moodys_challenge.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "de7fe4be-dd2d-4d8c-9358-5ab6a636496e",
   "metadata": {},
   "source": [
    "# Quantum Machine Learning for detecting financial crashes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c89cba0-4047-4b23-b949-baa20f67fae5",
   "metadata": {},
   "source": [
    "### Learning objectives of the challenge"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7fb51a43-6f42-4077-a894-38c874c61721",
   "metadata": {},
   "source": [
    "**1.** How to use classical topological data analysis, TDA, for financial bubble early warning? <br>\n",
    "**2.** How to implement its quantum counterpart? <br>\n",
    "**3.** Conduct a resource analysis on the quantum algorithm. Which step is most costly? <br>\n",
    "**4.** Get used to Quantum Phase Estimation, QPE. <br>\n",
    "**5.** How is the influence of the classical noise (the random fluctuations in financial markets)? <br>\n",
    "**6.** How is the influence of quantum noise? <br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85d339f8-0a2d-4c84-88d2-ae2f5d7e7597",
   "metadata": {},
   "source": [
    "## The challenge"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddf18fd5",
   "metadata": {},
   "source": [
    "### Main idea\n",
    "\n",
    "Topological Data Analysis (TDA) is a robust and innovative technique that has demonstrated impressive results in detecting financial crashes—critical transitions between financial regimes—and providing early warning signals. By analyzing changes in Betti numbers, TDA can reveal shifts in underlying structures that precede these transitions. In this notebook, we employ a quantum TDA algorithm to calculate Betti numbers, enabling effective early detection of financial crashes.\n",
    "\n",
    "### What is topological data analysis\n",
    "\n",
    "Topology studies the properties of geometric objects that are preserved under continuous deformations, such as stretching, twisting, crumpling, and bending. Homology serves as a tool to study and quantify the topological properties of spaces. The homology of an object is often summarized using $k$-th Betti numbers, which count the number of $k$-dimensional holes within the object. For example, the zeroth Betti number, $\\beta_0$, counts the number of connected components; the first Betti number, $\\beta_1$, counts the number of loops; and the second Betti number, $\\beta_2$, counts the number of enclosed volumes, and so on.\n",
    "\n",
    "In finance, input data is typically represented as time series, which are subsequently transformed into a series of discrete points. To model the underlying structure with them, we construct a simplicial complex (specifically, a Vietoris–Rips complex), a collection of simple shapes that connect the points together. Those simple shapes are called simplex, and they are generalization of the notion of a triangle or tetrahedron to arbitrary dimensions. A $k$-simplex is a collection of $k + 1$ vertices with $k(k + 1)/2$ edges in $k$ dimensions. A resolution threshold, $\\epsilon$, is chosen so that any two points within $\\epsilon$ distance of each other are connected by a line segment in the simplicial complex. As $\\epsilon$ increases, more connections are added, and lower-order components may merge into higher-order components. This results in a decrease in the lower-order Betti numbers and an increase in the higher-order Betti numbers. The study of how topological properties change across a sequence of resolution thresholds is called persistent homology.\n",
    "\n",
    "<img 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\" alt=\"Description of the figure\" style=\"max-width:50%; height:auto; display: block; margin: auto;\">\n",
    "\n",
    "For example, consider the figure above, which consists of five points. When $\\epsilon$ is small, no lines connect the points. Consequently, $\\beta_0 = 5$, as there are five discrete points, each representing an independent connected component, and no higher-dimensional features are present. As $\\epsilon$ increases, the Betti numbers for the configuration on the right become:\n",
    "\n",
    "* $\\beta_0=2$: There are two connected components (a line segment and a triangle).\n",
    "* $\\beta_1=1$: There is one 1-dimensional hole (the triangle encloses a region).\n",
    "* $\\beta_k=0$ for $k\\ge2$: No higher-dimensional features exist.\n",
    "\n",
    "This example also illustrates how Betti numbers change with the resolution threshold. The sequence of Betti numbers as the resolution threshold varies forms a curve known as the Betti curve. This curve can be utilized as input for kernel construction in machine learning applications.\n",
    "\n",
    "### What is quantum TDA?\n",
    "\n",
    "TDA can be used for extracting complex and valuable shape-related summaries of high-dimensional data. However, as the size of the dataset grows, the number of simplices considered increases significantly, leading to an exponential rise in the computational complexity of TDA algorithms ([ref](https://quantum-journal.org/papers/q-2022-11-10-855/)). \n",
    "\n",
    "Quantum computers have the potential to significantly accelerate TDA algorithms. Lloyd et al. introduced a fully quantum TDA algorithm leveraging quantum random access memory (qRAM), Grover's search algorithm, and quantum phase estimation (QPE) ([ref](https://www.nature.com/articles/ncomms10138)). In this approach, classical data is first loaded and encoded into the quantum amplitudes of a quantum state via qRAM. Grover's algorithm is then employed to construct the simplex state, with a membership function used to determine whether a given simplex belongs to the complex. Finally, the combinatorial Laplacian (also referred to as the \"Dirac operator\") is constructed, and the Betti numbers—key topological invariants—are extracted using QPE. \n",
    "\n",
    "However, this quantum TDA algorithm is really costly for NISQ computers. Even more, the qRAM requires long-lasting quantum coherence and low computational error to store and process the loaded data. Several exciting alternatives approaches have been proposed since then. It must be noted that quantum TDA is one of the first quantum machine learning algorithms with short depth and potential significant speedup under certain assumptions.\n",
    "\n",
    "Here is a list of different versions of quantum TDA. Note that they may be beyond the scope of this challenge, and mainly for your interest:\n",
    "\n",
    "* [QTDA via the estimation of the density of states (December 2023, University of Exeter)](https://arxiv.org/abs/2312.07115)\n",
    "* [NISQ-TDA  (Sep 2022, IBM Research + University of the Witwatersrand)](https://arxiv.org/pdf/2209.09371)\n",
    "* [Quantum persistent homology (Nov 2022, University of Tennessee)](https://arxiv.org/abs/2211.04465)\n",
    "* [Hybrid qTDA (Oct 2022, Deloitte)](https://arxiv.org/abs/2209.10596)\n",
    "* [Quantum-Enhanced TDA (Feb 2023, Tata Consultancy Services)](https://arxiv.org/pdf/2302.09553)\n",
    "\n",
    "### Does TDA have applications in finance?\n",
    "\n",
