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AnnePicusclassiqdor
AnnePicus
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classiqdor
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Minor English fixes to autocallable notebooks
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‎applications/finance/autocallable_options/partial_exponential_state_preparation.ipynb‎

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"id": "d0de1527-21cb-4a77-a1de-83e85569fc2f",
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"metadata": {},
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"source": [
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"# Prepare partial exponential state"
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"# Prepare Partial Exponential State"
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]
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},
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{
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"$$ |\\psi\\rangle = \\sum_{x_0}^{x_1}\\sqrt{\\frac{e^{-ar}}{Z}}|r\\rangle $$\n",
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"$$Z = \\sum_{x_0}^{x_1}\\sqrt{e^{-ar}}$$\n",
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"\n",
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"The methodology is to load the state on the full range of states, then use exact amplitude amplification to leave only the wanted part."
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"The methodology is to load the state on the full range of states, then use exact amplitude amplification to leave only the wanted part:"
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]
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},
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{
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"id": "bd93edb0-5acd-413e-80dd-25d593a58345",
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"metadata": {},
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"source": [
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"## Exponential state preparation on the full interval"
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"## Exponential State Preparation on the Full Interval"
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]
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},
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{
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"id": "079d2624-8ad5-44ea-a5d2-6644ba2e99a3",
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"metadata": {},
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"source": [
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"## Exp State on a specific interval with Exact Amplitude Amplification"
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"## Exp State on a Specific Interval with Exact Amplitude Amplification"
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]
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},
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{
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"id": "8edce582-89f8-4d19-aff4-375603c94308",
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"metadata": {},
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"source": [
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"### Adjust to the case that a single grover is not enough\n",
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"### Adjusting If a Single Grover is Not Enough\n",
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"\n",
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"If the wanted range does not hold enough amplitude, it is enough to load the end of the range (for positive `EXP_RATE`) or the beginning of the range (for negative `EXP_RATE`), then finish with a modular adder."
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"If the desired range does not hold enough amplitude, it is enough to load the end of the range (for a positive `EXP_RATE`) or the beginning of the range (for a negative `EXP_RATE`), then finish with a modular adder:"
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]
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},
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{
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"id": "f03aa802-2c23-4b89-aeab-db31a58ae5ba",
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"metadata": {},
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"source": [
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"This fraction of good states is not enough for a single grover iteration to amplify to 1. So we first load the same sized interval at the end of the range:"
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"This fraction of good states is not enough for a single Grover iteration to amplify to 1. So, first load the same sized interval at the end of the range:"
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]
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},
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{
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"id": "7c3e6647-fafc-41fc-84d2-72070ca01f9d",
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"metadata": {},
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"source": [
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"Verify the results:"
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"### Verifying the Results"
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]
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},
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{

‎applications/finance/autocallable_options/quantum_autocallable_option_pricing.ipynb‎

