:
+        qc (QuantumCircuit): Quantum circuit.
+        board (list): The Tic Tac Toe board.
+
+    Returns:
+        QuantumCircuit: Quantum circuit with measurement operation.
+    """
+    one_dimensional_list = [value for row in board for value in row]
+    index_empty_spaces = [i for i, value in enumerate(
+        one_dimensional_list) if value == ' ']
+
+    qc.measure(index_empty_spaces, qc.clbits)
+    return qc
+
+
+
+def grover_algorithm(board, rep=1):
+    """
+    Executes the Grover's algorithm for Tic Tac Toe.
+
+    Args:
+        board (list): The initial state of the Tic Tac Toe board.
+        rep (int): Number of iterations of the algorithm.
+
+    Returns:
+        QuantumCircuit: Quantum circuit representing the Grover's algorithm.
+    """
+    qc = setting_initial_configuration(board)
+    qc.barrier()
+
+    for _ in range(rep):
+        # Oracle
+        qc = qc.compose(oracle())
+        qc.barrier()
+        # Diffuser
+        qc = qc.compose(diffuser(board))
+        qc.barrier()
+
+    # Measurement
+    qc = measurement(qc, board)
+    qc.barrier()
+
+    return qc
+
+
+def circuit_execute(qc, shots=10000):
+    """
+    Executes the quantum circuit on a simulator.
+
+    Args:
+        qc (QuantumCircuit): Quantum circuit.
+        shots (int): Number of shots for the simulation.
+
+    Returns:
+        dict: Counts of the measurement outcomes.
+    """
+    simulator = Aer.get_backend('qasm_simulator')
+    job = execute(qc, simulator, shots=shots)
+    result = job.result()
+    # Returns counts
+    counts = result.get_counts(qc)
+
+    counts_without_qiskit_convention = {
+        key[::-1]: value for key, value in counts.items()}
+
+    return counts_without_qiskit_convention
+
+if __name__ == '__main__':
+    # Example of usage
+    from general_utils import generate_random_board
+
+    num_moves = 5
+    board = generate_random_board(num_moves)
+    # print(board)
+    qc_init = setting_initial_configuration(board)
+    print(qc_init)
+
+    # Oracle
+    print(oracle())
+    # print(diffuser(board))
diff --git a/challenges/openqaoa challenge/QuantumVoyagers/Image/image11.png b/challenges/openqaoa challenge/QuantumVoyagers/Image/image11.png
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diff --git a/challenges/openqaoa challenge/QuantumVoyagers/challenge_openqaoa.ipynb b/challenges/openqaoa challenge/QuantumVoyagers/challenge_openqaoa.ipynb
new file mode 100644
index 0000000..539eb3f
--- /dev/null
+++ b/challenges/openqaoa challenge/QuantumVoyagers/challenge_openqaoa.ipynb	
@@ -0,0 +1,1739 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "UXfAFmJAu1zx"
+      },
+      "source": [
+        "# Challenge: OpenQAOA\n",
+        "\n",
+        "Quantum computing is used extensively for modelling and solving combinatorial optimisation problems. The purpose of this is to find a problem with binary clauses where the amount of states is immense and difficult to solve with classical resources. This type of problem is known as NP-hard. in order to uncover the correct answers, quantum computing produces algorithms of NP-complexity. On the other hand, in quantum computing, we are interested in representing such a model in a quantum circuit and being able to find the optimal states that satisfy the cost function using a classical optimizer.\n",
+        "\n",
+        "Multiple companies work around computers and generate an SDK that can generate quantum circuits, in this challenge, we focus on a fundamental step of the Quantum Approximate Optimization Algorithm (QAOA) algorithm. Before starting the quantum part, one must model a problem in terms of 0 and 1 and convert it into a Quadratic unconstrained binary optimization (QUBO) form that can then be converted into an Ising model to find the optimal states. To validate the model one makes use of OpenQAOA, an SDK focused on circuitry of the QAOA algorithm.\n",
+        "\n",
+        "If you want to know more about this SDK you can check the following link https://openqaoa.entropicalabs.com/\n",
+        "\n",
+        "**NOTES**:\n",
+        ">\n",
+        ">   * To run on real QPU or  simulators you can use  [qbraid](https://account.qbraid.com/)\n",
+        ">\n",
+        ">   * The [OpenQAOA workflow](https://openqaoa.entropicalabs.com/workflows/customise-the-QAOA-workflow/#the-circuit-properties)\n",
+        ">\n",
+        ">   * To guide you, you can check out [examples of problems in OpenQAOA](https://github.com/entropicalabs/openqaoa/tree/main/examples/community_tutorials)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "wYvBlJm1vCLU",
+        "outputId": "5e9ae279-b6dc-4e3f-b5bb-0ed047f1c4a8"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Collecting docplex\n",
+            "  Downloading docplex-2.25.236.tar.gz (633 kB)\n",
+            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/633.5 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m92.2/633.5 kB\u001b[0m \u001b[31m2.9 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━━━━━━\u001b[0m \u001b[32m481.3/633.5 kB\u001b[0m \u001b[31m7.1 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m633.5/633.5 kB\u001b[0m \u001b[31m7.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from docplex) (1.16.0)\n",
+            "Building wheels for collected packages: docplex\n",
+            "  Building wheel for docplex (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for docplex: filename=docplex-2.25.236-py3-none-any.whl size=671350 sha256=1329a531f03c175bc208d61aa37e8e19bf9b297aa9d1d1b155ec2f85d9f8d9db\n",
+            "  Stored in directory: /root/.cache/pip/wheels/3b/e5/00/0bf0173d67188fe73a13e3a61412b3f975f60205e3fab93a69\n",
+            "Successfully built docplex\n",
+            "Installing collected packages: docplex\n",
+            "Successfully installed docplex-2.25.236\n",
+            "Requirement already satisfied: h5py in /usr/local/lib/python3.10/dist-packages (3.9.0)\n",
+            "Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.10/dist-packages (from h5py) (1.23.5)\n",
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+            "Requirement already satisfied: wheel in /usr/local/lib/python3.10/dist-packages (0.41.3)\n",
+            "Collecting azure-quantum[qiskit]\n",
+            "  Downloading azure_quantum-0.28.302812-py3-none-any.whl (180 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m180.2/180.2 kB\u001b[0m \u001b[31m5.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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+            "  Downloading qiskit_terra-0.24.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (6.0 MB)\n",
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+            "\u001b[?25hCollecting qiskit-qir<0.4,>=0.3.1 (from azure-quantum[qiskit])\n",
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+            "Collecting caio~=0.9.0 (from aiofile<4.0,>=3.7.2->azure-quantum[qiskit])\n",
+            "  Downloading caio-0.9.13-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (79 kB)\n",
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+            "  Downloading msal-1.25.0-py2.py3-none-any.whl (97 kB)\n",
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+            "\u001b[?25hCollecting msal-extensions<2.0.0,>=0.3.0 (from azure-identity<2.0.0,>=1.12.0->azure-quantum[qiskit])\n",
+            "  Downloading msal_extensions-1.0.0-py2.py3-none-any.whl (19 kB)\n",
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+            "Collecting decorator>=5.1.0 (from qiskit-ionq<1.0,>=0.3.3->azure-quantum[qiskit])\n",
+            "  Downloading decorator-5.1.1-py3-none-any.whl (9.1 kB)\n",
+            "Collecting retry>=0.9.0 (from qiskit-ionq<1.0,>=0.3.3->azure-quantum[qiskit])\n",
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+            "Requirement already satisfied: importlib-metadata>=4.11.4 in /usr/local/lib/python3.10/dist-packages (from qiskit-ionq<1.0,>=0.3.3->azure-quantum[qiskit]) (6.8.0)\n",
+            "Collecting qiskit>=0.34.2 (from qiskit-qir<0.4,>=0.3.1->azure-quantum[qiskit])\n",
+            "  Downloading qiskit-0.45.0-py3-none-any.whl (9.6 kB)\n",
+            "Collecting pyqir==0.8.0 (from qiskit-qir<0.4,>=0.3.1->azure-quantum[qiskit])\n",
+            "  Downloading pyqir-0.8.0-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.5 MB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.5/2.5 MB\u001b[0m \u001b[31m69.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hCollecting rustworkx>=0.12.0 (from qiskit-terra<0.25.0,>=0.19.1->azure-quantum[qiskit])\n",
+            "  Downloading rustworkx-0.13.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.0 MB)\n",
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+            "\u001b[?25hCollecting ply>=3.10 (from qiskit-terra<0.25.0,>=0.19.1->azure-quantum[qiskit])\n",
+            "  Downloading ply-3.11-py2.py3-none-any.whl (49 kB)\n",
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+            "Requirement already satisfied: scipy>=1.5 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra<0.25.0,>=0.19.1->azure-quantum[qiskit]) (1.11.3)\n",
+            "Requirement already satisfied: sympy>=1.3 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra<0.25.0,>=0.19.1->azure-quantum[qiskit]) (1.12)\n",
+            "Collecting dill>=0.3 (from qiskit-terra<0.25.0,>=0.19.1->azure-quantum[qiskit])\n",
+            "  Downloading dill-0.3.7-py3-none-any.whl (115 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m115.3/115.3 kB\u001b[0m \u001b[31m17.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: python-dateutil>=2.8.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra<0.25.0,>=0.19.1->azure-quantum[qiskit]) (2.8.2)\n",
+            "Collecting stevedore>=3.0.0 (from qiskit-terra<0.25.0,>=0.19.1->azure-quantum[qiskit])\n",
+            "  Downloading stevedore-5.1.0-py3-none-any.whl (49 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.6/49.6 kB\u001b[0m \u001b[31m6.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hCollecting symengine<0.10,>=0.9 (from qiskit-terra<0.25.0,>=0.19.1->azure-quantum[qiskit])\n",