    "Betti numbers offer valuable insights into the structure and shape of complex data. While their use in finance is still in its early stages, they show promise in various applications, such as credit risk prediction ([ref](https://ora.ox.ac.uk/objects/uuid:9f4bed48-1763-486f-acbe-393670fab6bb/files/skw52j939s)), fraud detection, financial bubble detection ([ref](https://arxiv.org/abs/2304.06877)), capturing financial instability ([ref](https://arxiv.org/pdf/2110.00098)), etc. It can also be used as an unsupervised learning algorithm for anomaly detection.\n",
    "\n",
    "Several studies suggest that Betti numbers serve as effective indicators of market crashes. The zeroth betti number $\\beta_0$ is small at the beginning of a market crash and increases as the market crash progresses. It can be interpreted as that there is a giant connected component in the market just before the crash, and as the market crashed, this broke up into many smaller components ([ref](https://www.mdpi.com/1099-4300/23/9/1211), [ref](https://www.frontiersin.org/journals/physics/articles/10.3389/fphy.2021.572216/full)). \n",
    "\n",
    "This concept serves as the foundation for the idea behind this challenge."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d128bf0",
   "metadata": {},
   "source": [
    "## Problem Statement - Detecting financial bubbles by using quantum topological data analysis (qTDA)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfe38b05-e39a-4d01-a1d6-b6fafcec3db3",
   "metadata": {},
   "source": [
    "The goal of this challenge is to build a quantum TDA pipeline for detecting financial market crashes. The process is outlined in the following key steps, with detailed instructions provided below. Follow the **Instructions** and **Action** parts carefully and implement the necessary code after **Answer** to complete the pipeline.\n",
    "\n",
    "These references deal with the problem at hand and can be helpful to consult:\n",
    "* [Quantum-Enhanced Topological Data Analysis: A  Peep from an Implementation Perspective](https://arxiv.org/pdf/2302.09553)\n",
    "* [Towards Quantum Advantage via Topological Data  Analysis](https://quantum-journal.org/papers/q-2022-11-10-855/)\n",
    "\n",
    "<div class=\"alert alert-block alert-success\"> \n",
    "    \n",
    "**STEPS**\n",
    "    \n",
    "* Input: a time series of stock price; Output: a time-evolution of topological properties.\n",
    "\n",
    "* Preparing point cloud\n",
    "    * Apply Taken's embedding.\n",
    "    * Apply a sliding window for obatining a time-varying point-cloud.\n",
    "* Building Laplacian\n",
    "    * Construct the Vietoris-Rips (VR) complex from the point cloud using [`GUDHI`](https://gudhi.inria.fr/).\n",
    "    * Build the boudnary operator of this complex.\n",
    "    * Build the Laplacian matrix based on the boundary operators, then pad it and rescale it.\n",
    "* Applying quantum phase estimation\n",
    "    * Use Quantum Phase Estimation (QPE) to find the number non-zero eigenvalues of the Laplacian matrix. Round up the results and get the Betti numbers.\n",
    "    * Vary the resolution threshold and obtain a series of Betti numbers, which are the Betti curves.\n",
    "* Detecting financial market crashes\n",
    "    * Find the relation between Betti numbers and financial market crashes.\n",
    "    \n",
    " </div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a89d505",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\"> <b>NOTE</b>:\n",
    "\n",
    "In the coding process, it is recommended to start with the following initial values for the variables: \n",
    "\n",
    "* `N = 4` # dimension of vectors\n",
    "* `d = 5`  # time delay\n",
    "* `w = 5`  # window size\n",
    "* `epsilon = 0.1` # resolution threshold\n",
    "* `q = 3` # number of precision qubits\n",
    "\n",
    "However, you will be tasked with determining the optimal values later in this challenge.\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1656ba25",
   "metadata": {},
   "source": [
    "### Step 0: Loading data\n",
    "\n",
    "\n",
    "To assess the practical applicability of TDA with quantum techniques, we will analyze a small dataset of the S&P 500 index from the period surrounding the 2008 financial crisis. You may find the associated file: *SP500.csv*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4ec880cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "time_series = np.log(pd.read_csv(\"SP500.csv\", header=None).to_numpy().squeeze())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4597392",
   "metadata": {},
   "source": [
    "### Step 1: Preparing point cloud\n",
    "\n",
    "**Instruction:**\n",
    "\n",
    "Consider a time series $X = \\{x_0, x_1, \\ldots, x_{L-1}\\}$ of numerical values of length $L$ as input. We choose and fix an embedded dimension $N$ and a time-delay $d \\ge 1$. Taken's embedding theorem convert this time series into a series of $N$-dimensional time-delay coordinate vectors $Z=\\{z_0, z_1, \\dots, z_{L-1-(N-1)d}\\}$:\n",
    "\n",
    "$$\n",
    "\\begin{align*}\n",
    "z_0 =& (x_0, x_d, \\ldots, x_{(N-1)d}),\\\\\n",
    "z_1 =& (x_1, x_{1+d}, \\ldots, x_{1+(N-1)d}),\\\\\n",
    "\\vdots\\\\\n",
    "z_t =& (x_t, x_{t+d}, \\ldots, x_{t+(N-1)d}),\\\\\n",
    "\\vdots&\\\\\n",
    "z_{L-1-(N-1)d} =& (x_{L-1-(N-1)d}, x_{L-1-(N-2)d}, \\ldots, x_{L-1}).\n",
    "\\end{align*}\n",
    "$$\n",
    "\n",
    "To detect qualitative changes along a time series, we apply a sliding window of size $w$ and assess how topological properties change along the sliding window. For a proper size, $w$ needs to fullfill $N \\ll w \\ll L$. The sliding window gives a time-varying point cloud embedded in $\\mathcal{R}^N$:\n",
    "\n",
    "$$\n",
    "Z^t = \\{z_t, z_{t+1}, \\ldots, z_{t+w-1}\\}, \\quad \\text{for } t \\in \\{0, \\ldots, K-1\\}\n",
    "$$\n",
    "\n",
    "**Action:**\n",
    "\n",
    "Following Takens' embedding theorem, transform the `time_series` into a series of $ N $-dimensional vectors. Afterward, apply a sliding window to these vectors and obtain a time-varying point cloud.\n",
    "\n",
    "**Answer:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b701be6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# write your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9376bd0b",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-danger\">\n",
    "    \n",
    "<b>BONUS EXERCISE:</b> \n",
    "\n",
    "`gtda.time_series.TakensEmbedding` can conduct this transformation. Try avoid using this function and build your own embedding function.\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9780b90c",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\"> <b>NOTE</b>:\n",
    "\n",
    "From step 2, we present an example originally provided in the appendix of [Khandelwal's and Chandra's paper](https://arxiv.org/abs/2302.09553). This example can be used to verify your code.\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c945e850",
   "metadata": {},
   "source": [
    "### Step 2: Building Laplacian\n",
    "\n",
    "**Instruction:**\n",
    "\n",
    "In this step, we are going to use `GUDHI`, a Python package specialized in TDA and and higher dimensional geometry understanding. For detailed instructions on the functions we will use, please refer to [this website](https://gudhi.inria.fr/python/latest/rips_complex_user.html#).\n",
    "\n",