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"metadata": {},
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"source": [
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"# Autocallables with Integration Amplitude Loading\n",
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"In this Notebook we will go through the implementation of the Integration Amplitude Loading Method for the autocallables based on https://arxiv.org/pdf/2402.05574.pdf and https://arxiv.org/pdf/2012.03819 using classiq platform QMOD language."
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"This notebook covers the implementation of the Integration Amplitude Loading Method for the autocallables based on [[1]](#QALROP) and [[2]](#TQA) using the Classiq platform's Qmod language."
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]
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{
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"execution_count": 39,
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"id": "7c206d17",
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2025-06-22T15:37:58.815349Z",
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"start_time": "2025-06-22T15:37:58.800464Z"
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},
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"collapsed": false,
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"jupyter": {
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"outputs_hidden": false
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}
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},
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"outputs": [],
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"id": "4d310535",
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"metadata": {},
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"source": [
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"## Gaussian State preparation"
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"## Gaussian State Preparation"
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]
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},
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{
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"id": "2ff92132",
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"metadata": {},
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"source": [
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"Compute $R_T^{max}$ resulting from discretization."
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"Compute $R_T^{max}$ resulting from discretization:"
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]
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},
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{
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"id": "7e2ec6ab",
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"metadata": {},
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"source": [
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"In two's complement, given $N$ as number of qubits, we can represent from $-2^{N-1}$ and $2^{N-1}-1$."
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"In two's complement, given $N$ as the number of qubits, represent from $-2^{N-1}$ and $2^{N-1}-1$:"
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]
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},
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{
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"id": "9720568b",
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"metadata": {},
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"source": [
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"### Compute constant rotations"
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"## Compute Constant Rotations"
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]
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},
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{
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"cell_type": "markdown",
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"id": "02902fd7",
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"metadata": {
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"collapsed": false
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"collapsed": false,
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"jupyter": {
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"outputs_hidden": false
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}
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},
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"source": [
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"## Verifications"
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"outputs": [
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{
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"data": {
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"text/plain": "1.9215788783046464"
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"text/plain": [
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"1.9215788783046464"
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]
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},
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"execution_count": 50,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": "1.9215788783046523"
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"text/plain": [
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"1.9215788783046523"
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]
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},
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"execution_count": 51,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": "2.7693490391599074"
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"text/plain": [
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"2.7693490391599074"
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]
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},
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"execution_count": 52,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": "2.7693490391599074"
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"text/plain": [
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"2.7693490391599074"
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]
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},
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"execution_count": 53,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": "1.7763568394002505e-15"
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"text/plain": [
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"1.7763568394002505e-15"
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]
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},
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"execution_count": 54,
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"metadata": {},
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"tags": []
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},
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"source": [
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"## Integration Method circuit synthesis"
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"## Integration Method Circuit Synthesis"
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]
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},
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"execution_count": 68,
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"id": "07f52524",
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2025-06-22T15:38:00.096570Z",
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"start_time": "2025-06-22T15:38:00.029467Z"
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},
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"collapsed": false,
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"jupyter": {
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"outputs_hidden": false
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}
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},
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"outputs": [],
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"id": "194c5c2f",
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"metadata": {},
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"source": [
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"## IQAE functions and QStruct"
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"## IQAE Functions and QStruct"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 69,
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"id": "c62677d3",
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2025-06-22T15:38:00.099770Z",
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"start_time": "2025-06-22T15:38:00.069101Z"
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},
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"collapsed": false,
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"jupyter": {
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"outputs_hidden": false
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}
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"outputs": [],
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"id": "2aa62bc4",
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"metadata": {},
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"source": [
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"## Base simulator sythesis"
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"## Base Simulator Synthesis"
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]
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},
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{
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"execution_count": 71,
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"id": "bb4c7d89",
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2025-06-22T15:38:45.852317Z",
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"start_time": "2025-06-22T15:38:45.785258Z"
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},
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"collapsed": false,
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"jupyter": {
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"outputs_hidden": false
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"outputs": [
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"id": "95d7c365",
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"metadata": {},
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"source": [
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"### Execution takes a lot of time\n",
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"See the results below"
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"Execution takes a lot of time. \n",
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"Examine the results:"
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]
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"execution_count": 74,
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"id": "5a474534",
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2025-06-22T15:38:45.924205Z",
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"start_time": "2025-06-22T15:38:45.827303Z"
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},
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"collapsed": false,
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"jupyter": {
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"outputs_hidden": false
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}
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"outputs": [
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" + str(postprocessing(0.1197666))\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d840bf68-8161-47a6-a106-a39549471b46",
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"metadata": {},
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"source": [
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"## References\n",
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"\n",
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"<a name='QALROP'>[1]</a> [Francesca Cibrario et al. (2024). Quantum Amplitude Loading for Rainbow Options Pricing. Preprint.](https://arxiv.org/abs/2402.05574v2)\n",
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"\n",
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"<a name='TQA'>[2]</a> [Shouvanik Chakrabarti et al. (2021). A Threshold for Quantum Advantage in Derivative Pricing, Quantum 5, 463.](https://arxiv.org/pdf/2012.03819)\n",
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" "
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]
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}
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],
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"metadata": {

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