+            "  Downloading symengine-0.9.2-cp310-cp310-manylinux2010_x86_64.whl (37.5 MB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m37.5/37.5 MB\u001b[0m \u001b[31m20.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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+            "Requirement already satisfied: PyJWT[crypto]<3,>=1.0.0 in /usr/lib/python3/dist-packages (from msal<2.0.0,>=1.24.0->azure-identity<2.0.0,>=1.12.0->azure-quantum[qiskit]) (2.3.0)\n",
+            "Collecting portalocker<3,>=1.0 (from msal-extensions<2.0.0,>=0.3.0->azure-identity<2.0.0,>=1.12.0->azure-quantum[qiskit])\n",
+            "  Downloading portalocker-2.8.2-py3-none-any.whl (17 kB)\n",
+            "INFO: pip is looking at multiple versions of qiskit to determine which version is compatible with other requirements. This could take a while.\n",
+            "Collecting qiskit>=0.34.2 (from qiskit-qir<0.4,>=0.3.1->azure-quantum[qiskit])\n",
+            "  Downloading qiskit-0.44.3-py3-none-any.whl (8.2 kB)\n",
+            "  Downloading qiskit-0.44.2-py3-none-any.whl (8.2 kB)\n",
+            "  Downloading qiskit-0.44.1-py3-none-any.whl (8.2 kB)\n",
+            "  Downloading qiskit-0.44.0.tar.gz (8.9 kB)\n",
+            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
+            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
+            "  Installing backend dependencies ... \u001b[?25l\u001b[?25hdone\n",
+            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Downloading qiskit-0.43.3.tar.gz (9.1 kB)\n",
+            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
+            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
+            "  Installing backend dependencies ... \u001b[?25l\u001b[?25hdone\n",
+            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+            "Collecting qiskit-aer==0.12.2 (from qiskit>=0.34.2->qiskit-qir<0.4,>=0.3.1->azure-quantum[qiskit])\n",
+            "  Downloading qiskit_aer-0.12.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.8 MB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m12.8/12.8 MB\u001b[0m \u001b[31m54.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hCollecting qiskit-ibmq-provider==0.20.2 (from qiskit>=0.34.2->qiskit-qir<0.4,>=0.3.1->azure-quantum[qiskit])\n",
+            "  Downloading qiskit_ibmq_provider-0.20.2-py3-none-any.whl (241 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m241.5/241.5 kB\u001b[0m \u001b[31m28.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hCollecting requests-ntlm<=1.1.0 (from qiskit-ibmq-provider==0.20.2->qiskit>=0.34.2->qiskit-qir<0.4,>=0.3.1->azure-quantum[qiskit])\n",
+            "  Downloading requests_ntlm-1.1.0-py2.py3-none-any.whl (5.7 kB)\n",
+            "Requirement already satisfied: urllib3>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from qiskit-ibmq-provider==0.20.2->qiskit>=0.34.2->qiskit-qir<0.4,>=0.3.1->azure-quantum[qiskit]) (2.0.7)\n",
+            "Requirement already satisfied: websocket-client>=1.5.1 in /usr/local/lib/python3.10/dist-packages (from qiskit-ibmq-provider==0.20.2->qiskit>=0.34.2->qiskit-qir<0.4,>=0.3.1->azure-quantum[qiskit]) (1.6.4)\n",
+            "Collecting websockets>=10.0 (from qiskit-ibmq-provider==0.20.2->qiskit>=0.34.2->qiskit-qir<0.4,>=0.3.1->azure-quantum[qiskit])\n",
+            "  Downloading websockets-12.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (130 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m130.2/130.2 kB\u001b[0m \u001b[31m18.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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+            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from requests-oauthlib>=0.5.0->msrest<1.0,>=0.7.1->azure-quantum[qiskit]) (3.2.2)\n",
+            "Collecting py<2.0.0,>=1.4.26 (from retry>=0.9.0->qiskit-ionq<1.0,>=0.3.3->azure-quantum[qiskit])\n",
+            "  Downloading py-1.11.0-py2.py3-none-any.whl (98 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m98.7/98.7 kB\u001b[0m \u001b[31m14.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hCollecting pbr!=2.1.0,>=2.0.0 (from stevedore>=3.0.0->qiskit-terra<0.25.0,>=0.19.1->azure-quantum[qiskit])\n",
+            "  Downloading pbr-6.0.0-py2.py3-none-any.whl (107 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m107.5/107.5 kB\u001b[0m \u001b[31m16.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy>=1.3->qiskit-terra<0.25.0,>=0.19.1->azure-quantum[qiskit]) (1.3.0)\n",
+            "Requirement already satisfied: pycparser in /usr/local/lib/python3.10/dist-packages (from cffi>=1.12->cryptography>=2.5->azure-identity<2.0.0,>=1.12.0->azure-quantum[qiskit]) (2.21)\n",
+            "Collecting ntlm-auth>=1.0.2 (from requests-ntlm<=1.1.0->qiskit-ibmq-provider==0.20.2->qiskit>=0.34.2->qiskit-qir<0.4,>=0.3.1->azure-quantum[qiskit])\n",
+            "  Downloading ntlm_auth-1.5.0-py2.py3-none-any.whl (29 kB)\n",
+            "Building wheels for collected packages: qiskit\n",
+            "  Building wheel for qiskit (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for qiskit: filename=qiskit-0.43.3-py3-none-any.whl size=7632 sha256=3268d2279302e4d69307ab6c608a97add695efa49340fcb19a0174e864b3dc75\n",
+            "  Stored in directory: /root/.cache/pip/wheels/c3/88/e5/483e1c761b53470dad74ee047f8ad4d67d4f52ec9dc9d13563\n",
+            "Successfully built qiskit\n",
+            "Installing collected packages: ply, websockets, typing-extensions, symengine, rustworkx, python-markdown-math, pyqir, py, portalocker, pbr, ntlm-auth, isodate, dill, deprecated, decorator, caio, stevedore, retry, azure-core, aiofile, requests-ntlm, qiskit-terra, msrest, azure-storage-blob, qiskit-ionq, qiskit-ibmq-provider, qiskit-aer, msal, qiskit, msal-extensions, qiskit-qir, azure-identity, azure-quantum\n",
+            "  Attempting uninstall: typing-extensions\n",
+            "    Found existing installation: typing_extensions 4.5.0\n",
+            "    Uninstalling typing_extensions-4.5.0:\n",
+            "      Successfully uninstalled typing_extensions-4.5.0\n",
+            "  Attempting uninstall: decorator\n",
+            "    Found existing installation: decorator 4.4.2\n",
+            "    Uninstalling decorator-4.4.2:\n",
+            "      Successfully uninstalled decorator-4.4.2\n",
+            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+            "ipython 7.34.0 requires jedi>=0.16, which is not installed.\n",
+            "moviepy 1.0.3 requires decorator<5.0,>=4.0.2, but you have decorator 5.1.1 which is incompatible.\n",
+            "tensorflow-probability 0.22.0 requires typing-extensions<4.6.0, but you have typing-extensions 4.8.0 which is incompatible.\u001b[0m\u001b[31m\n",
+            "\u001b[0mSuccessfully installed aiofile-3.8.8 azure-core-1.29.5 azure-identity-1.15.0 azure-quantum-0.28.302812 azure-storage-blob-12.19.0 caio-0.9.13 decorator-5.1.1 deprecated-1.2.14 dill-0.3.7 isodate-0.6.1 msal-1.25.0 msal-extensions-1.0.0 msrest-0.7.1 ntlm-auth-1.5.0 pbr-6.0.0 ply-3.11 portalocker-2.8.2 py-1.11.0 pyqir-0.8.0 python-markdown-math-0.8 qiskit-0.43.3 qiskit-aer-0.12.2 qiskit-ibmq-provider-0.20.2 qiskit-ionq-0.4.4 qiskit-qir-0.3.1 qiskit-terra-0.24.2 requests-ntlm-1.1.0 retry-0.9.2 rustworkx-0.13.2 stevedore-5.1.0 symengine-0.9.2 typing-extensions-4.8.0 websockets-12.0\n"
+          ]
+        },
+        {
+          "data": {
+            "application/vnd.colab-display-data+json": {
+              "pip_warning": {
+                "packages": [
+                  "decorator"
+                ]
+              }
+            }
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Requirement already satisfied: qiskit in /usr/local/lib/python3.10/dist-packages (0.43.3)\n",
+            "Requirement already satisfied: qiskit-terra==0.24.2 in /usr/local/lib/python3.10/dist-packages (from qiskit) (0.24.2)\n",
+            "Requirement already satisfied: qiskit-aer==0.12.2 in /usr/local/lib/python3.10/dist-packages (from qiskit) (0.12.2)\n",
+            "Requirement already satisfied: qiskit-ibmq-provider==0.20.2 in /usr/local/lib/python3.10/dist-packages (from qiskit) (0.20.2)\n",
+            "Requirement already satisfied: numpy>=1.16.3 in /usr/local/lib/python3.10/dist-packages (from qiskit-aer==0.12.2->qiskit) (1.23.5)\n",
+            "Requirement already satisfied: scipy>=1.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-aer==0.12.2->qiskit) (1.11.3)\n",
+            "Requirement already satisfied: requests>=2.19 in /usr/local/lib/python3.10/dist-packages (from qiskit-ibmq-provider==0.20.2->qiskit) (2.31.0)\n",
+            "Requirement already satisfied: requests-ntlm<=1.1.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-ibmq-provider==0.20.2->qiskit) (1.1.0)\n",
+            "Requirement already satisfied: urllib3>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from qiskit-ibmq-provider==0.20.2->qiskit) (2.0.7)\n",
+            "Requirement already satisfied: python-dateutil>=2.8.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-ibmq-provider==0.20.2->qiskit) (2.8.2)\n",
+            "Requirement already satisfied: websocket-client>=1.5.1 in /usr/local/lib/python3.10/dist-packages (from qiskit-ibmq-provider==0.20.2->qiskit) (1.6.4)\n",
+            "Requirement already satisfied: websockets>=10.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-ibmq-provider==0.20.2->qiskit) (12.0)\n",
+            "Requirement already satisfied: rustworkx>=0.12.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.24.2->qiskit) (0.13.2)\n",
+            "Requirement already satisfied: ply>=3.10 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.24.2->qiskit) (3.11)\n",
+            "Requirement already satisfied: psutil>=5 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.24.2->qiskit) (5.9.5)\n",
+            "Requirement already satisfied: sympy>=1.3 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.24.2->qiskit) (1.12)\n",
+            "Requirement already satisfied: dill>=0.3 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.24.2->qiskit) (0.3.7)\n",
+            "Requirement already satisfied: stevedore>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.24.2->qiskit) (5.1.0)\n",