    "A simplicial complex is constructed on the point cloud using `gudhi.RipsComplex` class, followed by its `create_simplex_tree` method. The resolution threshold `epsilon` is set via the `max_edge_length` parameter. This process identifies the connectivity of the complex within the resolution threshold and produces a simplex tree. The simplex tree serves as a general representation of simplicial complexes. Using its `get_filtration` method, simplicies are retrieved as a collection of lists, where elements are grouped based on their connections. Each dimension up to a specified maximum is represented by its respective collection of lists.\n",
    "\n",
    "**Example:**\n",
    "\n",
    "Here is an example of a simplex tree $\\mathcal{K}$ with a maximum dimension of 2. In its zeroth dimension, each point is a connected component; In the first dimension, 6 line segments connect 6 pairs of points $[1, 2], [1, 3], [2, 3], [3, 4], [3, 5], [4, 5]$; In the second dimension, a filled trangle is formed among points $[1 ,2 ,3]$.\n",
    "\n",
    "$$\n",
    "\\mathcal{K} = [[[1], [2], [3], [4], [5]],[[1, 2], [1, 3], [2, 3], [3, 4], [3, 5], [4, 5]], [[1, 2, 3]]]\n",
    "$$\n",
    "\n",
    "**Action:**\n",
    "\n",
    "Build a simplicial complex by applying functions from `GUDHI` on the point cloud obtained in step 1, and extract its simplex tree. It is recommended to store the simplex tree in a format similar to the example provided, i.e., in the format $[S_0, S_1, S_2, \\dots]$, where $S_i$ represents the set of $i$-simplices.\n",
    "\n",
    "**Answer:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "026d6b61",
   "metadata": {},
   "outputs": [],
   "source": [
    "# write your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "573efefa",
   "metadata": {},
   "source": [
    "**Instruction:**\n",
    "\n",
    "Let $S_k$ be the set of $k$-simplicies in the complex $\\mathcal{K}$ with individual simplicies denoted by $s_k ∈ S_k$ written as $[j_0, j_1, \\dots, j_k]$ where $j_i$ is the $i$-th vertex of $s_k$. Note that the vertices are ordered in ascending fashion in the initial point cloud, and this order is kept throughout. The restricted boundary operator $\\partial_k$ is defined on the $k$-simplicies as:\n",
    "\n",
    "$$\n",
    "\\begin{align*}\n",
    "\\partial_k s_k &= \\sum_{t=0}^{k} (-1)^t [v_0, \\dots, v_{t-1}, v_{t+1}, \\dots, v_k]\\\\\n",
    "&= \\sum_{t=0}^{k} (-1)^t s_{k-1} (t)\n",
    "\\end{align*}\n",
    "$$\n",
    "\n",
    "where $s_{k−1}(t)$ is defined as the lower simplex defined from $s_k$ by leaving out the vertex $v_t$. \n",
    "\n",
    "**Example:**\n",
    "\n",
    "In the simplex tree $\\mathcal{K}$ we have 1 2-simplex and 6 1-simplicies. By leaving out vertice $v_0=1$, $v_1=2$, $v_2=3$, we obtain the lower simplex $s_1=[2, 3]$, $s_2=[1, 3]$, $s_3=[1, 2]$, respectively. Therefore, the boundary operator on the 2-simplicies $\\partial_2$ should be a 6-by-1 matrix:\n",
    "\n",
    "$$\n",
    "\\partial_2 =\n",
    "\\begin{bmatrix}\n",
    "1 \\\\\n",
    "-1 \\\\\n",
    "1 \\\\\n",
    "0 \\\\\n",
    "0 \\\\\n",
    "0\n",
    "\\end{bmatrix}\n",
    "$$\n",
    "\n",
    "In the same way, the boundary operator on the 1-simplicies $\\partial_1$ is:\n",
    "\n",
    "$$\n",
    "\\partial_1 =\n",
    "\\begin{bmatrix}\n",
    "1 & 1 & 0 & 0 & 0 & 0 \\\\\n",
    "-1 & 0 & 1 & 0 & 0 & 0 \\\\\n",
    "0 & -1 & -1 & 1 & 1 & 0 \\\\\n",
    "0 & 0 & 0 & -1 & 0 & 1 \\\\\n",
    "0 & 0 & 0 & 0 & -1 & -1\n",
    "\\end{bmatrix}\n",
    "$$\n",
    "\n",
    "**Action:**\n",
    "\n",
    "Define a function that generates the boundary operator for a specified dimension, using a given simplex tree as input.\n",
    "\n",
    "**Answer:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "246e41ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "# write your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81764f0d",
   "metadata": {},
   "source": [
    "**Instruction:**\n",
    "\n",
    "The combinatorial laplacian $\\Delta_k$ is defined as:\n",
    "\n",
    "$$\n",
    "\\Delta_k = \\left( \\partial_k \\right)^\\dagger \\partial_k \n",
    "+ \\partial_{k+1} \\left( \\partial_{k+1} \\right)^\\dagger\n",
    "$$\n",
    "\n",
    "The QPE algorithm will be used to estimate the number of zero eigenvalues of the Laplacian matrix. Since its exponential matrix serves as the unitary matrix in this algorithm, it must have dimensions $2^q \\times 2^q$, where $q$ represents the number of target qubits. It is recommanded to pad the combinatorial laplacian $\\Delta_k$ with an identity matrix with $\\tilde{\\lambda}_{max}/2$ in place of ones, where $\\tilde{\\lambda}_{max}$ is the estimate of the maximum eigenvalue of $\\Delta_k$ using the Gershgorin circle theorem ([details](https://mathworld.wolfram.com/GershgorinCircleTheorem.html)), such that:\n",
    "\n",
    "$$\n",
    "\\tilde{\\Delta}_k =\n",
    "\\begin{bmatrix}\n",
    "\\Delta_k & 0 \\\\\n",
    "0 & \\frac{\\widetilde{\\lambda}_{\\text{max}}}{2} \\cdot I_{2q - |S_k|}\n",
    "\\end{bmatrix}_{2q \\times 2q}\n",
    "$$\n",
    "\n",
    "where $\\Delta_k$ is the padded combinatorial laplacian and $q = \\lceil \\log_2 |S_k| \\rceil$ is the number of qubits this operator will act on. In QPE, as $2\\pi\\theta$ increases beyond $2\\pi$, the eigenvalues will start repeating due to their periodic form. Thus, $\\theta$ is restricted to $[0, 1)$. As $\\lambda \\to 2\\pi\\theta$ this means that $λ \\in [0, 2\\pi)$. Thus, we need to restrict the eigenvalues of the combinatorial laplacian to this range. This can be achieved by rescaling $\\tilde{\\Delta}_k$ by $\\delta/\\tilde{\\lambda}_{max}$ where $\\delta$ is slightly less than $2\\pi$. Thus, the rescaled matrix $H$ and the unitary marix $U$ for QPE are:\n",
    "\n",
    "$$\n",
    "\\begin{align*}\n",
    "H &= \\frac{\\delta}{\\tilde{\\lambda}_k} \\tilde{\\Delta}_k\\\\\n",
    "U &= e^{iH}\n",
    "\\end{align*}\n",
    "$$\n",
    "\n",
    "**Example:**\n",
    "\n",
    "In our example, the combinational laplacian is in the form of a $6\\times6$ matrix:\n",
    "\n",
    "$$\n",
    "\\begin{align*}\n",
    "\\Delta_1 &= (\\partial_1)^\\dagger \\partial_1 + \\partial_2 (\\partial_2)^\\dagger\\\\\n",
    "&=\n",
    "\\begin{bmatrix}\n",
    "3 & 0 & 0 & 0 & 0 & 0 \\\\\n",
    "0 & 3 & 0 & -1 & -1 & 0 \\\\\n",
    "0 & 0 & 3 & -1 & -1 & 0 \\\\\n",
    "0 & -1 & -1 & 2 & 1 & -1 \\\\\n",
    "0 & -1 & -1 & 1 & 2 & 1 \\\\\n",
    "0 & 0 & 0 & -1 & 1 & 2\n",
    "\\end{bmatrix}\n",
    "\\end{align*}\n",
    "$$\n",
    "\n",
    "It is padded with $\\tilde{\\lambda}_{max}=6$ and $\\delta=6$ to its nearest power of 2, which is 8 ($q=3$):\n",
    "\n",
    "$$\n",
    "\\begin{align}\n",
    "H_1 = \\begin{bmatrix}\n",
    "3 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\\\\n",
    "0 & 3 & 0 & -1 & -1 & 0 & 0 & 0 \\\\\n",
    "0 & 0 & 3 & -1 & -1 & 0 & 0 & 0 \\\\\n",
    "0 & -1 & -1 & 2 & 1 & -1 & 0 & 0 \\\\\n",
    "0 & -1 & -1 & 1 & 2 & 1 & 0 & 0 \\\\\n",
    "0 & 0 & 0 & -1 & 1 & 2 & 0 & 0 \\\\\n",
    "0 & 0 & 0 & 0 & 0 & 0 & 3 & 0 \\\\\n",
    "0 & 0 & 0 & 0 & 0 & 0 & 0 & 3\n",
    "\\end{bmatrix}\n",
    "\\end{align}\n",
    "$$\n",
    "\n",
    "**Action:**\n",
    "\n",
    "Define a function to build the Laplacian, where Define a function that automatically determines whether the input Laplacian matrix requires padding. If padding is needed, the function will pad and rescale the matrix accordingly. Then, build the unitary based on the padded matrix, in the form of a circuit.\n",
    "\n",
    "**Answer:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8f818f78",
   "metadata": {},
   "outputs": [],
   "source": [
    "# write your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0acfea73",
   "metadata": {},
   "source": [
    "### Step 3: Applying QPE\n",
    "\n",
    "**Instruction:**\n",
    "\n",
    "The Betti number is the number of zero eigenvalues in the Laplacian ([ref](https://link.springer.com/article/10.1007/PL00009218)). \n",
    "\n",
    "$$\n",
    "\\beta_k = \\dim (\\ker(\\Delta_k))\n",
    "$$\n",
    "\n",
    "The betti curve is then a series of Betti numbers on different resolution threshold `epsilon`.\n",
    "\n",
    "To estimate the number of zero eigenvalues (nullity) in the padded Laplacian matrix (padding didn't add more zero eigenvalues), QPE algorithm is employed. The fundamental concept is that, if the target qubits start out in the maximally mixed state (shown below), which can be thought of as a random choice of an eigenstate, the proportion of all-zero states among all measured states is equal to the proportion of zero eigenvalues among all eigenvalues. Assume the all-zero state show up for $\\{i|\\tilde{\\theta}_i=0\\}$ times in $\\alpha$ shots, the probability of getting all-zero state $p(0)$ is given by:\n",
    "\n",
    "$$\n",
    "\\begin{align*}\n",
    "p(0) &= \\frac{\\left| \\{i \\mid \\tilde{\\theta}_i = 0\\} \\right|}{\\alpha} = \\frac{\\tilde{\\beta}_k}{2^q} \\\\\n",
    "\\implies \\tilde{\\beta}_k &= 2^q \\cdot p(0)\n",
    "\\end{align*}\n",
    "$$\n",
    "\n",
    "Where $\\tilde{\\beta}_k$ is the estimation of $k$-th Betti number. This estimation is then rounded to the nearest integer to obtain the final result."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc95fe90",
   "metadata": {},
   "source": [
    "<img 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b24+CiAgICAgICAgIDxleGlmOlVzZXJDb21tZW50PlNjcmVlbnNob3Q8L2V4aWY6VXNlckNvbW1lbnQ+CiAgICAgIDwvcmRmOkRlc2NyaXB0aW9uPgogICA8L3JkZjpSREY+CjwveDp4bXBtZXRhPgrEKpBuAAAAHGlET1QAAAACAAAAAAAAAwQAAAAoAAADBAAAAwQAAeFWo+MvggAAQABJREFUeAHs3Qf8E0X+//EBGxbE7tnF3g7uVBTbCYp6iljALjY8OfHQ/6EnWMCCqCBnxYKigoCInihYQEQFKwKKAgJKUYoKgggCIljIf9/7u8ltNpNk8/0m+833m9c8Hl92s9mdnXnOZhMyn8zUSnjJkBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRqvEAtAkVqfBtTQQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAwBcgUIQLAQEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQKBMBAkXKpKGpJgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggQKAI1wACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIFAmAgSKlElDU00EEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQIBAEa4BBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEECgTAQIFCmThqaaCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAgSJcAwgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQJkIEChSJg1NNRFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQJFuAYQQAABBBBAAAEEEEAAAQQQKILA6tWrzcKFC83SpUvNNttsY7bbbjtTu3btIpyJLBFAAAEEEEAAAQQQQAABBBBAAAEEEIguQKBIdCv2RAABBBBAAAEEEEAAAQQQQCCjwCeffGJeeOEFM3LkSPP555+bFStWpO3boEEDs88++5i9997bNG3a1DRp0sTUqlUrbT82IIAAAnELrFy50vzwww9+cNuSJUv8dS31d+yxx5pDDz007iJxPgQQQAABBBBAAAEEEEAAgSIJEChSJFiyRQABBBBAAAEEEEAAAQQQqPkCP/74o+nVq5fp27ev+fLLL/OusAJHOnbsaM4880yz/vrr5308ByCAQOkKHH/88Wbu3LlFKeC2226bHKlIARxHHnmk2XXXXfM+lwLa9thjD7No0aKsx/bu3dv8/e9/z7oPT9ZcgS+++MJ069atZCp46623mt12261kykNBEEAAAQQQQAABBBCojgIEilTHVqPMCCCAAAIIIIAAAggggAACVSqwdu1aM2jQIHPNNdekdbDut99+5txzzzXNmzf3O7Lq1atnFFCiDuMRI0b4x02ePDml/Jqa5tprrzVXXnml2WCDDVKe4wECCFRPgZ122sl8/fXXsRV+r7328u9J559/vtl4440jnVf3ps022yznvgSK5CSq0Tu8//77fjBSqVTylVde8d9jS6U8xS7Hb7/9ZmbMmGE0pZ1GJIv6+i52uci/OAKrVq3yR6bT50G197rrrlucE5ErAggggAACCJS9AIEiZX8JAIAAAggggAACCCCAAAIIIJCPgH5ZffHFF5sPP/ww5bAdd9zRH13ktNNOS9nuevD666+bdu3apY1CcsQRR5ghQ4YYjRZAQgCB6i0wYMAA89Zbb5lffvnF/PTTT2b69Ol+Z2+2WinYY//99zebbrpp2rRUymfx4sXmm2++MfPnz3dOb6W869ata+677z5zySWXpOURPncikTAanWHixIlm4cKFZsKECeFd/McEijhZymajplZr3bq1X18FK+g6dE2v5gLRe6Ou52xp+fLlfkBl1Dwffvhh/z00W5415bk33njDtGzZMsVbgaoKSCXVPIG7777b/Otf/0pWTCPnaFrDhg0bJrexggACCCCAAAIIFEqAQJFCSZIPAggggAACCCCAAAIIIIBAjRdQcIimkwh3ZmkkkB49epgNN9wwssGaNWtM165dzR133JFyjDrVXnrpJfPnP/85ZTsPEECg+gtMmzbNNG7cOO0eopqpI75///45gzu0r0Y1+uijj8ywYcP8ALXwPUn7aFSjfv36ma222koPIyUFixx99NFpAS0EikTiK6udNN1az549ja4NV7riiiuMOr3r1Knjetq5TYFL8+bNMxp167333jOPPPKI87XSqVMn0717d2ceNWmjgsL0mcCVPv74Y3PggQe6nmJbNRV4+eWXzSmnnJJWel0DCjTcZJNN0p5jAwIIIIAAAgggUBkBAkUqo8exCCCAAAIIIIAAAggggAACZSOgoe5btGiRVt/bbrvNdO7cOW171A29evUyV111Vdruzz//vGnVqlXadjZUXwF1qI4bN85v15NPPrn6VoSSV0rg6quvNvfee29aHuoUv/zyy9O259rw3XffmX/84x/+aEThfRs0aGDefPPNvIJFBg4caC644IKUrAgUSeHgwX8FFPCYKRDknXfeMUcddVSlrDQSj94jr7/++pR8zjzzTPPcc8+lbCuFB4W+xz/66KMZ7wn63KHPH6SqE9BnNwXp3XDDDWbPPfesdEHOPvvsjNf1yJEj/UDlSp+EDBBAAAEEEEAAgYAAgSIBDFYRQAABBBBAAAEEEEAAAQQQcAkMHTrUnH766WlP3XXXXebaa69N257vhj59+pi2bdumHcbw8mkk1XrDscce609Fcuedd5rrrruuWteFwldcoFu3bqZLly5pGfTt29ef1irtiQgbNMLIWWed5QwW0agD77//fsYO/XD2muriuOOOS9lMoEgKBw8CApoqbdGiRYEt/7eqEW8OOuigtO0V2TBixAhz0kknJQ/VNa0RNUotFfoer0CQm266yVnNjh07+iOZOZ9kY9EFfvvtN7Peeuv559H99fDDD6/0OZs2bWrGjBnjzEfByholioQAAggggAACCBRSgECRQmqSFwIIIIAAAggggAACCCCAQI0TmDVrlvOXoieeeKJ59dVXI00TEQXl/PPPNwoMCaeZM2eaPfbYI7yZx9VQYPfddzearoFAkWrYeAUsstpfv0APp8oEiiivlStXGl1jrk57dTbfeuut4VM6H2uKrcMOOyzlOQJFUjh4EBDYaaedzNdffx3Y8n+rhZ4aRVO13XzzzX7mdevWNcuXL087Z1VvKPQ9PtNIZqqnpt7RFDykqhH49ttvzQ477OCfvFCBIgr+0XROrlSoc7jyZhsCCCCAAAIIlK8AgSLl2/bUHAEEEEAAAQQQQAABBBBAIIfAqlWr/A7TyZMnp+ypTqovvvjCbLfddinbK/Ng6dKlZp999knr5G3UqJE/GoD95WplzsGxVSeQSCRM7dq1/QIQKFJ17VAKZy5WoIjqps7j8DQdts6zZ882u+22m32YcUmgSEYannAIxBUo8ssvvxidywZC6T1zs802c5SoajYV4x6vqX00SomCBIJpm222MdOnTzdbbLFFcDPrMQooEOrggw/2z1ioII45c+YYTRem6WyC6YQTTjAaVadWrVrBzawjgAACCCCAAAKVFiBQpNKEZIAAAggggAACCCCAAAIIIFBTBf7xj3+Yhx9+OK16lf3lf1qG/90wbNgwc9ppp6U9rdEHbr/99rTtbKg+AnPnzjW77rqrX2ACRapPuxWjpMUMFJk6dao54IADnMXWiCKZprEIHkCgSFCD9VwCcQWKqBy33HJLcmScKVOmZLzWc5W5GM8X6x6/ZMkSo9FUXnvtNb/YRx11lO+w4447FqMa5BlR4OmnnzatW7f29y5UoIgy++yzz/z2Hjt2rFFA0Mknn+xPVbfhhhtGLBm7IYAAAggggAAC0QUIFIluxZ4IIIAAAggggAACCCCAAAJlJKBf6+63335pNdZoIvpFc506ddKeq+yG33//3ey1117+9CThvDRv/dFHHx3ezONqInDfffeZDh06+KUlUKSaNFqRilnMQBHdQ9Zdd11nyTWaiEYVyZUIFMklxPNBgTgDRdSJ/sc//tE//fDhw42mgCuVxD2+VFoinnKccsop5uWXX/ZPVshAkXhKz1kQQAABBBBAAIH/EyBQhCsBAQQQQAABBBBAAAEEEEAAAYfA+eefbwYNGpT2jH7Z26VLl7Tthdrw0EMPmfbt26dl16RJEzN69Oi07WyoHgIHHXSQmThxol9YAkWqR5sVq5TFDBRRmbfddtvk9BzhOmj6jlzTWBEoElbjcTaBOANF1q5d6083o6k5HnnkEXP55ZdnK1qsz3GPj5W7Sk/2ww8/mC233DJZBgJFkhSsIIAAAggggEA1EyBQpJo1GMVFAAEEEEAAAQQQQAABBBAovsC0adPM/vvv7zzRggULzB/+8Afnc4XY+OOPP/odYa68ZsyYYfbcc0/XU2wrYYGZM2f6I8XYIhIoYiXKc1mVgSKLFy82W221VVZ4AkWy8vBkSCDOQBGdWlNxvPrqq6ZTp06me/fuodJUzUPu8VXjXlVn1fSDbdq0SZ6eQJEkBSsIIIAAAgggUM0ECBSpZg1GcRFAAAEEEEAAAQQQQAABBIovcMkll5h+/fqlneiYY44xb775Ztr2Qm8499xzzeDBg9OyveGGG8ztt9+etp0NpS3Qrl0707t372QhCRRJUpTlSrEDRTJ13Atb02ZtvfXWWd0JFMnKw5MhgUzX28cff2wOPPDA0N7uh7ou//Wvf/kBmgoAyZauv/56P0DkrLPOMs8++2y2XWN7jnt8bNRVfqI1a9b417UCim0iUMRKsEQAAQQQQACB6iZAoEh1azHKiwACCCCAAAIIIIAAAgggUFSB3377zWyxxRZGQ9uH06233mpuuumm8OaCP840/cw222xjvv7665xTRxS8QGRYYYHXX3/dnHDCCSnHEyiSwlF2D4odKJJt6hnd39ZZZ52s5gSKZOXhyZBAIQJFpkyZYho0aODn/Ouvv5p11103dJb/PXziiSfM3/72N9OoUSMzfvz4/z1RRWvc46sIvopOe+ONN5o77rgj5ewEiqRw8AABBBBAAAEEqpEAgSLVqLEoKgIIIIAAAggggAACCCCAQPEFPvjgA3PEEUc4TzRq1CjTrFkz53OF3PjRRx/5nWCuPIcNG2ZOOeUU11PVZtvvv/9uvv32W/PVV1+Z1atX+4E56txWh