+            "Requirement already satisfied: symengine<0.10,>=0.9 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.24.2->qiskit) (0.9.2)\n",
+            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.0->qiskit-ibmq-provider==0.20.2->qiskit) (1.16.0)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19->qiskit-ibmq-provider==0.20.2->qiskit) (3.3.2)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19->qiskit-ibmq-provider==0.20.2->qiskit) (3.4)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19->qiskit-ibmq-provider==0.20.2->qiskit) (2023.7.22)\n",
+            "Requirement already satisfied: ntlm-auth>=1.0.2 in /usr/local/lib/python3.10/dist-packages (from requests-ntlm<=1.1.0->qiskit-ibmq-provider==0.20.2->qiskit) (1.5.0)\n",
+            "Requirement already satisfied: cryptography>=1.3 in /usr/local/lib/python3.10/dist-packages (from requests-ntlm<=1.1.0->qiskit-ibmq-provider==0.20.2->qiskit) (41.0.5)\n",
+            "Requirement already satisfied: pbr!=2.1.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from stevedore>=3.0.0->qiskit-terra==0.24.2->qiskit) (6.0.0)\n",
+            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy>=1.3->qiskit-terra==0.24.2->qiskit) (1.3.0)\n",
+            "Requirement already satisfied: cffi>=1.12 in /usr/local/lib/python3.10/dist-packages (from cryptography>=1.3->requests-ntlm<=1.1.0->qiskit-ibmq-provider==0.20.2->qiskit) (1.16.0)\n",
+            "Requirement already satisfied: pycparser in /usr/local/lib/python3.10/dist-packages (from cffi>=1.12->cryptography>=1.3->requests-ntlm<=1.1.0->qiskit-ibmq-provider==0.20.2->qiskit) (2.21)\n",
+            "Collecting cplex\n",
+            "  Downloading cplex-22.1.1.0-cp310-cp310-manylinux1_x86_64.whl (44.2 MB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m44.2/44.2 MB\u001b[0m \u001b[31m25.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hInstalling collected packages: cplex\n",
+            "Successfully installed cplex-22.1.1.0\n",
+            "Collecting openqaoa-qiskit\n",
+            "  Downloading openqaoa_qiskit-0.2.3-py3-none-any.whl (14 kB)\n",
+            "Collecting openqaoa-core==0.2.3 (from openqaoa-qiskit)\n",
+            "  Downloading openqaoa_core-0.2.3-py3-none-any.whl (280 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m280.4/280.4 kB\u001b[0m \u001b[31m5.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: qiskit>=0.36.1 in /usr/local/lib/python3.10/dist-packages (from openqaoa-qiskit) (0.43.3)\n",
+            "Collecting qiskit-ibm-provider (from openqaoa-qiskit)\n",
+            "  Downloading qiskit_ibm_provider-0.7.2-py3-none-any.whl (243 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m243.3/243.3 kB\u001b[0m \u001b[31m12.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: qiskit-aer in /usr/local/lib/python3.10/dist-packages (from openqaoa-qiskit) (0.12.2)\n",
+            "Requirement already satisfied: pandas>=1.3.5 in /usr/local/lib/python3.10/dist-packages (from openqaoa-core==0.2.3->openqaoa-qiskit) (1.5.3)\n",
+            "Requirement already satisfied: sympy>=1.10.1 in /usr/local/lib/python3.10/dist-packages (from openqaoa-core==0.2.3->openqaoa-qiskit) (1.12)\n",
+            "Requirement already satisfied: numpy>=1.22.3 in /usr/local/lib/python3.10/dist-packages (from openqaoa-core==0.2.3->openqaoa-qiskit) (1.23.5)\n",
+            "Requirement already satisfied: networkx>=2.8 in /usr/local/lib/python3.10/dist-packages (from openqaoa-core==0.2.3->openqaoa-qiskit) (3.2.1)\n",
+            "Requirement already satisfied: matplotlib>=3.4.3 in /usr/local/lib/python3.10/dist-packages (from openqaoa-core==0.2.3->openqaoa-qiskit) (3.7.1)\n",
+            "Requirement already satisfied: scipy>=1.8 in /usr/local/lib/python3.10/dist-packages (from openqaoa-core==0.2.3->openqaoa-qiskit) (1.11.3)\n",
+            "Requirement already satisfied: docplex==2.25.236 in /usr/local/lib/python3.10/dist-packages (from openqaoa-core==0.2.3->openqaoa-qiskit) (2.25.236)\n",
+            "Requirement already satisfied: autograd>=1.4 in /usr/local/lib/python3.10/dist-packages (from openqaoa-core==0.2.3->openqaoa-qiskit) (1.6.2)\n",
+            "Collecting semantic-version>=2.10 (from openqaoa-core==0.2.3->openqaoa-qiskit)\n",
+            "  Downloading semantic_version-2.10.0-py2.py3-none-any.whl (15 kB)\n",
+            "Collecting autoray>=0.3.1 (from openqaoa-core==0.2.3->openqaoa-qiskit)\n",
+            "  Downloading autoray-0.6.7-py3-none-any.whl (49 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.9/49.9 kB\u001b[0m \u001b[31m6.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from openqaoa-core==0.2.3->openqaoa-qiskit) (2.31.0)\n",
+            "Collecting ipython>=8.2.0 (from openqaoa-core==0.2.3->openqaoa-qiskit)\n",
+            "  Downloading ipython-8.17.2-py3-none-any.whl (808 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m808.4/808.4 kB\u001b[0m \u001b[31m16.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from docplex==2.25.236->openqaoa-core==0.2.3->openqaoa-qiskit) (1.16.0)\n",
+            "Requirement already satisfied: qiskit-terra==0.24.2 in /usr/local/lib/python3.10/dist-packages (from qiskit>=0.36.1->openqaoa-qiskit) (0.24.2)\n",
+            "Requirement already satisfied: qiskit-ibmq-provider==0.20.2 in /usr/local/lib/python3.10/dist-packages (from qiskit>=0.36.1->openqaoa-qiskit) (0.20.2)\n",
+            "Requirement already satisfied: requests-ntlm<=1.1.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-ibmq-provider==0.20.2->qiskit>=0.36.1->openqaoa-qiskit) (1.1.0)\n",
+            "Requirement already satisfied: urllib3>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from qiskit-ibmq-provider==0.20.2->qiskit>=0.36.1->openqaoa-qiskit) (2.0.7)\n",
+            "Requirement already satisfied: python-dateutil>=2.8.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-ibmq-provider==0.20.2->qiskit>=0.36.1->openqaoa-qiskit) (2.8.2)\n",
+            "Requirement already satisfied: websocket-client>=1.5.1 in /usr/local/lib/python3.10/dist-packages (from qiskit-ibmq-provider==0.20.2->qiskit>=0.36.1->openqaoa-qiskit) (1.6.4)\n",
+            "Requirement already satisfied: websockets>=10.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-ibmq-provider==0.20.2->qiskit>=0.36.1->openqaoa-qiskit) (12.0)\n",
+            "Requirement already satisfied: rustworkx>=0.12.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.24.2->qiskit>=0.36.1->openqaoa-qiskit) (0.13.2)\n",
+            "Requirement already satisfied: ply>=3.10 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.24.2->qiskit>=0.36.1->openqaoa-qiskit) (3.11)\n",
+            "Requirement already satisfied: psutil>=5 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.24.2->qiskit>=0.36.1->openqaoa-qiskit) (5.9.5)\n",
+            "Requirement already satisfied: dill>=0.3 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.24.2->qiskit>=0.36.1->openqaoa-qiskit) (0.3.7)\n",
+            "Requirement already satisfied: stevedore>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.24.2->qiskit>=0.36.1->openqaoa-qiskit) (5.1.0)\n",
+            "Requirement already satisfied: symengine<0.10,>=0.9 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.24.2->qiskit>=0.36.1->openqaoa-qiskit) (0.9.2)\n",
+            "Collecting qiskit>=0.36.1 (from openqaoa-qiskit)\n",
+            "  Using cached qiskit-0.45.0-py3-none-any.whl (9.6 kB)\n",
+            "Requirement already satisfied: typing-extensions>=4.3 in /usr/local/lib/python3.10/dist-packages (from qiskit-ibm-provider->openqaoa-qiskit) (4.8.0)\n",
+            "Collecting qiskit-terra>=0.21.0 (from qiskit-aer->openqaoa-qiskit)\n",
+            "  Downloading qiskit_terra-0.45.0-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (6.3 MB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.3/6.3 MB\u001b[0m \u001b[31m9.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: future>=0.15.2 in /usr/local/lib/python3.10/dist-packages (from autograd>=1.4->openqaoa-core==0.2.3->openqaoa-qiskit) (0.18.3)\n",
+            "Requirement already satisfied: decorator in /usr/local/lib/python3.10/dist-packages (from ipython>=8.2.0->openqaoa-core==0.2.3->openqaoa-qiskit) (5.1.1)\n",
+            "Collecting jedi>=0.16 (from ipython>=8.2.0->openqaoa-core==0.2.3->openqaoa-qiskit)\n",
+            "  Downloading jedi-0.19.1-py2.py3-none-any.whl (1.6 MB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.6/1.6 MB\u001b[0m \u001b[31m63.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: matplotlib-inline in /usr/local/lib/python3.10/dist-packages (from ipython>=8.2.0->openqaoa-core==0.2.3->openqaoa-qiskit) (0.1.6)\n",
+            "Requirement already satisfied: prompt-toolkit!=3.0.37,<3.1.0,>=3.0.30 in /usr/local/lib/python3.10/dist-packages (from ipython>=8.2.0->openqaoa-core==0.2.3->openqaoa-qiskit) (3.0.39)\n",
+            "Requirement already satisfied: pygments>=2.4.0 in /usr/local/lib/python3.10/dist-packages (from ipython>=8.2.0->openqaoa-core==0.2.3->openqaoa-qiskit) (2.16.1)\n",
+            "Collecting stack-data (from ipython>=8.2.0->openqaoa-core==0.2.3->openqaoa-qiskit)\n",
+            "  Downloading stack_data-0.6.3-py3-none-any.whl (24 kB)\n",
+            "Requirement already satisfied: traitlets>=5 in /usr/local/lib/python3.10/dist-packages (from ipython>=8.2.0->openqaoa-core==0.2.3->openqaoa-qiskit) (5.7.1)\n",
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+            "Requirement already satisfied: cryptography>=1.3 in /usr/local/lib/python3.10/dist-packages (from requests-ntlm<=1.1.0->qiskit-ibmq-provider==0.20.2->qiskit>=0.36.1->openqaoa-qiskit) (41.0.5)\n",
+            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy>=1.10.1->openqaoa-core==0.2.3->openqaoa-qiskit) (1.3.0)\n",
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+            "Requirement already satisfied: ptyprocess>=0.5 in /usr/local/lib/python3.10/dist-packages (from pexpect>4.3->ipython>=8.2.0->openqaoa-core==0.2.3->openqaoa-qiskit) (0.7.0)\n",
+            "Requirement already satisfied: wcwidth in /usr/local/lib/python3.10/dist-packages (from prompt-toolkit!=3.0.37,<3.1.0,>=3.0.30->ipython>=8.2.0->openqaoa-core==0.2.3->openqaoa-qiskit) (0.2.9)\n",