2NNSm+88YY57rjj0qpEoEgaSVltKGagiDrZ119/faenRnfQKA+5UikHiiiAT/cN3T822mgjfxqdXXbZxWy88ca5qlXh5xcuXOiPxLJ06VKzatUq37d+/fpG5w0G3ej5CRMmmCOPPNIvW0VOqEAeja7xzTffmO+//95suOGGZvPNN/enrtJ6KaZCBIoE33dzBYpo38suu8z89a9/NXfffXdkkrVr15p58+aZH374waitfvnlF7PJJpv407mFp5P78ssv/aDMo446ytSqVSvjObjHZ6SJ/QlNq6V2U/vqNaMptnbdddesQUf5FjLTvbu6BIokEgn/2tf9U/c1BWTtscceZvvttze1a9fOl4P9EUAAAQQQQKAGCBAoUgMakSoggAACCCCAAAIIIIAAAggUTkCjhtxyyy3ODNW5tNlmmzmfK+RGdWBtsMEGziwvuOAC079//7Tn1Lk7f/58s2TJkuSfOhrt34IFC4xGJMnWUTx9+nSjP3W0KB8tdbw6YPSnDkzl8fbbb2fsjE4r2H83qIO1b9++5rHHHjOTJ0927rbjjjuaFi1amMsvvzz563Lnjhk2zpw50+iX6bbctu4q93fffeeXX79Cf+GFF1JyUKfsgAEDjIaSnzp1qlE+9erVMyrPbrvtZk466ST/T51PUdKcOXPMXXfdZR555BHn7urkVDtmSmr7Qw45xPl0qbSzbMeOHZtyreka0XZrrcc//vhjSkerroOBAweaTz75xG8rXQvqAN9zzz39jveGDRuac845x+y8887O+mujOtNfeeUVP49Jkyb517TOow5r/R1++OH+dfTnP/85Yx5V+USmzka9Pi6++OJKFU2v74MPPtiZh0YquuKKK5zPBTdGCRRRsNeIESN8e7WBAiRsG+ywww5+GzRv3jxjwFvwfLnWda38+9//NuqU12vZlRSQ1apVK3PhhRf615Nrn3y26brUdFEjR470O58zHXvVVVeZa6+91g94a9q0qR9ccM8995gOHTpkOsS5XfdUTTf29NNPO0ez0kFNmjQxF110kdHUZJneH5yZF3ljIQJF9HrWvV8pV6BIPtVRx/hrr73mv/do6RopTPnpfe26667zA1DUFieffLJ/Gl3XrtdTMe/xCoTSa8q+f9ll8H1M7yHZRjcr5HuhpqpSwIX+FDjTsmVLs+mmm2ZshmXLlpmhQ4f69/dPP/3UvzfoHq/3U10rxx9/vN/WWq9MUuDP8OHDzb333uufw9W2devWNSeeeKL/fqv7Ubagn0xl0TU0btw4/3Oh7geu9OCDD2b9zKLra++993YdahQYrDa37WyXev/Ue6kCOvT5RG4VTbqH/uc///Hz0ah0rqTPRvqs0759ez/IxrWPa5veL+bOnZv2uStYfr22wvdE1fvFF1/0P3Pqc5c+o+pa0/uHPgeoLMcee2zenzVdZWQbAggggAACCGQR8D7skBBAAAEEEEAAAQQQQAABBBBA4L8C3q/uE95/o9P+9tprr1iNvA6ZtDKoXI0bN3aWI1O5g3Xxgh6cx9qNXiey85zBPLTuBWLYQ3Iuvc6cRK9evRJeR0lK3t40A4lTTz014XVOpGy35zrzzDMTXodGzvyDO3Tq1MmZl81TS69DOXmI6hHlGB3ndTglvI7j5LGuFa+DOK2ewXPns+6NXuM6RaJU2tnroMtprfqq/ZW8zt/Eo48+GtlH7bJmzZo0g/feey+hayeKpdfxnPB+OZ2WR1Vv8KYtcJbfCxSpdNE6duzozFvXb9TXrRcAlJZH8Nr3OgYzvm7D7aLXm9eJWKF6zZgxI6E2DOapenhTOSW8Tl/ntaT7TGUcly9fnvCCuFLOqTy9zuaE14Ga8AIJE15wiH8fCZYruK59oqbPP//czzt4vNZ1Ttntt99+KWWxz02cODHqKYq+nxcAkFZGldMLWop87ksvvTSZh+4VhUhesETadSrP008/PXHNNdckvIDQhBeUmPV+Mnr06JSixHGPz3R/CF4jeg1kS1He1yr6XqhyeMF+aaf3gsf8155eo8GyZlrXvcoLik3LJ8oGvT+G3wd0Heq+cMwxx/jv1+Hz6r1T97Z80llnneXMK5x3lMdeoLHz1GqHXMd3797deWyujV4ASkKfpcL567Og7mk6t+v16wV2JLwAlVzZ+89H+UziBUcm89I9z1WmcBn1WOX0AreSx7KCAAIIIIAAAoUXMIXPkhwRQAABBBBAAAEEEEAAAQQQqL4Cri+rtU2dD3Emb1SFtC/3VQ51wrhSlC/rqyJQ5Oabb07WQx0Sjz/+eMIbrSSlCgoI8EbfSO5n20Cdpd6Q7in7ZnuQT+eY92vXlE5YBa2oM9z7lWvis88+8zu8XKY9e/bMWIR27dql1cHWJd/lkCFDnOdxlSmcdxztnE+giDp+g53vqoM34kpCnbDqzPVGeEmoQy5cDwUJ2EATYahj1+6ja0OPvZEI/DzUcajOX/u8XcrC+4W707KqNmbqCK5MgIPqoqAYW+/w8rnnnotc3WyBIuqwtHmrDbp06ZJ46aWX/DZ48803E9dff33y+eB+er3lkxRcovxtHrp+9Nr0RpNJyUbBJN5IG8n97P5t27ZNeNNapeyb64E6rYOBawoO9H6Fn1AHuCspkC0Y4GDPHTVQ5JlnnkkrtzpvvVEYUk7njSqQ8EaQSNlX7wMK2CmF5OpolkXUQBEFMFk7LQsRKOKN+JHSwa/AivHjx2fkUuCNgjCD5dC67lHBFMc9PtP9IVi2QgaKVPS90Jv2J0nz888/+wFctoyy1PPvvPNOQq9RvY70Hmuft0vd9/NN3qgeKfl4I6skvClnUrLR+4Y3ApEzCEIBi1GT3j9sWSu7zBR4UaxAkaeeeiqt7Lp+vdFq0qqve374M6fuMQrMzJWifCaxgSJ6DQYDiRR8N2jQIP8zl5677777Up635lHKkaucPI8AAggggAACbgECRdwubEUAAQQQQAABBBBAAAEEEChDAW/qhLQv1u0X1foFZJwp2+geP/30U1pR1LmoThl1nOvLd1vu4DJXAIE67dXh7g0HnlCAR7CjNphP1JEJHn744WQ5vCk1nCNEBCui87s6ZqJ2OM6ePdsvvzfsfaJr167OTiJ1yqj89tfI6rRQJ5YrKaBFncXBumvdm5bCtXti1qxZ/i+W1eli/1SO8PHqHFMATLY/b/h55zlKpZ1lo8CAl19+OeENu5844ogj0uqpeqtjv02bNsnnFNzh+hW5OuNbt26d3M+aedOl+A7qQLLbzjvvvIyjY3hTlCT3s/tr1IBSSpk6gisTKKKO2kxtoHtJPilToIgCqaypRmXIFPyhjli7n12qzaImXfvB153Kky3p2nG9zvK9Z99+++3Jcuv8K1euzHba5HPB4BnVN0qgiF4z1sYu9drIFJSikwVfA/aYd999N1mOqlqpTKCI3rOCba16VTZQREECwc53vfdESQpYDAczhANF4rjHK0hK78PDhg1LdO7c2dlxnitQJK73QgXYqL28aZ+S17OCAlxtqG1hX7W3AqaiJgUT2Gtfo8PkGjFKn+lc57TvK7nOq/rZ93K71L3PlsEue/TokfX9XO/1rvc9nV+BGwp+UTCfAtxsnsFlviOKBO9lykef5XRN5UoK2gieV+vPP/981sP0+cybhsz/HHXllVc6r1ddE7K0QSJqO1fAik6kgMBwGfS5MOr9OGtheRIBBBBAAAEE0gQIFEkjYQMCCCCAAAIIIIAAAggggEC5CihQIfwFtX0cd2ezfqlvzx1eaujuXEkdIeHjcgWKhPOcMmVKWh7KM0qgSPhX4uogUKdXeESA8DkVfOAqt6aEyDe52lMdiOo41DnUWTF//vys2aojNlwejW4QNanzJ3y8/XVt1Dyy7VfV7WzLpk7WcIev6q3gB1v/XKPDKADK7muX6oR+6623ktufeOIJe8qMy+CoEDafb775JuP+cT9R6ECRqVOnpoyEYeusZYcOHbIGH7jq7goUUaCHzVdTSeVKGoHJ7m+XGlkgStIIAfYYLTU6QaZORZufAixc03VFHT1AZQueM2pwms6vwIRgfXMFiiiYL3gurWvEkCgpODKPjtN91RU4GCWvQu2TKVDkhhtuSDz22GMpfwoe1GhCGv3HNRKM6uQKMsinrP3790/6qoM8nw5mvW/ZzmyVJRwo4ipHse/x6uBXWYJ/uQJFwuUs1nuhrlsbpCU3dfJnS+HPBaqT3jeipnAwnILBcn0eWbRoUUqbWsfwyD1Ry+AKxM313hY1b+3n+uyXT6CIK6As1/0zWD7X/SlXsEjweFewiYLgbBCw3ktWrVoVPCRtPRzoojZ78skn0/ZjAwIIIIAAAghUXoBAkcobkgMCCCCAAAIIIIAAAggggEANEXB1kNpOBXV6xZk0bLs9d3gZ5Zeh+kVx+Lh8A0VUX1cnYK6OGR3n6jxTefRL+lzJBnIEy68Ox4okBYME8wmuT5gwIWeW6rQMdhzqeD2O2pnpcihkoEhVt3MQUEEJQV9rpaU6r6Kk4C/Tw3lpxJEoSb7hY0upk6kQgSL6pbym7HGNwqK667U+ePDgKFxp+2S7D+rX+VGSa8SMKAEmytsVcKQOf42aki1Nnz49rd11XJTXqu4vwWtGwR/5pODrPFugyLx585z3kxUrVkQ6nabYCJZT65q2qyqT6z0iXMZ8Hkdpr2z1DQY1Rb1eg/kFR/MqhUARBeGF/fINFFH9ivFeGCyXppWLkoKjvdjjowSRKdjP7h9c6j0jVwoGLNpj8xnlKJh/sQNFdM3ZMtpl1EARBazYY+xy4MCBweJHWldQrz1eS33miRpsqZGmgscG13U/1ntXrqTAluBxWtdILiQEEEAAAQQQKLwAgSKFNyVHBBBAAAEEEEAAAQQQQACBairg+iWl/bJaQ4vHmTJ1Jqs8+sV0rrR69eq0L9orEijiGp0hSqCIvKxdcNm8efNcRU+4RvHQaAEVScFf+gfLoaCGqMk11PycOXMiHR7sQLbnL2SgSFW3cxDB9Stg1fnAAw+M1FmvvFwBBspDHVULFy4Mni7j+nvvvZd27V199dUZ94/7iUyvbQVIqBM1059eA64gCntdaamOOAUOqHO5oilboIgCHaIk/Vo/WC6ta1qFXEkjg4SPs4817USu5Hq9a0SaXCnc+bt06dJch6Q8HxwNJ1ugSHhEENXtgQceSMkr14PwVBq6r1c2uCLXObM9X2qBIsHXiO49+abg/aMUAkVU/nCwYkUCRVyvDV1/lX0vVB4a6SPbtEnBNnDd/zTNTq6U7b6UK7DLFWyjckcN0AqWLXyvUD6FHFHEFSQRJVBEnwXCr0W9FnLZBOtm110jv+iai5KX7kUycf1pWsMoSecJH6+6kRBAAAEEEECg8AIEihTelBwRQAABBBBAAAEEEEAAAQSqqcCYMWPSvpy2X1arcyPOFP6Fuy2HllFHCggeo/WKBIqEh3pXPlECRTJ1+Ldo0SIno4aKD5ddjyuSTjzxxLS81OkW5Vet9nyadihcnqhTUxQ7UERlDJctzna2RlpqSolwWfT4ww8/DO6Wdf2ZZ55x5tG7d++sxwWfnDZtWloeUUcjCeZTrHVXR6nLLZ9tep3++9//rlDHZ7iemTpke/bsGd4142MFlITLH2V0B3U2hzvFbT5RRgByjWoTZRQjdYLa82jZp0+fjHXL9ISd+iZToIimDAuew65HDYCy59XILPZYu4zS0W6PL/Qy3Dlty6RpxL7//vuUP9VVo6LonqDXtOvYygS9uDqYdT/IJ2nkGluHmhQoUqz3QllpmrqoyfXZJspoJK4ACttOUQIYXCOqVGT6mWIHirjev6IEirhc8w1CC7bhlVdemXwdWOeo9xm7f3Cp6y+fpM8xweO1TkIAAQQQQACBwgvwDlt4U3JEAAEEEEAAAQQQQAABBBCopgKuaTzsF9XXXXddrLWq7NQzKqwtu13GGUDw2WefpZ1f5Yja2ezqLI4SoBJuJFfn2GWXXRbeLevjTp06pdXljTfeyHqMfbLcA0Xy/RXw8OHD06x13Wg4+6jJNUVBvp1UUc9Vkf0yBYo0adIk8fDDD0f601QKGgFJHe4V+VV8tnJnChSJOoqO8l62bFlaOyqYJUo666yz0o7V/WDlypU5D1eAh73f2WXHjh1zHufq/B00aFDO44I72NFCFLDjSq6OV43YlG9yjdZy00035ZtNwfZ3BXvIPkownUZi0Wg/tq20rEygiCoVHFFE+WmUHQUZ5JN0jI4dN25czsPiuMeH3w8rMqJIsd4LGzRokNMouIPLS0GGuVKmILKo9/bglET2etM9NN/kulcUckSRigSK/PLLL/51butll5qOq6LJNcJelEBfnc+eP7jMdwocjQYUPF7rq1atqmh1OA4BBBBAAAEEMggQKJIBhs0IIIAAAggggAACCCCAAALlJ+CaxsN+UX3FFVfECqJfpdtzh5dROuBU2PBxcQaK6Pz6xXiwDOoA1q+1oyR1mgeP1fqCBQuiHJqyj6tzLOqILDajm2++Oa0sI0eOtE9nXbo6xQo59YxOHnaKu50tgGtEkXbt2tmnIy0VgBOuT77TRyioJJyHpnMplZQpUCSfKSCKWRdXoEi+15Q69MJtEDUo4uuvv040btw4ebw6yUeNGhWpyq5RoRSgkSvpnhAurx4ruGXIkCGJ5cuX58oiMXXq1IQC/ObPn+/c1xVQUZEAxN9++y1t1BV1gldVctVLdlHfpxQYEsyjsoEiuue42vKcc87xpzVTp3qupPu73r8UyJIrxXGPL1agSCHeC6MEYgUNhw4dmtY+Ud8TFZBhg3jUxnpvUIBvlNS1a9e08z7//PNRDk3ZpxQDRVzT9cmnMq8lV8Cl8tT2XMn1+tN9PZ/kGs2u0EGR+ZSHfRFAAAEEEKipAgSK1NSWpV4IIIAAAggggAACCCCAAAIVEgh2QgS/7I67I841hYItz1dffRWpbnZ/u8y3s1cncX1Zn8/IHupo05QLS5cujVRmu1N4KgjVIUoHhT3eLl2BIuoIzye5AkU08kWUFEcnom1fu6yKdpaFK1CkR48eUZiS+7gCRc4888zk81FWXIEixxxzTJRDY9mnOgaK5DuCQWUCRdQImkpCHYvqBFZgRNTkCnKJEuSn4A77+sm01NQyN9xwQ+LFF19M5DtdjH7Z78r3kUceiVq1lP3Cv7aPGoSTkkmBHgSDPIJ1jBooomJ069Yt6VOZzm3llSnoJ1g2TYOk4ARNjxNlpBrlmynFcY8vVqBIId4LNQpSPskVKKL2j5p0fei+kO/nAb0XBa8Bravt8k2lGCii+1K4bvmO9OJyCOepx1Gm8nIdpxFh8kmuz575TBmYz7nYFwEEEEAAgXIWIFCknFufuiOAAAIIIIAAAggggAACCKQJqDPQ9SV3vqMapGWc5waNgOAqhzqMon7hHj6+qgIIMlVdHT6aokbz3j/00EOJ66+/PtG2bduEAgPCHWOqS76/SNV5XYEiM2fOzFQk53ZXoEjUIevj6EQslXZ2BYpoipR8kitQRB1z+SRXoIhGqCmVVB0DRS666KK8+FyBIoW8hy5ZsiSh0UMGDBjgd/hfddVVCU394upcjDqqjaaMCb+Wsj3WFCc6r8qRK2nkAlde99xzT2LKlCl5/4WDM3S/rKoULoutZz6BIhoxxh4XNVBEwXoakeU///lPStUVWKRAEJtflKWuG93nZ8yYkZJXlAdx3OPD74f5Bm6pHsV6Lwz75zJzBYpotI9CJU2RpRFhnnjiiYRGZlOgmEaTCU9JpOsi3xFVVMZSDBQJjsBkr3dd05VN+sxo87PLKO/Hdl+7VAB2vsl1L8834Djfc7I/AggggAAC5ShAoEg5tjp1RgABBBBAAAEEEEAAAQQQyChw8cUXp30xbr/sjtqBlTHziE/o1/ThjiFbBnWARU32GLsshUCRefPmJfTLXo3wYMsVdVmoQJFMU0NkciVQJJNM6nZXoMgzzzyTulOOR65AkXynNnAFiigArFRSdQwUufzyy/PiK3SgiO69Cgxo06ZNwtV5me0eEjVQRBW89NJL874v6dzqqNXUM5mSAuGylbEQz2U6d7G3FyJQZNy4cUmfqO+zmspMbq7pezRVkEZUqIirAo7yGTWrOgeKxPleaK9DV6CIAjoqmjTKxFNPPZU4/fTTM35uynQd1JRAEddIeBUJJgq3QXjkIjk2b948vFva47B3KXz2TCskGxBAAAEEEEDAFyBQhAsBAQQQQAABBBBAAAEEEEAAgYCAOhzCX3Lbx5pCJY40a9asjGW4++67IxfBltsuq/LLev3CN9MoKSqfAmAUQDJw4EB/OgBX5yOBIu6mt+1rl1XVzgSKuNsnvJVAkbBI5sfqsNe0Cq6OUF3v++23X0LTdD366KP+yES6P9rXgV3mEyiyZs2aROfOndPysHnlWg4ZMsRZGVewmfJS+Vu1alWpP43AVJmOdmeB89joulerbvmMKBKcmidqoIgNGNJ7titpeqB8Rxax7au8swX+BM9HoMgrQY6c64UKFNHnMY10ZNssvLSjxGhUqxEjRvgjlYX3qQmBIhpBJ1wvPdZ9pbLJNQqLtuVK4fJU1WeSXOXkeQQQQAABBBBIJAgU4SpAAAEEEEAAAQQQQAABBBBAICCwYsUK55fu+uK7Ip0Kgawjr77wwgsZyzBx4sTI+ZTCl/UKesnUWacOzvfeey/h6hjUr2HD5SdQxN30Yaeq6pQhUMTdPuGtBIqERdIfq/OzT58+zhECFJjwwAMPJBYsWJB24NixY9PuG/kEitgMNSWWpqzINLJT+DUXfOwKkLjpppvSyqVjdJ7qngoRKPLTTz8lNJ2X/jSiVq4UfJ/+8MMPs+6uIMVM70HBdguvq17Lli3LmreeJFAk3kARtUmnTp2cr6dGjRolNM2Tro9wUiBquI0r8pmu1Kae0Ygq4Xrp8XnnnRcmyPuxa1QeBbflSuHyVNVnklzl5HkEEEAAAQQQIFCEawABBBBAAAEEEEAAAQQQQACBNAF1EIa/6Nbj1q1bp+1bjA36Bb3r/BoGPJ8UziPuL+vVQRcugx5rmoZco7MQKBK9pcPGcbezLSmBIlYi+5JAkew+mrZG0xuEr2s9VoDIL7/8kjGDQgWK2BMoiG38+PGJe++91+941WvLVa7gNu0T7qhW0EtwH7uuvKt7KkSgSL4Gb7/9dtIz6jQxK1euTIwaNSrRtWvXRIsWLSIFAUV5zydQJL5Aka+++irhut404pA+b2RLNTVQRIFV9n4SXCoQt7LJNfVMlM8XwXJoPcox4bJqRJhwPlFf6+G8eIwAAggggAACmQUYUSSzDc8ggAACCCCAAAIIIIAAAgiUqcBHH32U9gW1/cL6559/LqqKvvTP1BmpIdTzSbbMdhnnl/XDhw93GioIJ1tHr61fOQeKXHrppYljjjkmMX/+fMuRdWnb1y7jbOdgwQgUCWpkXidQJLONgkRcr32N7BFlNKWKBor8/vvviUWLFmUuWOAZ7afpM04//XTnPU6vwwcffDBwRMLvxLavz+BS98nqnlwd96qja2SVQtXVvoYUIBBOeo/WKAtRkka8evLJJxOuDnHbTpMmTcqaVUUCRfK9x4dHttFrJN904oknpl2vUd9j7LlcUyhpFJh8UkWnnpk9e7YzSESBp1Feu1UVKKLRclTGCy64wDl6Wthu2rRpae3UvXv38G4pjzXKh71e7VJT/VU2uV7bTZo0yZmtLYNdVtVnkpwFZQcEEEAAAQQQYOoZrgEEEEAAAQQQQAABBBBAAAEEXAKuIbf1pffLL7/s2r1g295///20L/x1XnUU6RfR+ST7Jb1dVuTLelcHRK5fder5cMeWyqBfuGpKiSjJ1VlcLlPPqFNJXupQi5Js+9plXO0cLhuBImER92PbyW3byy47dOjgPiDmra5gi8svvzyvUijgw9bLLqOMiNStW7e043R8rulFbOFcZY8y9Yzqp/No2op80syZMxOa7sLW0S71Gg6m6dOnp+2jfR9//PHgbtVy3dWZrLoVM1BEneA6hytgQvc/PZfv+8Wbb77pfN/q0qVL1napSKBIvvf48Pupq95ZC+k9Wd0DRRQ8qXYN/qmtFy9enKvq/vNVFSiiz222zFHKWpFAEY2QY89hl/oMW9lk8wouL7744pzZBvfXekU+kzCiSE5mdkAAAQQQQKAgAowoUhBGMkEAAQQQQAABBBBAAAEEEKhpAs8880zaF+/6wltfXudKCoYYMmRI4tprr/U7Z9QJqdFA5s2bl+tQf3qD8Jfsevzoo4/mPDa8QziffL+sVz3CeehxrkAR19Q56uiK0kli6xAlUEQdeJ06dUosWLDAHpa2rOrOsTg6EcNtFFc7h7EJFAmLuB8TKOJ2+e6775z3G41iEDW5Au3CgSLvvvuuf98YMGBAMlt7vznrrLOS26KuLF++3B8BKPw6DB6/Zs0aZxBCuGzBY6rLetyBIt9++23yOgkHVwWn4ejdu3fehJoSTaOUBNuyVatWWfOJ4x5f7oEimaaxe+ONN7K2TfBJjcoRbFetDx48OLiL/zlNnykUcJYptW/fPi0f3XcypTgCRW655Za0Mql+mjqrokmBVmEvPR44cGDOLMPH5fuZRCcgUCQnMzsggAACCCBQEAECRQrCSCYIIIAAAggggAACCCCAAAI1UeCcc85xflH+1ltvZazuwoULE/bXzuEvy/VYnUqZkoa4dx2jX+JX5Av/cOdSvl/WK7DFVZ5sgSIqp+sYBc3kk1xTAYR/IW7PM3Xq1IxZV8dAETtCQdQRRaqinV3gBIq4VNK3ESiSbqItd999t/PesWTJEvcBjq2aBsPeF+wyHIzRq1cvfx/d320K3rMrMr2Y7on2fFrqNRmeYksd0MF9tK4RmyqTVNa2bdsmdE1VVYo7UOTee+9NOvbp0yel2ppCyBrr3l+RpOADm4eWGq0hW6pIoEhl7/HlNqJI8+bNU9pE7ZLviBmu1184UMROJ5UtMDffQBFNg2SvpyjBshUZUUQjG9lzBJfZPhtlu6b13IgRI5x5fv/997kOTTsu38+eOgGBIjmZ2QEBBBBAAIGCCBAoUhBGMkEAAQQQQAABBBBAAAEEEKiJAkuXLk24OsEUxBDuBLT1t79M15f1N910U+LFF19MPPjggynDvj/wwAN29+RSv4QOHhv8sn/cuHHJ/fJZCf8yOt8v699+++20L/xVrmyBIrNmzXIe85///Cefojt/fV8dA0VeeumlNI/bbrstq4Vtt+HDh2fdzz5p97fXTBztbM8dXBIoEtTIvE6giNtGUxrYa9gu99prL/fOGbZqKhd7rF3mGyii0Qsqki644IKUc4eD+zRahS1TcKlpaSqaBg0a5OeZ72u+oudzHed6j1T9ijH1zIoVK1LekzU6TDAFA0VUBr2HVyQF76m5gjLiuMeHgwFzlclV56oOmrRlUgBk8PrX+q233mqfdi6D7WGPVcBGPql169Zp561IoMg111yTlo8+K2VKs2fPTu6/bNmyTLslt1ckUEQHu6bmeeihh5L55rviCohRIE2UZNvILityfyJQJIo0+yCAAAIIIFB5AQJFKm9IDggggAACCCCAAAIIIIAAAjVYwDWVgb781lDf4aSOffvF+Pjx41OeViBIt27dks9/+umnKc8HfyVt89Ay2wgkKRk4HqiTNZiXOpvySZoyJ3i8Xc8WKDJq1CjnMZ999lnkU6vj1J4ruMwUKKKOlUypqjvH1M7BOmg9WwdXcESW8DWSqY5V0c6ushAo4lJJ30agSLqJtjRu3DjttZLvVDDnnXdeWh6ZAkW0r03BEUUuvfRSuzmv5ZVXXpk8d6bRDlwjI+g+W5Gk9xSdR/cUdRJXVYozUCQ8KoRG8AqmcKBIcHqh4H651oP31FyjYcVxjy/nQJGffvop+boKvpfmM7WQptFzBZtkChR57LHHMl4iCvwNlkPr2QJh33vvveT+GTMNPFHRQJGXX345eR5bPo1YpPtEvmnVqlXOYN1sn7WC57Dnt0sCRYI6rCOAAAIIIFBaAgSKlFZ7UBoEEEAAAQQQQAABBBBAAIESFNAIEPYL7+BS0xwEk+3E0i9OMyV1fCoPdfCpU0spUzDKI488kimbSNs1ZH6wvFqPmubMmZN2rM3rm2++yZiNfkVu9wsu1VkSNV1//fXOPObPn5/MQlMu2PyzDYXuGqVFU+rkk7p06ZI8lz1nuO0z5ReekkLHq0M8Uwq6L1q0KNNuKdurop1TCvDfBz169EhzeuaZZ1y7ZtzmCjTK9npyZSQ32052edRRR7l2rZJtwYAxWz4tr7rqqiopT/ikY8eOTfPLN5jB1bmrkZiypVNPPTXtvArgiJq+++67tOPlGi67Ri/Q9o4dOyazDgaK6LmKjIYRzEOjo7iS7p3hTn+dT1NH5JvUya1j9adRLaoqxRUo8uSTTybrqzq7Ah/DgSIKDtAoJPmkNWvWpJynb9++WQ+P4x4fvmbyeV3YwhfrvVABCvkkjbJmr1u7zDaiiIInw/XXcflMt5RpGpXw+5PeJ5R3tvd31/RWnTt3zkgwcOBAP8+o00xpuhjrYpd33nlnxvyDT7hGZcq3fZSf6z0qW4BrsAxat+W2y4oEirgCB7MFKYfLwGMEEEAAAQQQiCYQ/RuiaPmxFwIIIIAAAggggAACCCCAAAI1TkC/yLz99tvTvvzWl+BvvfVWsr62wz5bp11w+gGNQDJ69GhnJ0iu6UmSJ82y4irzlClTshzxv6f0K3z7JX94OWnSpP/tGFrTL3ddnToqS5T0zjvvZDyvOrBtCg7nHp7iwe6jpf3FfbAOEydODO6Sc901ssoLL7yQ8zi7g+uXzMuXL7dPpyx79uzp11/HRP0lcFW0c0qh//tAv7wPOmu9V69erl0zblPHXTiPiy66KOP+ridcI9JkC85x5VHMbQpQCNdRjzMFFxSzLK68Xb9MjzrlgM1PQV3hOubqKHX9Ul95ROnoV4CAqyNcx2tUoWBq06aNX7a77747uTkY5KFjGjVqlNC9LGpSAEiwvuGRCoL5uKYqkY2Ca6ImBZbY+2y+o65EPUfU/Ww5gvXXevB+HTUv135yscE9wXO4gr/CgSLaXwGc+aRwIMCXX36Z8/Bi3uM1zV2w3lrX9ZlvKtZ7Ya5AmnA5+/Tpk1YfBWNmS7r/hA2ijqKjwEFX+yg/jYIVTHa/8IhwwX302guXRdOkZEp2VLOo72Ouz0A33HBDpuxTtutzhYIyguXT61MBqFGTa4QcvX9qlJEoyRU4pfLkm8L1UB4KBiQhgAACCCCAQGEF8n+XLuz5yQ0BBBBAAAEEEEAAAQQQQACBaiMwdOjQlC/g7ZfxCupQsILtgHzqqaey1sk197rNS8t8O7YynUwdXMF8te6aMid8vA1W0P5NmjRJy+Oyyy7LGsRwzjnnpB2jvHINWx7s0PnnP/+Z1uHRoUOHZFFtp7Krs9Du5Kq/yqH6RU0rV65MBKch0PH60/QUUQM5XNMKudpYv2S3v87v2rVr1CImXPWMo52DBdQILxoxwvrYpabasCPnBPfPtO76RbQ6jH788cdMh6Rtt9eGLYNdhqcuSjswhg3qRLNtbMtll+rQyzZaTwzF80+hX47bMtmlOlCXLFkSuQjqPLbHBpfZRs5w/ZJex+q+mit17949eT79+j54Tq1bVwUd2M7gYJBfOFBEx1x99dUJddLnSuEgFQWs5Lo3uMqo94XwVCqucytQz9ZB10yUY1z5FGLbsGHD0qytvUYAqWhSkI6CGnWvzhSI4hrhwBUoovKER47IVK7ge5CO03UVJRXzHu8aZUkmCxYsiFI0fx/Xe4TqV4j3wnwClfS6OPPMM9OuGb136D0kU3r00UfTjlH5+/fvn+kQf7uuIxuooUAZvW/rOPun89pA02CARK6gLRsUbPPR0jUKSTAweMyYMVnLap90jWCmQI2o76O6j4bfYxSINmPGDHuKjEsFd4Vfb8rr22+/zXhM+AlNwxN0sesffvhheNeMj4Nu9ngtc322zpghTyCAAAIIIIBARoFaesZ7oyUhgAACCCCAAAIIIIAAAggggEAEgcmTJxuv89t4nc4pe3udfKZhw4bm4YcfNt6X+ubdd9816667bso+9oEX8GDuu+8++zC59AISzGOPPWaOPvro5LbKrlx55ZXG6zhPyUbn8II9UrbpgddhYrzpL0zv3r3957xOMuN1sBpvVIi0fb3OA+N1wJjNNtvMbLvttsabHiS5j9fZZrwADuN1TCS3acXr8Ddex46RVTB5nUfm2WefNV5wiNGxXqeG8aaqMQ899JDxOk2CuxpvehOz8847m7Zt2xpvpAHjjaZhvF/b+vu88cYbxpvGx3idQ8brGDPeyAj+PikZ/PeB1zFs/vSnP5kNN9zQHHLIIX6b6qnPPvvMeKOF+Bber1fNm2++6eflysPrZDKHHnqo8TptTe3atY2sN99887RdvU4ns91226WVxeuU8a8VHeB1SBsvwMZ4w/L7x3vT45iddtopLa9MG+JuZ6/D33idr7714sWLjdfpntbetqxeB535y1/+4tv84Q9/MN4ILb6X2s/rYDVeB5jxfgltvI4k/88eF1zqevM64H3H9dZbz3jTlPivN+1zzz33GC+QxKxevdp4nehm5MiRwUOT614HmN/Ou+66q9/u3i+8zS677JJ8vtArun6XLl3q10/XgF4PXsd6ztPo/rL33nsblVf3ENXXCyzKeVxFdpCZ96t6v4xqD++X9P5ryJWX2qBZs2ZGy/XXX9+/3vX6V1JddR0oP90