+            "Requirement already satisfied: pbr!=2.1.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from stevedore>=3.0.0->qiskit-terra==0.24.2->qiskit>=0.36.1->openqaoa-qiskit) (6.0.0)\n",
+            "Collecting executing>=1.2.0 (from stack-data->ipython>=8.2.0->openqaoa-core==0.2.3->openqaoa-qiskit)\n",
+            "  Downloading executing-2.0.1-py2.py3-none-any.whl (24 kB)\n",
+            "Collecting asttokens>=2.1.0 (from stack-data->ipython>=8.2.0->openqaoa-core==0.2.3->openqaoa-qiskit)\n",
+            "  Downloading asttokens-2.4.1-py2.py3-none-any.whl (27 kB)\n",
+            "Collecting pure-eval (from stack-data->ipython>=8.2.0->openqaoa-core==0.2.3->openqaoa-qiskit)\n",
+            "  Downloading pure_eval-0.2.2-py3-none-any.whl (11 kB)\n",
+            "Requirement already satisfied: pycparser in /usr/local/lib/python3.10/dist-packages (from cffi>=1.12->cryptography>=1.3->requests-ntlm<=1.1.0->qiskit-ibmq-provider==0.20.2->qiskit>=0.36.1->openqaoa-qiskit) (2.21)\n",
+            "Installing collected packages: pure-eval, semantic-version, jedi, executing, autoray, asttokens, stack-data, qiskit-terra, qiskit, ipython, qiskit-ibm-provider, openqaoa-core, openqaoa-qiskit\n",
+            "  Attempting uninstall: qiskit-terra\n",
+            "    Found existing installation: qiskit-terra 0.24.2\n",
+            "    Uninstalling qiskit-terra-0.24.2:\n",
+            "      Successfully uninstalled qiskit-terra-0.24.2\n",
+            "  Attempting uninstall: qiskit\n",
+            "    Found existing installation: qiskit 0.43.3\n",
+            "    Uninstalling qiskit-0.43.3:\n",
+            "      Successfully uninstalled qiskit-0.43.3\n",
+            "  Attempting uninstall: ipython\n",
+            "    Found existing installation: ipython 7.34.0\n",
+            "    Uninstalling ipython-7.34.0:\n",
+            "      Successfully uninstalled ipython-7.34.0\n",
+            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+            "google-colab 1.0.0 requires ipython==7.34.0, but you have ipython 8.17.2 which is incompatible.\u001b[0m\u001b[31m\n",
+            "\u001b[0mSuccessfully installed asttokens-2.4.1 autoray-0.6.7 executing-2.0.1 ipython-8.17.2 jedi-0.19.1 openqaoa-core-0.2.3 openqaoa-qiskit-0.2.3 pure-eval-0.2.2 qiskit-0.45.0 qiskit-ibm-provider-0.7.2 qiskit-terra-0.45.0 semantic-version-2.10.0 stack-data-0.6.3\n"
+          ]
+        },
+        {
+          "data": {
+            "application/vnd.colab-display-data+json": {
+              "pip_warning": {
+                "packages": [
+                  "IPython"
+                ]
+              }
+            }
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "!pip install docplex\n",
+        "!pip install h5py\n",
+        "!pip install typing-extensions\n",
+        "!pip install wheel\n",
+        "!pip install --upgrade azure-quantum\\[qiskit\\]\n",
+        "!pip install qiskit\n",
+        "!pip install cplex\n",
+        "!pip install openqaoa-qiskit"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "nxUZikB1u1z1"
+      },
+      "source": [
+        "# Problem to solve\n",
+        "\n",
+        "Find a real-world problem that can benefit from the application of combinatorial optimization. Consult the list of [OpenQAOA](https://openqaoa.entropicalabs.com/) problem classes to find references.\n",
+        "\n",
+        "Your solution's innovativeness will be rewarded with extra points.\n",
+        "\n",
+        "The process is the following\n",
+        "\n",
+        "![wf.png](attachment:wf.png)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Kxt5UK1pu1z1"
+      },
+      "source": [
+        "## Part 1: Define your problem and solve it using QAOA\n",
+        "Considering the examples based on OpenQAOA, we already have different classes and methods that facilitate the construction of quantum circuits, but to generate a QUBO we will rely on docplex.\n",
+        "\n",
+        "You can find more information on QAOA [examples](https://github.com/entropicalabs/openqaoa/tree/main/examples) and how to generate [QUBOs](https://openqaoa.entropicalabs.com/problems/what-is-a-qubo/) in the [OpenQAOA documentation](https://openqaoa.entropicalabs.com/). The code is available on [GitHub](https://github.com/entropicalabs/openqaoa/tree/main) and you can find more details of implementation in the [API reference](https://el-openqaoa.readthedocs.io/en/main/index.html)."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## 1) Tic Tac Toe Game\n",
+        "This problem can be solved by treating each cell as a variable, and our objective function aims to maximize the number of winning moves. For instance, if we want to address the following problem:\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "<div>\n",
+        "<p style = 'text-align:center;'>\n",
+        "<img src=\"Image/image11.png\" alt=\"JuveYell\" width=\"300px\">\n",
+        "</p>\n",
+        "</div>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "So, for x_0, we observe it has 2 winning possibilities. On the other hand, x_1 has only one, x_2 has only one too, x_3 has 0 winning possibilities, and x_4 has only 1 winning option. Therefore, our objective function is formulated as follows:\n",
+        "$$f_1(\\textbf{x}) = 2*x_0 + 1*x_1 + 1*x_2 + 0*x_3 + 1*x_4$$\n",
+        "\n",
+        "This objective function is subject to an equality constraint, as when the game starts with 0's, there should be a total of 4 X's played. This forms our constraint, but in this case, given an initial configuration, we subtract 2 X's:\n",
+        "\n",
+        "$$x_0 + x_1 + x_2 + x_3 + x_4= 2$$"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": []
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "id": "PTkbAZxDu1z2"
+      },
+      "outputs": [],
+      "source": [
+        "%matplotlib notebook\n",
+        "\n",
+        "# Import external libraries to present an manipulate the data\n",
+        "import numpy as np\n",
+        "import matplotlib.pyplot as plt\n",
+        "import pandas as pd\n",
+        "\n",
+        "# Import docplex model to generate the problem to optimize\n",
+        "from docplex.mp.model import Model\n",
+        "\n",
+        "# Import the libraries needed to employ the QAOA quantum algorithm using OpenQAOA\n",
+        "from openqaoa import QAOA\n",
+        "\n",
+        "# method to covnert a docplex model to a qubo problem\n",
+        "from openqaoa.problems.converters import FromDocplex2IsingModel #check this method and properties\n",
+        "from openqaoa.backends import create_device\n",
+        "\n",
+        "# method to find the correct states for the QAOA object\n",
+        "from openqaoa.utilities import ground_state_hamiltonian"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "id": "DbPRjxw3u1z4"
+      },
+      "outputs": [],
+      "source": [
+        "# inputs\n",
+        "\n",
+        "\n",
+        "def Problem():\n",
+        "  # initialize a model\n",
+        "  mdl = Model(\"Tic_Tac_Toe_Problem_using_maximize\")\n",
+        "  # indicate the binary variables\n",
+        "  n_vars = 5\n",
+        "\n",
+        "  # Using binary variables for this model\n",
+        "  x = mdl.binary_var_list(n_vars, name=\"x\")\n",
+        "  # define the objective function\n",
+        "  obj_func = 2*x[0] + x[1] + 1*x[2] + 0*x[3] + 1*x[4]\n",
+        "  mdl.maximize(obj_func)\n",
+        "  # add the constraints\n",
+        "  mdl.add_constraint(x[0] + x[1] + x[2] + x[3] + x[4] == 2)\n",
+        "  #qubo = FromDocplex2IsingModel(mdl)\n",
+        "  return  mdl#return model, check FromDocplex2IsingModel"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "i34LQrzbu1z5",
+        "outputId": "a79c2515-b188-4c4b-ab17-7409b6eca188"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "// This file has been generated by DOcplex\n",
+            "// model name is: Tic_Tac_Toe_Problem_using_maximize\n",
+            "// var contrainer section\n",
+            "dvar bool x[5];\n",
+            "\n",
+            "// single vars section\n",
+            "dvar bool x_0;\n",
+            "dvar bool x_1;\n",
+            "dvar bool x_2;\n",
+            "dvar bool x_3;\n",
+            "dvar bool x_4;\n",
+            "\n",
+            "minimize\n",
+            " - 26 x_0 - 25 x_1 - 25 x_2 - 24 x_3 - 25 x_4 [ 6 x_0^2 + 12 x_0*x_1\n",
+            " + 12 x_0*x_2 + 12 x_0*x_3 + 12 x_0*x_4 + 6 x_1^2 + 12 x_1*x_2 + 12 x_1*x_3\n",
+            " + 12 x_1*x_4 + 6 x_2^2 + 12 x_2*x_3 + 12 x_2*x_4 + 6 x_3^2 + 12 x_3*x_4\n",
+            " + 6 x_4^2 ] + 24;\n",
+            " \n",
+            "subject to {\n",
+            "\n",
+            "}\n"
+          ]
+        }
+      ],
+      "source": [
+        "problem = Problem()\n",
+        "qubo = FromDocplex2IsingModel(problem)\n",
+        "\n",
+        "# Ising encoding of the QUBO problem for binpacking problem\n",
+        "ising_encoding = qubo.ising_model\n",
+        "\n",
+        "# Docplex encoding of the QUBO problem for binpacking problem\n",
+        "mdl_qubo_docplex = qubo.qubo_docplex\n",
+        "\n",
+        "mdl_qubo_docplex.prettyprint()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 363
+        },
+        "id": "5xBd6VY7u1z6",
+        "outputId": "7bca826e-429b-44e6-d509-59f0c0691a00"
+      },
+      "outputs": [
+        {
+          "data": {
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+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-0fb91cdc-eb78-409a-8d92-d60e3b2db5f6 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "text/plain": [
+              "  solutions_bitstrings  bitstrings_energies  probabilities\n",
+              "0                10001                 -3.0       0.087510\n",
+              "1                11000                 -3.0       0.087510\n",
+              "2                10100                 -3.0       0.087510\n",
+              "3                10010                 -2.0       0.156561\n",
+              "4                01001                 -2.0       0.020661\n",