jvakeXFn427yOZVO/fn2z0UYb+W2otrRJ+XgBAPZhcumNwmJuuukms/HGGye3aUX3YW+qKuNN7+Bv90Yr8F9Hsgsm3XO8EW/M888/7++r5/Uas+U//vjjjdchHzzEX9e9XNe5rhlX0v1CZQvWV/ce1S9X8jpUjSyCSfeSf//73/72DTbYIPiU8QIDjNdhbrzRNZLb9T5z5JFHJh8Xa0VWAwYMMLpX6/7qBTyZDz74wHijM2U9ZevWrf3rRe1Wq1atjPt6oxX494Bly5YZ3Xd1L9D1mC3pWrniiitSdlH51llnnZRt9oEXJGDuv//+tGvIPv/qq68aLzgoeR/Tfeujjz7yX392n0zLQt7jdS3PmjXLeIGDxhsdKeM9Q9fwaaed5t8T999/f3PhhRcmixf3e6E3wok57LDDTL169fx7ln0v9ILL/HuDrhm1rd6fM10zuq/odbjDDjv4bfT//t//M3Xq1PHrpOPPP/9889xzzyXraFe8oDS/7noPDiZdQ/o8M2HCBH+z2lLtFP585QUnmlatWpkbb7zRv3d5I5X47/vBvMLrylOfG4JJn2/0mtDnISUvuML/HKT7gT7becEPaa8Bdct407z4rykvKNW38QJK/OPD/yh/+eieddJJJ/l5h/exj3VuL5glzdqbztB3DN8fde/W5z7dY4NJn+OGDBlitt566+DmlHXdc/U5Ufd+3Q/1OnIlnVPvH/vss4///nHGGWeYAw44wN9Vx6h99DlI177up5le//ocoM+Iutb0p8+NJAQQQAABBBCohEDGEBKeQAABBBBAAAEEEEAAAQQQQAABp4B+dex1UDl/Nen9F93fft555yV/xa5MvA6KhNdJmfx1q93PLjW0frZf1NqC6Nfk+fyyX6NU2F/U2nNpqW0aecHrBEjo19Aa2t37Ij9ZJ81Rr+R1+CS3BY8PruvX7eGkX/C7RpjQcTqXpn3Qr0M7d+6csp9+9StfJY0AYX85HzyfXdfQ8/bXwNpfo3TY5/JZqt42eR1RFcpD5/M6OGw2aUu1W9DXlk+/xtbUNho1w27T0Pz5prjbWdMm2fLmu/QCCfzq6RrJ91i7f/CXxdmuEbu/a6lRa4qZvI7PCtcvXN5ildPrvK1wGb2guGSxgtdvuOzZHrum23nggQecZZKnXuNex7A/pZEdwcnmH3zduKYqsftpqVEagik4ooh+fa9pIoL7a2QlLxjOP/cTTzyR0FQQXoBLyj6aDuTjjz8OZptzXVNc6LjgubSua1r3Bo0uoHOF95G317GaM/9C7eAF7qWVMVzmuB97wRBp1QuPKKKRHzTqlC2b7sHaphGXvICMhBdsktBIVRqxwe6jpd6/8xmxQwUp1D0+eC0Gy5RrXaMV2VQq74UaxSJXuTM9H57eTaP7XHDBBc789PrQKFxeMFNCo/UER/xQm3uBHT6Nrg/XKGm2DHrdRR15atCgQWll0bm8IFa/nPb9Pnh+2z52Gb5ebTlyLfU5KVfyAi0SXhBdWhmVt0Z10TWia1+jfrnOp3uoPlfkSpk+57nyDG5TGWzK9Xk6eFxwXe1FQgABBBBAAIHKCTD1TOX8OBoBBBBAAAEEEEAAAQQQQKCMBRTQoIAK2yEQ/ALbruuL7GzPa7/gFAjZOG3Hujoo80ka7l2dm1E6czXNioIlbKpooIg9Xh2M6nSzHpmWMvJGNkiocyOYNF1NuBNPeSi44vvvvw/u6ncS2fyVn+xVZ9VJHSvqANZjdTjredsuWtoUDBSxeWh/m4fy0bq2BdtWj73RI2w2zqUCSVzD7tsya6mOy4qmONvZ+6V7sk3zcVId1aGqZK9nbQvmoTZSW2Wy1v4aIt8mtYPNw+YTzkOPg+2l/b1fm9ssirK0bR2+DtWxZv/Uwak/+9jW2ZZX5cw2vVJlC66OQF3P1k9l1bUc9gtf79o/eK1qf20L5hPMw772wm3gjazkrII6vfVcMF+bf3ipqV7C0xrotaApwcL7qq6aLiWcbGepzmenWfBG9/Gvw3aikY0AAEAASURBVHAe4ce65mQRDFoL55/r8ejRoxOqRzjv8GP5qUPcG4EjV5YFfb4UA0Xmz5/vrKM10/uk2kR/3khU/uvfPpdpqfYPBxE5T5JhYyHu8cFAkUz3s/DrUddFMFBEARO2jsE87PuYfT0qHz2vP+2vpU2FeC8MBorYcuicKkeue7yCWF1J01cpyMGW2dbTtVQAgjcaTko23uhVzs8kcrdBjCkHZHmgz27hIK5wOYLvVeGsgoEi+fgo0DdqUmCxgj6ieOk60pRb9h4Y5RyaitDW2dYhyr0/U6BIMI9c12u+n4Wj1Id9EEAAAQQQKDcBpp7xPsmQEEAAAQQQQAABBBBAAAEEEKiMgDcSiBk8eLA/bYiGDc80ZLbO4X0JbrxftPrTothzeh2axhtZwz7MuNQ5zj33XH9aAk3VUpHkBV7407poeH8NN66pMTSUuaZK8DqpjYZdDw7h3q9fP39/DT2+5ZZbmq222spsscUW/rqmWdG6luFpEsJlW7hwofnkk0+M17nn/2nKCA0r73UE+H8a4nzTTTcNH5Z8rOHq58yZYzbZZBPzxz/+0R9uP/lkNVvR0OrvvPOOmTJlitHQ/JrGY4899jAail3LQqSqaudClJ08ELACmkpE0zx89dVX/n1DU6BomiFNy6TpeTR9lO5bmZKmSNF0OppyQtMMaX/XlGCaXuH111/3p17Q1Bc2eV8UG00RpWksvvjiC6MpUvR61X3Q61T1p4466KCDklNk2OMqulT9NEWRpnbS0guG86eyUH1139MUTq7yV/R8NfE4L5DGn7ZF02gE35e8oCijKVm8UV/M3Llz/aky9J6j9zD5anoiTeESfP+rqE8c9/iKlq2mHKfXol6X+iyh9tRnCy8oyH8P1ecKTRulds2UdE/RVCl6jeteor+KJB2ve5SmndFrVvcnXVO6ljS1lNZLIelzqu4r9t6ia1RJ9ztNCecFvBjdywpx/ZdCfSkDAggggAACCEQTIFAkmhN7IYAAAggggAACCCCAAAIIIBBJQJ0G6rSwQRgKGlFwiDoW9ef9mtb/It6bcsF402f4eep5zSmvIIhsyRt23XjD5Rvv16TGm/oj2648hwACCCCAAAIIIIAAAggggAACCCCAgFOAQBEnCxsRQAABBBBAAAEEEEAAAQQQKK7A3Xffbf71r38lT+INkW686QuSj8MrGlFDv/ZUUpBJ3759w7vwGAEEEEAAAQQQQAABBBBAAAEEEEAAgZwCBIrkJGIHBBBAAAEEEEAAAQQQQAABBAovoGkOTjjhhJSMNVrI+eefn7JNDzRCyZFHHukPsa7HGlq/S5cuWiUhgAACCCCAAAIIIIAAAggggAACCCCQlwCBInlxsTMCCCCAAAIIIIAAAggggAAChRH45ptv/Glowrm1a9fOtGnTxuy+++5m/vz5ZtiwYeamm25K2W3MmDHm6KOPTtnGAwQQQAABBBBAAAEEEEAAAQQQQAABBKIIECgSRYl9EEAAAQQQQAABBBBAAAEEECiCQMOGDc3kyZPzznnNmjVm/fXXz/s4DkAAAQQQQAABBBBAAAEEEEAAAQQQQIBAEa4BBBBAAAEEEEAAAQQQQAABBKpI4I477jA33nhjXmc/88wzzXPPPZfXMeyMAAIIIIAAAggggAACCCCAAAIIIICAFSBQxEqwRAABBBBAAAEEEEAAAQQQQCBmgalTp5oDDjggr7MOHjzYnH322Xkdw84IIIAAAggggAACCCCAAAIIIIAAAghYAQJFrARLBBBAAAEEEEAAAQQQQAABBKpA4JBDDjETJkyIdOYGDRqYiRMnmnXWWSfS/uyEAAIIIIAAAggggAACCCCAAAIIIIBAWIBAkbAIjxFAAAEEEEAAAQQQQAABBBCIUeCjjz4yjRo1inRG7XvQQQdF2pedEEAAAQQQQAABBBBAAAEEEEAAAQQQcAkQKOJSYRsCCCCAAAIIIIAAAggggAACMQq88MILplWrVhnPWLduXaN9mjVrlnEfnkAAAQQQQAABBBBAAAEEEEAAAQQQQCCKAIEiUZTYBwEEEEAAAQQQQAABBBBAAIEiC8yaNcvcf//95q233jLTpk3zz9a4cWNz9NFHm2uvvdZsueWWRS4B2SOAAAIIIIAAAggggAACCCCAAAIIlIMAgSLl0MrUEQEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQ8AQIFOEyQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEykSAQJEyaWiqiQACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIECjCNYAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCJSJAIEiZdLQVBMBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEECBQhGsAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBAoEwECRcqkoakmAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBAoAjXAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggUCYCBIqUSUNTTQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAgEARrgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQKBMBAgUKZOGppoIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggACBIlwDCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAmQgQKFImDU01EUAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBA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\" alt=\"Description of the figure\" style=\"max-width:50%; height:auto;display: block; margin: auto;\">\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72511671",
   "metadata": {},
   "source": [
    "For your reference, the tutorial of QPE in several major quantum computing libraries are listed below:\n",
    "\n",
    "* [Qiskit](https://github.com/qiskit-community/qiskit-textbook/blob/main/content/ch-algorithms/quantum-phase-estimation.ipynb)\n",
    "* [Pennylane](https://pennylane.ai/qml/demos/tutorial_qpe)\n",
    "* [CUDA-Q](https://nvidia.github.io/cuda-quantum/latest/specification/cudaq/examples.html#quantum-phase-estimation:~:text=Quantum%20Phase%20Estimation-,%C2%B6,-C%2B%2B)\n",
    "* [Cirq](https://quantumai.google/cirq/experiments/textbook_algorithms#phase_estimation)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "481e000c",
   "metadata": {},
   "source": [
    "**Example:**\n",
    "\n",
    "In our example, the probability of measuring all-zero states is approximately $p(0)=0.137 = \\tilde{\\beta}_k / 2^3 \\implies \\tilde{\\beta}_k = 1.096$, which is then rounded to $1$.\n",
    "\n",
    "**Action:**\n",
    "\n",
    "Utilize your preferred quantum computing library to apply QPE for estimating the number of zero eigenvalues in the Laplacian matrix. Note that the exponential of the Laplacian matrix is used as the unitary operator in QPE.\n",
    "\n",
    "**Answer:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "848ef40c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# write your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8724ca3",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\"> <b>NOTE</b>:\n",
    "\n",
    "The unitary operator can be constructed by converting the exponential matrix of the Laplacian into a quantum circuit. For instance, in Qiskit, this can be implemented using `circuit.unitary(exp_matrix)`. Alternative methods for constructing the unitary operator will be optionally explored in the **BONUS** section at the end of this notebook.\n",
    "</div>\n",
    "<div class=\"alert alert-block alert-danger\">\n",
    "    \n",
    "<b>BONUS EXERCISE:</b> \n",
    "\n",
    "1. Why we should measure all-zero states?\n",
    "2. What is the difference between a maximally mixed state and the $(H\\ket{0})^{\\otimes n}$ state? Two possible aspects are:\n",