+              "5                01100                 -2.0       0.020661\n",
+              "6                00101                 -2.0       0.020661\n",
+              "7                00011                 -1.0       0.013770\n",
+              "8                01010                 -1.0       0.013770\n",
+              "9                00110                 -1.0       0.013770"
+            ]
+          },
+          "execution_count": 5,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "# Initialize the QAOA object\n",
+        "qaoa = QAOA()\n",
+        "\n",
+        "# Set the parameters to use the QAOA algorithm\n",
+        "# where n_shots=1024 and  seed_simulator=1\n",
+        "qaoa.set_backend_properties(n_shots=1024, seed_simulator=1)\n",
+        "\n",
+        "# p=1, a custom type and range from 0 to pi\n",
+        "qaoa.set_circuit_properties(p=1, init_type=\"rand\")\n",
+        "\n",
+        "qaoa.compile(ising_encoding)\n",
+        "\n",
+        "# Run the QAOA algorithm\n",
+        "qaoa.optimize()\n",
+        "\n",
+        "results = pd.DataFrame(qaoa.result.lowest_cost_bitstrings(10))\n",
+        "results = results[results[\"bitstrings_energies\"]<0]\n",
+        "results"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {
+        "id": "GVqdkRTju1z7"
+      },
+      "outputs": [],
+      "source": [
+        "# To find the correct answer using ground_state_hamiltonian\n",
+        "# and the parameter is a cost_hamiltonian\n",
+        "correct_solution = ground_state_hamiltonian(qaoa.cost_hamil)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "PC0-VZOUu1z9"
+      },
+      "source": [
+        "Validate your answer using docplex, you can see how to check the classical solution using the following tutorial [here](https://github.com/entropicalabs/openqaoa/blob/main/examples/community_tutorials/02_docplex_example.ipynb)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "YnC1X8SCu1z9",
+        "outputId": "4317e32e-898e-495d-b219-f3f15b7dcff8"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "objective: -3.000\n",
+            "status: OPTIMAL_SOLUTION(2)\n",
+            "  x_0=1\n",
+            "  x_1=1\n",
+            "  x_2=0\n",
+            "  x_3=0\n",
+            "  x_4=0\n"
+          ]
+        }
+      ],
+      "source": [
+        "## docplex solution\n",
+        "sol = mdl_qubo_docplex.solve()\n",
+        "mdl_qubo_docplex.print_solution(print_zeros=True)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "32b5dlcxu1z-"
+      },
+      "source": [
+        "## Part 2: Improve the QAOA circuit\n",
+        "\n",
+        "Perform the same process as above now with the variant of using different backends, p values, and different optimizers until you find the one that can provide the correct answers with the least number of iterations, quantum circuit depth."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 332
+        },
+        "id": "L6MEliaZu1z-",
+        "outputId": "1c85d436-e322-4927-d42e-5af2d12f20c6"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "\n",
+              "  <div id=\"df-94bf326e-503a-42eb-8d6e-46ee2c9e4291\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
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+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>solutions_bitstrings</th>\n",
+              "      <th>bitstrings_energies</th>\n",
+              "      <th>probabilities</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>10001</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>10100</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>11000</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.20</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>10010</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>00101</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>01100</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.15</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>00011</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7</th>\n",
+              "      <td>00110</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8</th>\n",
+              "      <td>01010</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.15</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-94bf326e-503a-42eb-8d6e-46ee2c9e4291')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
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+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-94bf326e-503a-42eb-8d6e-46ee2c9e4291 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-94bf326e-503a-42eb-8d6e-46ee2c9e4291');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-e9ac606f-1d4b-4470-badc-db1f1ac3a0bc\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e9ac606f-1d4b-4470-badc-db1f1ac3a0bc')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-e9ac606f-1d4b-4470-badc-db1f1ac3a0bc button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "text/plain": [
+              "  solutions_bitstrings  bitstrings_energies  probabilities\n",
+              "0                10001                 -3.0           0.05\n",
+              "1                10100                 -3.0           0.05\n",
+              "2                11000                 -3.0           0.20\n",
+              "3                10010                 -2.0           0.10\n",
+              "4                00101                 -2.0           0.10\n",
+              "5                01100                 -2.0           0.15\n",
+              "6                00011                 -1.0           0.05\n",
+              "7                00110                 -1.0           0.10\n",
+              "8                01010                 -1.0           0.15"
+            ]
+          },
+          "execution_count": 8,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "## Implementation\n",
+        "\n",
+        "# Initialize the QAOA object and use a device\n",
+        "device = create_device(\"local\", 'qiskit.qasm_simulator')\n",
+        "\n",
+        "qaoa = QAOA(device)\n",
+        "\n",
+        "# Set the parameters to work the QAOA algorithm\n",
+        "# play with the parameters values\n",
+        "qaoa.set_backend_properties(n_shots=20, seed_simulator=1)\n",
+        "qaoa.set_circuit_properties(p=2, init_type=\"custom\", variational_params_dict={\"betas\":2*[0.01*np.pi],\"gammas\":2*[0.01*np.pi]})\n",
+        "\n",
+        "qaoa.compile(ising_encoding)\n",
+        "\n",
+        "# Run the QAOA algorithm\n",
+        "qaoa.optimize()\n",
+        "\n",
+        "results = pd.DataFrame(qaoa.result.lowest_cost_bitstrings(10))\n",
+        "results = results[results[\"bitstrings_energies\"]<0]\n",
+        "results"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "HUMiQwQeu1z-"
+      },
+      "source": [
+        "## Part 3: Noise Model\n",
+        "\n",
+        "The optimal combination that you found with the best optimizer, the lowest number of $p$'s and the correct answer, can give the same answer with noise, use the circuit with a noise model and identify if it gives the same answer."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 332
+        },
+        "id": "YzQuaAAru1z_",
+        "outputId": "328e189a-9fdc-4d4a-b6c2-a675243e35b5"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
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+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>solutions_bitstrings</th>\n",
+              "      <th>bitstrings_energies</th>\n",
+              "      <th>probabilities</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
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+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>10001</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.05</td>\n",
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+              "      <th>1</th>\n",
+              "      <td>10100</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>11000</td>\n",
+              "      <td>-3.0</td>\n",
+              "      <td>0.20</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>10010</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>00101</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.10</td>\n",
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+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>01100</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>0.15</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>00011</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.05</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7</th>\n",
+              "      <td>00110</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.10</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8</th>\n",
+              "      <td>01010</td>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>0.15</td>\n",
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+              "    .colab-df-container {\n",
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+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
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+              "      height: 32px;\n",
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+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
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+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-d32ef79a-c6aa-4423-a7d7-c8442e73ac67 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-d32ef79a-c6aa-4423-a7d7-c8442e73ac67');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
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+              "<div id=\"df-0c3469a6-6eaa-4785-9fbf-2d18bed40ab3\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-0c3469a6-6eaa-4785-9fbf-2d18bed40ab3')\"\n",
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+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-0c3469a6-6eaa-4785-9fbf-2d18bed40ab3 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "text/plain": [
+              "  solutions_bitstrings  bitstrings_energies  probabilities\n",
+              "0                10001                 -3.0           0.05\n",
+              "1                10100                 -3.0           0.05\n",
+              "2                11000                 -3.0           0.20\n",
+              "3                10010                 -2.0           0.10\n",
+              "4                00101                 -2.0           0.10\n",
+              "5                01100                 -2.0           0.15\n",
+              "6                00011                 -1.0           0.05\n",
+              "7                00110                 -1.0           0.10\n",
+              "8                01010                 -1.0           0.15"
+            ]
+          },
+          "execution_count": 9,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "# implementation using a noise model using qiskit\n",
+        "\n",
+        "# initialize the QAOA object\n",
+        "q = QAOA()\n",
+        "\n",
+        "## real hardware\n",
+        "from qiskit.providers.fake_provider import FakeVigo\n",
+        "from qiskit.providers.aer.noise import NoiseModel\n",
+        "from qiskit.providers.aer import QasmSimulator\n",
+        "\n",
+        "\n",
+        "device = create_device(\"local\", 'qiskit.qasm_simulator')\n",
+        "# choose the noise model\n",
+        "device_backend = FakeVigo()\n",
+        "fake_device = QasmSimulator.from_backend(device_backend)\n",
+        "noise_model = NoiseModel.from_backend(fake_device)\n",
+        "\n",
+        "# set your device\n",
+        "q.set_device(device)\n",
+        "\n",
+        "# set the parameters to work the QAOA algorithm\n",
+        "q.set_backend_properties(n_shots = 200, noise_model = noise_model)\n",
+        "\n",
+        "q.compile(ising_encoding)\n",
+        "\n",
+        "# run the QAOA algorithm\n",
+        "q.optimize()\n",
+        "\n",
+        "results = pd.DataFrame(qaoa.result.lowest_cost_bitstrings(10))\n",
+        "results = results[results[\"bitstrings_energies\"]<0]\n",
+        "results"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "HyT33WK9u1z_"
+      },
+      "source": [
+        "# Acknowledgments\n",
+        "\n",
+        "🎉🎉🎉\n",
+        "\n",
+        "Special thanks to Entropica Labs for helping us create this challenge and being able to use their SDK, OpenQAOA. If you want to know more about OpenQAOA or ask them questions directly, check out their [discord channel](discord.gg/ana76wkKBd).\n",
+        "\n",
+        "🎉🎉🎉"
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "mitiq-qaoa",
+      "language": "python",
+      "name": "mitiq-qaoa"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.8.8"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
diff --git a/hackathon/QuantumVoyagers/Q_BattleShip_2.ipynb b/hackathon/QuantumVoyagers/Q_BattleShip_2.ipynb
new file mode 100644
index 0000000..bdd0071
--- /dev/null
+++ b/hackathon/QuantumVoyagers/Q_BattleShip_2.ipynb
@@ -0,0 +1,789 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Código"
+      ],
+      "metadata": {
+        "id": "YooIMoDE5cp1"
+      },
+      "id": "YooIMoDE5cp1"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "FyCBkHkDom6j",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "2f16b82c-e091-4e08-99f3-d5721a14a3a5"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.3/6.3 MB\u001b[0m \u001b[31m39.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m76.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.6/49.6 kB\u001b[0m \u001b[31m4.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m115.3/115.3 kB\u001b[0m \u001b[31m11.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.6/49.6 kB\u001b[0m \u001b[31m5.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m37.5/37.5 MB\u001b[0m \u001b[31m31.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m107.5/107.5 kB\u001b[0m \u001b[31m9.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25h"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install qiskit --quiet"
+      ],
+      "id": "FyCBkHkDom6j"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Yv2p1wdao9Xv",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "92f60958-1b53-4dbd-d13d-c5b9eabe4428"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/162.6 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m41.0/162.6 kB\u001b[0m \u001b[31m963.8 kB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━\u001b[0m \u001b[32m153.6/162.6 kB\u001b[0m \u001b[31m2.3 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m162.6/162.6 kB\u001b[0m \u001b[31m1.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Building wheel for pylatexenc (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m12.3/12.3 MB\u001b[0m \u001b[31m77.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25h"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install pylatexenc --quiet\n",
+        "!pip install -U qiskit-aer --quiet"
+      ],
+      "id": "Yv2p1wdao9Xv"
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Importación de paquetes"
+      ],
+      "metadata": {
+        "id": "lqVHgBZg5b2Q"
+      },
+      "id": "lqVHgBZg5b2Q"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "a56a63b5"
+      },
+      "outputs": [],
+      "source": [
+        "from qiskit import *\n",
+        "from qiskit.visualization import plot_histogram\n",
+        "\n",
+        "from qiskit.quantum_info import Statevector\n",
+        "from qiskit.visualization import array_to_latex, plot_bloch_multivector\n",
+        "from qiskit.extensions import UnitaryGate\n",
+        "\n",
+        "from qiskit.providers.aer import AerSimulator\n",
+        "from qiskit.providers.fake_provider import FakeYorktown\n",
+        "\n",
+        "from qiskit import execute, Aer\n",
+        "\n",
+        "from qiskit import transpile"
+      ],
+      "id": "a56a63b5"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "L8vacay5pz_-"
+      },
+      "outputs": [],
+      "source": [
+        "import numpy as np\n",
+        "import math\n",
+        "import matplotlib.pyplot as plt\n",
+        "\n",
+        "import getpass\n",
+        "\n",
+        "import random\n",
+        "import re"
+      ],
+      "id": "L8vacay5pz_-"
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Declaración de variables iniciales"
+      ],
+      "metadata": {
+        "id": "J8EA8Quj7QSe"
+      },
+      "id": "J8EA8Quj7QSe"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "DyuWyqKo7Blv"
+      },
+      "outputs": [],
+      "source": [
+        "n = 4\n",
+        "tablero1 = np.empty([n, n], dtype=\"<U1000\")\n",
+        "tablero2 = np.empty([n, n], dtype=\"<U1000\")\n",
+        "k=1\n",
+        "for i in range(n):\n",
+        "    for j in range(n):\n",
+        "        tablero1[i][j] = str(k)\n",
+        "        tablero2[i][j] = str(k)\n",
+        "        k+=1\n",
+        "\n",
+        "barcos1 = np.empty([n], dtype=\"<U1000\")\n",
+        "barcos2 = np.empty([n], dtype=\"<U1000\")\n",
+        "\n",
+        "hits1 = np.empty([100], dtype=\"<U1000\")\n",
+        "hits2 = np.empty([100], dtype=\"<U1000\")"
+      ],
+      "id": "DyuWyqKo7Blv"
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Main"
+      ],
+      "metadata": {
+        "id": "lwpPVQW97SZP"
+      },
+      "id": "lwpPVQW97SZP"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "6e72126d"
+      },
+      "outputs": [],
+      "source": [
+        "j1=n\n",
+        "j2=n\n",
+        "\n",
+        "turn=0\n",
+        "\n",
+        "Cj2 = True\n",
+        "Cj1 = True\n",
+        "\n",
+        "def home():\n",
+        "    print(\" 🔱🔱🔱 QuantumNaval 🔱🔱🔱\\n\")\n",
+        "    print(\"🚨 Posicionen sus barcos 🚨\\n\")\n",
+        "\n",
+        "    escoger(1,barcos1)\n",
+        "    print(\"⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓\\n\")\n",
+        "\n",
+        "    escoger(2,barcos2)\n",
+        "    print(\"⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓\\n\")\n",
+        "\n",
+        "    bol = True\n",
+        "\n",
+        "    while (bol):\n",
+        "        jugada(2,1,barcos1,tablero1)\n",
+        "        jugada(1,2,barcos2,tablero2)\n",
+        "        print(\"🔱 JUGADOR \"+str(1)+\"  |   \"+ \"🔱 JUGADOR \"+str(2))\n",
+        "        print(\" 🚩 Puntaje 🚩\")\n",
+        "        print(\"  \"+str(n-j2)+\"           |      \"+str(n-j1))\n",
+        "        print(\" 🚢 Barcos 🚢\")\n",
+        "        print(\"  \"+str(j1)+\"           |      \"+str(j2))\n",
+        "        print(\"\\n⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓\\n\")\n",
+        "        if(j1==0):\n",
+        "            bol=False\n",
+        "        if(j2==0):\n",
+        "            bol=False\n",
+        "        global turn\n",
+        "        turn+=1\n",
+        "\n",
+        "def escoger(s, barcos):\n",
+        "    print(\"¡Jugador \"+str(s)+\" selecciona tus 4 barcos!\")\n",
+        "    for i in range(4):\n",
+        "        # Validar que sean números enteros\n",
+        "        while True:\n",
+        "          barcos[i]=getpass.getpass(prompt =\" ⚓ Ingresa la posición del barco 🚢\"+str(i+1)+\"\\n\")\n",
+        "          userAnswer = barcos[i]\n",
+        "          try:\n",
+        "            val = int(userAnswer)\n",
+        "            break\n",
+        "          except ValueError:\n",
+        "            print(\"🚨🚨🚨 Ingrese solo números enteros 🚨🚨🚨\")\n",
+        "\n",
+        "    return barcos\n",
+        "\n",
+        "def jugada(jugadorA, jugadorB, barcos,tablero):\n",
+        "    t = input(\"🔱 Jugador \"+str(jugadorA)+\" Ingresa una posición para atacar al jugador \"+str(jugadorB)+\"\\n\")\n",
+        "\n",
+        "    hits = np.empty([100], dtype=\"<U1000\")\n",
+        "    if jugadorA==1:\n",
+        "      hits=hits1\n",
+        "    if jugadorA==2:\n",
+        "      hits=hits2\n",
+        "\n",
+        "####### JUGADA CUÁNTICA #######\n",
+        "    if (\"Q\") in t:\n",
+        "\n",
+        "        t=re.sub(r'[a-zA-Z]', '', t)\n",
+        "        print(\" 🔱 JUGADA CUANTICA 🔱 \")\n",
+        "        QQ=Qtarget_()\n",
+        "        print(\"Resultado: 👉 \"+str(QQ))\n",
+        "        if (QQ):\n",
+        "\n",