    "\n",
    "* Plotting of their density matrix.\n",
    "* Results from QPE.\n",
    "\n",
    "3. What parameters affect the accuracy of the estimation before rounding? For Laplacian matrices of varying sizes, how does the accuracy depend on these parameters? Within what range of values do these parameters guarantee (or are highly likely to produce) a correct final result?\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cbe5cf2",
   "metadata": {},
   "source": [
    "### Step 4: Detecting market crashes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f27e81b",
   "metadata": {},
   "source": [
    "**Instruction:**\n",
    "\n",
    "At this point, we have betti curves for each window across our dataset, and we wish to use this to detect market crashes. One such way is to take the difference between these curves—or the pairwise distance—for successive windows and look for spikes. This can be done with the $L^p$ norm of the betti curve for each window, defined as follows:\n",
    "\n",
    "$$||x||_p = (\\sum_{n}^{i=1} |x_i|^p)^{1/p}$$\n",
    "\n",
    "Combining these pairwise distances into a vector, we get a single output curve we can analyze. Experiment with different values of $p$, but a good starting point is the $L^2$ Norm. Using this, it is possible to detect regions where a market crash is occuring. Comparing detected crashes with the price data indicates how accurate the crash detection methodology is ([ref](https://github.com/giotto-ai/stock-market-crashes/blob/master/Stock%20Market%20Crash%20Detection.ipynb)). \n",
    "\n",
    "**Action:**\n",
    "\n",
    "Use the $L^p$ norm to create pairwise distance curves for successive windows, and then use the results to define when a crash is occuring. Compare this with your data to see how well it performs. You may find the following classical solver is useful.\n",
    "\n",
    "**Answer:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5ef68f98",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ripser import ripser\n",
    "\n",
    "def classical_betti_solver(point_cloud, epsilon, dim):\n",
    "    '''Return the Betti number on a given point cloud.\n",
    "    Args:\n",
    "        point_cloud: the point cloud after applying the sliding window.\n",
    "        epsilon: resolution threshold.\n",
    "        dim: the dimension on which the Betti number is calculated\n",
    "    '''\n",
    "    result = ripser(point_cloud, maxdim=dim)\n",
    "    diagrams = result[\"dgms\"]\n",
    "    return len(\n",
    "        [interval for interval in diagrams[dim] if interval[0] < epsilon < interval[1]]\n",
    "    )\n",
    "\n",
    "# write your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1c2e4b5",
   "metadata": {},
   "source": [
    "## *BONUS:* Explore future directions of quantum TDA\n",
    "\n",
    "The following is a non-exhaustive list of possible next steps for the quantum TDA pipeline. It is recommended to at least explore 1 option or sub-option.\n",
    "\n",
    "- **Find more of applications of TDA in finance**:\n",
    "\n",
    "  There are several directions where to extend the analysis. Most work on time series analysis has used persistent homology, and more specifically, the $L^{P}$ norm of persistence landscapes, which can be used to detect early warning signals of imminent market crashes. This is precisely studied in the seminal work by Gidea and Katz, see [ref](https://arxiv.org/abs/1703.04385)\n",
    "    - Analyze financial correlation network and their degree of association with Betti curves or other topological features. From the time-series of multiple stock prices, we can build time-dependent correlation networks, which exhibit topological structures and might show some association to the evolution of betti curves or other topological data measures. Generally speaking, the cross correlations in a stock market will be in the form of a high-dimension topological space, with more complicated features. One can also think about other time varying financial graphs (e.g. cryptocurrencies). The following articles can help uncover more applications: \n",
    "  \n",
    "      - [Integral Betti signature confirms the hyperbolic geometry of brain, climate,and financial networks](https://www.arxiv.org/pdf/2406.15505)\n",
    "      - [Using Topological Data Analysis (TDA) and Persistent Homology to Analyze the Stock Markets in Singapore and Taiwan](https://www.frontiersin.org/journals/physics/articles/10.3389/fphy.2021.572216/full)\n",
    "    - Build a ML classifier or regressor on top of vectorized features such as Betti Curves (given their potential to identify trends, patterns or potential turning points in the market) to help with investment or risk management strategies. Show that Betti curves have some predictive skill, as key topological descriptors. See [ref1](https://arxiv.org/abs/2411.13881) and [ref2](https://www.sciencedirect.com/science/article/pii/S2405918823000235) for further information on the topic.\n",
    "- **A hybrid and more NISQ-friendly quantum TDA pipeline**:\n",
    "  \n",
    "  QPE remains primarily theoretical. Its circuits are simply too deep to run on real hardware. Come up an with iterative or hybrid quantum phase estimation protocol or use tools that increase the algorithmic performance when running quantum circuits on real hardware. Benchmark them against textbook-QPE circuits. Here are some proposals to subtitute the QPE part:\n",
    "    - Variational Quantum Deflation (VQD) Algorithm: VQD is a quantum algorithm that uses a variational technique to find the k eigenvalues of the Hamiltonian H of a given system. [ref](https://quantum-journal.org/papers/q-2019-07-01-156/)\n",
    "    - Variational Quantum Eigensolver (VQE): Using VQE to determine the spectra of adjancency or laplacian matrix. Inspired by: [ref](https://arxiv.org/pdf/1912.12366)\n",
    "  \n",
    "  Finally, run some circuits on simulator + real hardware and compare the performance (runtime, noise effects, # resources) of the new proposal to the QPE solution of the above sections.\n",
    "\n",
    "- **A proper procedure of encoding the Laplacian matrix to the unitary**:\n",
    "\n",
    "  In Step 3, encoding the exponential matrix is recommanded. An alternative approach is to conduct the Paulis decomposition on the Laplacian, then followed by Trotterization. Can you implement this approach in your pipeline? What parameters influence the accuracy? Can you optimize your code to minimize the circuit depth?\n",
    "\n",
    "- **Extend the quantum TDA to extract persistent Betti numbers**: \n",
    "  \n",
    "  Implement a quantum TDA algorithm for persistent Betti numbers. Esstimating the persistent Betti numbers is a more general task than estimating the Betti number and it is more practical for TDA. It is an open problem to construct a quantum algorithm for the persistent Betti numbers in a way that is preferable for NISQ devices, and the only current implementation of a quantum algorithm for persistent betti number is shown [here](https://quantum-journal.org/papers/q-2022-12-07-873/pdf/)."
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    "# This is the end of the challenge. Good luck!"
   ]
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