+        "            ataque(t,barcos,tablero,jugadorA,hits)\n",
+        "\n",
+        "            print(\"🟣🔱ATAQUE CUÁNTICO 🔱🟣\")\n",
+        "\n",
+        "            hitsnew=np.setdiff1d(hits,[''])\n",
+        "            hits=[int(numeric_string) for numeric_string in hitsnew]\n",
+        "\n",
+        "            Qtarget = Qtarget_n(4)\n",
+        "            for i in range(len(hits)):\n",
+        "                if hits[i] in Qtarget:\n",
+        "                    Qtarget.remove(hits[i])\n",
+        "\n",
+        "            t_=random.choice(Qtarget)\n",
+        "            global turn\n",
+        "            turn+=1\n",
+        "            if jugadorA==1:\n",
+        "                hits1[turn] = t_\n",
+        "            if jugadorA==2:\n",
+        "                hits2[turn] = t_\n",
+        "\n",
+        "            ataque(t_,barcos,tablero,jugadorA,hits)\n",
+        "        else:\n",
+        "          print(\"🟣 FAIL CUÁNTICO 🟣\\n\")\n",
+        "\n",
+        "####### TUNELAMIENTO #######\n",
+        "    elif (\"T:\") in t:\n",
+        "      print(t,\"type:\",type(t))\n",
+        "      split_values = t.split(':')\n",
+        "      posA = split_values[1].split(',')[1]\n",
+        "      barcoB = split_values[1].split(',')[0]\n",
+        "\n",
+        "      print(\" 🔱 TUNELAMIENTO 🔱 \")\n",
+        "\n",
+        "      def actu_barcos(jA,barcos):\n",
+        "        if jugadorA==2:\n",
+        "          global barcos1\n",
+        "          barcos1 = barcos\n",
+        "        if jugadorA==1:\n",
+        "          global barcos2\n",
+        "          barcos2 = barcos\n",
+        "\n",
+        "      def n2coord(number, matrix_size=n):\n",
+        "        if 1 <= number <= matrix_size**2:\n",
+        "            row = (number - 1) // matrix_size\n",
+        "            col = (number - 1) % matrix_size\n",
+        "            return row, col\n",
+        "\n",
+        "      Tun_res = tuneling_attack(n2coord(int(barcoB)),tablero,barcos)\n",
+        "      ataque(barcoB,barcos,tablero,jugadorA,hits)\n",
+        "      barcos = np.delete(barcos, np.where(barcos == barcoB))\n",
+        "\n",
+        "      if jugadorA==2:\n",
+        "        if Tun_res[0] is not None:\n",
+        "          global j2\n",
+        "          j2+=1\n",
+        "          global barcos2\n",
+        "          barcos2 = np.append(barcos2, barcoB)\n",
+        "          actu_barcos(jugadorA,barcos)\n",
+        "      if jugadorA==1:\n",
+        "        if Tun_res[0] is not None:\n",
+        "          global j1\n",
+        "          j1+=1\n",
+        "          global barcos1\n",
+        "          barcos1 = np.append(barcos1, barcoB)\n",
+        "          actu_barcos(jugadorA,barcos)\n",
+        "\n",
+        "####### COPENAGEN #######\n",
+        "    elif (\"C\") in t:\n",
+        "      global Cj1\n",
+        "      global Cj2\n",
+        "      if (jugadorA==1 and Cj1 == True) or (jugadorA==2 and Cj2 == True):\n",
+        "        print(\" 🔱 COPENHAGEN 🔱 \")\n",
+        "        if jugadorA==2:\n",
+        "          L_watch = copenhague_attack(tablero1)\n",
+        "          barcos = barcos1\n",
+        "        if jugadorA==1:\n",
+        "          L_watch = copenhague_attack(tablero2)\n",
+        "          barcos = barcos2\n",
+        "\n",
+        "        def coordenadas(i, j):\n",
+        "        # Convertir los índices a un número binario de 4 bits\n",
+        "          bin_index = format(4*i + j, '04b')\n",
+        "          qc = QuantumCircuit(4, 4)\n",
+        "\n",
+        "          for qubit in range(4):\n",
+        "              if bin_index[3-qubit] == '1':  #el 3-qubit aquí es para invertir el orden de los qubits\n",
+        "                  qc.x(qubit)\n",
+        "          qc.measure(range(4), range(4))\n",
+        "          result = execute(qc, Aer.get_backend('qasm_simulator')).result()\n",
+        "          counts = result.get_counts(qc)\n",
+        "\n",
+        "          for state in counts:\n",
+        "              return int(state, 2) + 1\n",
+        "\n",
+        "        r_watch = []\n",
+        "        for tup in L_watch:\n",
+        "          result = coordenadas(tup[0], tup[1])\n",
+        "          r_watch.append(str(result))\n",
+        "\n",
+        "        common_ = [num for num in r_watch if num in barcos]\n",
+        "\n",
+        "        for i in common_:\n",
+        "          comparar(i, tablero, \"🔵\", \"👀 BARCO 🛳️\\n\")\n",
+        "\n",
+        "        if (len(common_) !=0):\n",
+        "          if jugadorA==2:\n",
+        "            Cj2 = False\n",
+        "          if jugadorA==1:\n",
+        "            Cj1 = False\n",
+        "        else:\n",
+        "          print(\"🟣 FAIL CUÁNTICO 🟣\\n\")\n",
+        "\n",
+        "      else:\n",
+        "        print(\" 🔱 COPENHAGEN 🔱 solo se puede usar una vez\\n\")\n",
+        "    else:\n",
+        "        #JUGADA NORMAL\n",
+        "        ataque(t,barcos,tablero,jugadorA,hits)\n",
+        "\n",
+        "    print(\"🏴🏳️🏴🏳️Tablero del jugador \"+str(jugadorB)+\"🏴🏳️🏴🏳️\")\n",
+        "    imprimir(tablero)\n",
+        "    print(\"\")\n",
+        "\n",
+        "    #print(\"barcos1: \", barcos1)\n",
+        "    #print(\"barcos2: \", barcos2)\n",
+        "\n",
+        "def ataque(t,barcos,tablero,jugadorA,hits):\n",
+        "    #print(\"ATAQUE/\",\"t: \",t, \"jugadorA: \", jugadorA, \"hits: \", hits)\n",
+        "\n",
+        "    bol_at = True # Asegura que al atacar al mismo barco no sume puntos\n",
+        "    #l = len([s for s in hits if s])\n",
+        "    #print(\"l: \",l)\n",
+        "    if(t in hits):\n",
+        "        bol_at = False\n",
+        "    #print(\"bol_at: \",bol_at)\n",
+        "\n",
+        "    hits = np.empty([100], dtype=\"<U1000\")\n",
+        "    if jugadorA==1:\n",
+        "        hits1[turn] = t\n",
+        "        #print(\"ATAQUE/ hits1: \",hits1)\n",
+        "    if jugadorA==2:\n",
+        "        hits2[turn] = t\n",
+        "        #print(\"ATAQUE/ hits2: \", hits2)\n",
+        "\n",
+        "    if((t==barcos[0] or t==barcos[1] or t==barcos[2] or t==barcos[3]) and (bol_at)):\n",
+        "        comparar(t, tablero, \"🟢\", \"💥 HIT 💥\\n\")\n",
+        "        if jugadorA==1:\n",
+        "            global j2\n",
+        "            #j1+=1\n",
+        "            j2-=1\n",
+        "        if jugadorA==2:\n",
+        "            global j1\n",
+        "            #j2+=1\n",
+        "            j1-=1\n",
+        "    else:\n",
+        "        comparar(t, tablero, \"🔴\", \"🕳️ FAIL 🕳️\\n\")\n",
+        "\n",
+        "def comparar(t, tablero, accion, output):\n",
+        "  # Marca el tablero con 'accion' en el número 't' e imprime en pantalla 'output'\n",
+        "    x=-1\n",
+        "    y=-1\n",
+        "    for i in range(4):\n",
+        "        for j in range(4):\n",
+        "            if (t==tablero[i][j]):\n",
+        "                y=j\n",
+        "                x=i\n",
+        "                break\n",
+        "            else:\n",
+        "                continue\n",
+        "    if (x!=-1 and y!=-1):\n",
+        "        tablero[x][y] = accion\n",
+        "    print(output)\n",
+        "    #return tablero\n",
+        "\n",
+        "def imprimir(tab):\n",
+        "    for i in range(4):\n",
+        "        for j in range(4):\n",
+        "          print(\" ⚜️  \"+tab[i][j],end=\"  \")\n",
+        "          if (j == 3):\n",
+        "            print(\" ⚜️ \")\n",
+        "        print(\"〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\")"
+      ],
+      "id": "6e72126d"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "11SnTICs78jX"
+      },
+      "outputs": [],
+      "source": [
+        "# Ataque tunelamiento\n",
+        "\n",
+        "def tuneling_attack(casilla_robo, tableroB,barcosB):\n",
+        "    # Crea un circuito cuántico con 3 qubits\n",
+        "    circ = QuantumCircuit(3)\n",
+        "    # Aplica una puerta X al primer qubit si la casilla de intercambio es un barco\n",
+        "    print(\"Inputs: \",tableroB[casilla_robo], barcosB)\n",
+        "    if tableroB[casilla_robo] in barcosB:\n",
+        "        print(\"🟣🔱BARCO TUNELADO 🔱🟣\")\n",
+        "        circ.x(0)\n",
+        "        # Aplica una puerta de Hadamard al segundo qubit\n",
+        "        circ.h(1)\n",
+        "        # Aplica puertas CNOT con el segundo y primer qubit como control y el tercer qubit como objetivo\n",
+        "        circ.cx(1, 2)\n",
+        "        circ.cx(0, 1)\n",
+        "        circ.h(0)\n",
+        "        # Ejecuta el circuito en el simulador de estado de vectores\n",
+        "        result = execute(circ, Aer.get_backend('statevector_simulator')).result()\n",
+        "        # Obtiene el estado final del circuito\n",
+        "        state = result.get_statevector(circ)\n",
+        "        return state, tableroB\n",
+        "    else:\n",
+        "        print(\"🟣 FAIL CUÁNTICO 🟣\\n\")\n",
+        "        return None, tableroB"
+      ],
+      "id": "11SnTICs78jX"
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Copenhague attack\n",
+        "def copenhague_attack(tablero_oponente):\n",
+        "    num_q = len(tablero_oponente.flatten())\n",
+        "    circ = QuantumCircuit(num_q)\n",
+        "    for i in range(num_q):\n",
+        "        circ.h(i)\n",
+        "\n",
+        "    # Aplica la operación de oráculo\n",
+        "    for i in range(num_q):\n",
+        "        if (tablero_oponente.flatten()[i] == 'barco'):\n",
+        "            circ.x(i)\n",
+        "    circ.h(num_q - 1)\n",
+        "    circ.mcx(list(range(num_q - 1)), num_q - 1)  #compuerta multicontrolada x\n",
+        "    circ.h(num_q - 1)\n",
+        "    for i in range(num_q):\n",
+        "        if (tablero_oponente.flatten()[i] == 'barco'):\n",
+        "            circ.x(i)\n",
+        "\n",
+        "    # Aplica la operación de difusión\n",
+        "    for qubit in range(num_q):\n",
+        "        circ.h(qubit)\n",
+        "    for qubit in range(num_q):\n",
+        "        circ.x(qubit)\n",
+        "    circ.h(num_q - 1)\n",
+        "    circ.mcx(list(range(num_q - 1)), num_q - 1)  #compuerta multicontrolada x\n",
+        "    circ.h(num_q - 1)\n",
+        "    for qubit in range(num_q):\n",
+        "        circ.x(qubit)\n",
+        "    for qubit in range(num_q):\n",
+        "        circ.h(qubit)\n",
+        "\n",
+        "    res = execute(circ, Aer.get_backend('statevector_simulator')).result()\n",
+        "    estado = res.get_statevector(circ)\n",
+        "    estado = np.asarray(estado)\n",
+        "\n",
+        "    #calcula las probabilidades de cada estado\n",
+        "    probabilidades = [abs(amplitude)**2 for amplitude in estado]\n",
+        "\n",
+        "    #ordena las casillas del tablero por probabilidad\n",
+        "    casillas_ordenadas = sorted(range(num_q), key=lambda i: probabilidades[i], reverse=True)\n",
+        "\n",
+        "    #estima las posiciones de los barcos del oponente\n",
+        "    estimacion = set()\n",
+        "    while len(estimacion) < 3:  #asume que hay 4 barcos, el valor se lo puede cambiar por la cantidad de barcos deseada\n",
+        "        estimacion.add(random.choice(casillas_ordenadas[:num_q//2]))\n",
+        "\n",
+        "    #convierte los índices a coordenadas\n",
+        "    estimacion_coordenadas = [(i//4, i%4) for i in estimacion]\n",
+        "\n",
+        "    #devuelve las posiciones estimadas de los barcos, arroja el número de posiciones como de barcos se estime en el tablero\n",
+        "    return estimacion_coordenadas"
+      ],
+      "metadata": {
+        "id": "TXYvCDGNfNV0"
+      },
+      "id": "TXYvCDGNfNV0",
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "0f2d64ac"
+      },
+      "source": [
+        "Generador de números aleatorios (1-16)"
+      ],
+      "id": "0f2d64ac"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "846545da"
+      },
+      "outputs": [],
+      "source": [
+        "def bin2dec(bin_):\n",
+        "    decimal = 0\n",
+        "    for digit in bin_:\n",
+        "        decimal = decimal*2 + int(digit)\n",
+        "    return decimal"
+      ],
+      "id": "846545da"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "38177bd5",
+        "scrolled": true
+      },
+      "outputs": [],
+      "source": [
+        "def Qtarget_n(n):\n",
+        "    device_backend = FakeYorktown()\n",
+        "    sim_yorktown = AerSimulator.from_backend(device_backend)\n",
+        "    N_QUBITS = n\n",
+        "    circ = QuantumCircuit(N_QUBITS, N_QUBITS)\n",
+        "    circ.h(0)\n",
+        "    for idx in range(N_QUBITS - 1):\n",
+        "        circ.cx(idx, idx + 1)\n",
+        "    circ.measure_all()\n",
+        "    #circ.draw('mpl')\n",
+        "\n",
+        "    tcirc = transpile(circ, sim_yorktown)\n",
+        "    result_noise = sim_yorktown.run(tcirc, shots=1024).result()\n",
+        "    counts_noise = result_noise.get_counts(0)\n",
+        "    #print(counts_noise)\n",
+        "    lcounts=list(counts_noise.keys())\n",
+        "    #print(lcounts)\n",
+        "    for i in range(len(lcounts)):\n",
+        "        lcounts[i]=str(bin2dec(lcounts[i].replace(\" 0000\",\"\"))+1) # se suma 1 para que los valores vayan desde 0+1 hasta 15+1\n",
+        "    #print(lcounts)\n",
+        "    #return(lcounts[0:4])\n",
+        "    return(lcounts)"
+      ],
+      "id": "38177bd5"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "b68d972a"
+      },
+      "source": [
+        "Generador números aleatorios (0-1)"
+      ],
+      "id": "b68d972a"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "6bf96889"
+      },
+      "outputs": [],
+      "source": [
+        "def Qtarget_():\n",
+        "    circ_ghz = QuantumCircuit(3, 3)     # circuito con 3 qubits y 3 bits clásicos\n",
+        "    circ_ghz.h(0)                       # aplicar compuerta H al qubit 0\n",
+        "    circ_ghz.cx(0, 1)                   # aplicar compuerta CNOT a los qubits 0 y 1\n",
+        "    circ_ghz.cx(0, 2)                   # aplicar compuerta CNOT a los qubits 0 y 2\n",
+        "    circ_ghz.barrier()\n",
+        "    circ_ghz.measure([0,1,2], [0,1,2])  # medir los 3 qubits en los 3 bits clásicos\n",
+        "\n",
+        "    #circ_ghz.draw('mpl')                # mostrar el circuito\n",
+        "\n",
+        "    simulator = Aer.get_backend('aer_simulator')\n",
+        "\n",
+        "    job = execute(circ_ghz, simulator, shots=1)               # ejecutar el circuito una sola vez\n",
+        "    counts = job.result().get_counts(circ_ghz)                # obtener los resultados de la ejecución\n",
+        "    #print(counts)\n",
+        "    r=23\n",
+        "    if '1' in list(counts.keys())[0]:\n",
+        "        r=1\n",
+        "    else:\n",
+        "        r=0\n",
+        "    #print(\"r=\",r)\n",
+        "    return r"
+      ],
+      "id": "6bf96889"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "fac7fe17"
+      },
+      "source": [
+        "# Inicio Juego"
+      ],
+      "id": "fac7fe17"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "iXf0IT9P7Ygq",
+        "scrolled": false,
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "d7107af5-b72b-45a2-b75f-e3d81eb69b74"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            " 🔱🔱🔱 QuantumNaval 🔱🔱🔱\n",
+            "\n",
+            "🚨 Posicionen sus barcos 🚨\n",
+            "\n",
+            "¡Jugador 1 selecciona tus 4 barcos!\n",
+            " ⚓ Ingresa la posición del barco 🚢1\n",
+            "··········\n",
+            " ⚓ Ingresa la posición del barco 🚢2\n",
+            "··········\n",
+            " ⚓ Ingresa la posición del barco 🚢3\n",
+            "··········\n",
+            " ⚓ Ingresa la posición del barco 🚢4\n",
+            "··········\n",
+            "⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓\n",
+            "\n",
+            "¡Jugador 2 selecciona tus 4 barcos!\n",
+            " ⚓ Ingresa la posición del barco 🚢1\n",
+            "··········\n",
+            " ⚓ Ingresa la posición del barco 🚢2\n",
+            "··········\n",
+            " ⚓ Ingresa la posición del barco 🚢3\n",
+            "··········\n",
+            " ⚓ Ingresa la posición del barco 🚢4\n",
+            "··········\n",
+            "⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓\n",
+            "\n",
+            "🔱 Jugador 2 Ingresa una posición para atacar al jugador 1\n",
+            "4\n",
+            "💥 HIT 💥\n",
+            "\n",
+            "🏴🏳️🏴🏳️Tablero del jugador 1🏴🏳️🏴🏳️\n",
+            " ⚜️  1   ⚜️  2   ⚜️  3   ⚜️  🟢   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            " ⚜️  5   ⚜️  6   ⚜️  7   ⚜️  8   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            " ⚜️  9   ⚜️  10   ⚜️  11   ⚜️  12   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            " ⚜️  13   ⚜️  14   ⚜️  15   ⚜️  16   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            "\n",
+            "🔱 Jugador 1 Ingresa una posición para atacar al jugador 2\n",
+            "2\n",
+            "💥 HIT 💥\n",
+            "\n",
+            "🏴🏳️🏴🏳️Tablero del jugador 2🏴🏳️🏴🏳️\n",
+            " ⚜️  1   ⚜️  🟢   ⚜️  3   ⚜️  4   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            " ⚜️  5   ⚜️  6   ⚜️  7   ⚜️  8   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            " ⚜️  9   ⚜️  10   ⚜️  11   ⚜️  12   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            " ⚜️  13   ⚜️  14   ⚜️  15   ⚜️  16   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            "\n",
+            "🔱 JUGADOR 1  |   🔱 JUGADOR 2\n",
+            " 🚩 Puntaje 🚩\n",
+            "  1           |      1\n",
+            " 🚢 Barcos 🚢\n",
+            "  3           |      3\n",
+            "\n",
+            "⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓\n",
+            "\n",
+            "🔱 Jugador 2 Ingresa una posición para atacar al jugador 1\n",
+            "8\n",
+            "🕳️ FAIL 🕳️\n",
+            "\n",
+            "🏴🏳️🏴🏳️Tablero del jugador 1🏴🏳️🏴🏳️\n",
+            " ⚜️  1   ⚜️  2   ⚜️  3   ⚜️  🟢   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            " ⚜️  5   ⚜️  6   ⚜️  7   ⚜️  🔴   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            " ⚜️  9   ⚜️  10   ⚜️  11   ⚜️  12   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            " ⚜️  13   ⚜️  14   ⚜️  15   ⚜️  16   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            "\n",
+            "🔱 Jugador 1 Ingresa una posición para atacar al jugador 2\n",
+            "1\n",
+            "🕳️ FAIL 🕳️\n",
+            "\n",
+            "🏴🏳️🏴🏳️Tablero del jugador 2🏴🏳️🏴🏳️\n",
+            " ⚜️  🔴   ⚜️  🟢   ⚜️  3   ⚜️  4   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            " ⚜️  5   ⚜️  6   ⚜️  7   ⚜️  8   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            " ⚜️  9   ⚜️  10   ⚜️  11   ⚜️  12   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            " ⚜️  13   ⚜️  14   ⚜️  15   ⚜️  16   ⚜️ \n",
+            "〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️\n",
+            "\n",
+            "🔱 JUGADOR 1  |   🔱 JUGADOR 2\n",
+            " 🚩 Puntaje 🚩\n",
+            "  1           |      1\n",
+            " 🚢 Barcos 🚢\n",
+            "  3           |      3\n",
+            "\n",
+            "⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓⚓\n",
+            "\n"
+          ]
+        }
+      ],
+      "source": [
+        "home()"
+      ],
+      "id": "iXf0IT9P7Ygq"
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.10.4"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 5
+}
\ No newline at end of file
diff --git a/hackathon/QuantumVoyagers/Q_BattleShip_2.ipynb:Zone.Identifier b/hackathon/QuantumVoyagers/Q_BattleShip_2.ipynb:Zone.Identifier
new file mode 100644
index 0000000..053d112
--- /dev/null
+++ b/hackathon/QuantumVoyagers/Q_BattleShip_2.ipynb:Zone.Identifier
@@ -0,0 +1,3 @@
+[ZoneTransfer]
+ZoneId=3
+HostUrl=about:internet