microsoft/qdk
Publicmirrored fromhttps://github.com/microsoft/qdkAvailable
samples/estimation/estimation-factoring.ipynb
101lines · modecode
| 1 | { |
| 2 | "cells": [ |
| 3 | { |
| 4 | "cell_type": "markdown", |
| 5 | "metadata": {}, |
| 6 | "source": [ |
| 7 | "# Resource Estimation for Integer Factoring\n", |
| 8 | "\n", |
| 9 | "In this notebook we calculate resource estimates for a 2048-bit integer factoring application based on the implementation described in [[Quantum 5, 433 (2021)](https://quantum-journal.org/papers/q-2021-04-15-433/)]. Our implementation incorporates all techniques described in the paper, except for carry runways and semi-classical Fourier transform. As tolerated error budget, we choose $\\epsilon = 1/3$.\n", |
| 10 | "\n", |
| 11 | "We start by loading the Q# implementation of the algorithm." |
| 12 | ] |
| 13 | }, |
| 14 | { |
| 15 | "cell_type": "code", |
| 16 | "execution_count": null, |
| 17 | "metadata": {}, |
| 18 | "outputs": [], |
| 19 | "source": [ |
| 20 | "import qsharp\n", |
| 21 | "from qsharp_widgets import EstimatesOverview\n", |
| 22 | "\n", |
| 23 | "with open(\"EkeraHastadFactoring.qs\", \"r\") as f:\n", |
| 24 | " qsharp.eval(f.read())" |
| 25 | ] |
| 26 | }, |
| 27 | { |
| 28 | "cell_type": "markdown", |
| 29 | "metadata": {}, |
| 30 | "source": [ |
| 31 | "Here are some RSA integers to choose from, taken from this [extensive list](https://en.wikipedia.org/wiki/RSA_numbers#RSA-2048). Add and remove comments to pick the number you'd like to estimate, and feel free to add other numbers." |
| 32 | ] |
| 33 | }, |
| 34 | { |
| 35 | "cell_type": "code", |
| 36 | "execution_count": null, |
| 37 | "metadata": {}, |
| 38 | "outputs": [], |
| 39 | "source": [ |
| 40 | "# RSA-100 (330 bits)\n", |
| 41 | "rsa_number = 1522605027922533360535618378132637429718068114961380688657908494580122963258952897654000350692006139\n", |
| 42 | "\n", |
| 43 | "# RSA-1024 (1024 bits)\n", |
| 44 | "# rsa_number = 135066410865995223349603216278805969938881475605667027524485143851526510604859533833940287150571909441798207282164471551373680419703964191743046496589274256239341020864383202110372958725762358509643110564073501508187510676594629205563685529475213500852879416377328533906109750544334999811150056977236890927563\n", |
| 45 | "\n", |
| 46 | "# RSA-2048 (2048 bits)\n", |
| 47 | "# rsa_number = 25195908475657893494027183240048398571429282126204032027777137836043662020707595556264018525880784406918290641249515082189298559149176184502808489120072844992687392807287776735971418347270261896375014971824691165077613379859095700097330459748808428401797429100642458691817195118746121515172654632282216869987549182422433637259085141865462043576798423387184774447920739934236584823824281198163815010674810451660377306056201619676256133844143603833904414952634432190114657544454178424020924616515723350778707749817125772467962926386356373289912154831438167899885040445364023527381951378636564391212010397122822120720357" |
| 48 | ] |
| 49 | }, |
| 50 | { |
| 51 | "cell_type": "markdown", |
| 52 | "metadata": {}, |
| 53 | "source": [ |
| 54 | "Next, we estimate the resource estimates for all default qubit parameter configurations." |
| 55 | ] |
| 56 | }, |
| 57 | { |
| 58 | "cell_type": "code", |
| 59 | "execution_count": null, |
| 60 | "metadata": {}, |
| 61 | "outputs": [], |
| 62 | "source": [ |
| 63 | "estimates = qsharp.estimate(f\"EkeraHastad({rsa_number.bit_length()}, {rsa_number}L, 7L)\", [\n", |
| 64 | " {\"errorBudget\": 0.333, \"qubitParams\": {\"name\": \"qubit_gate_ns_e3\"}},\n", |
| 65 | " {\"errorBudget\": 0.333, \"qubitParams\": {\"name\": \"qubit_gate_ns_e4\"}},\n", |
| 66 | " {\"errorBudget\": 0.333, \"qubitParams\": {\"name\": \"qubit_gate_us_e3\"}},\n", |
| 67 | " {\"errorBudget\": 0.333, \"qubitParams\": {\"name\": \"qubit_gate_us_e4\"}},\n", |
| 68 | " {\"errorBudget\": 0.333, \"qubitParams\": {\"name\": \"qubit_maj_ns_e4\"}, \"qecScheme\": {\"name\": \"floquet_code\"}},\n", |
| 69 | " {\"errorBudget\": 0.333, \"qubitParams\": {\"name\": \"qubit_maj_ns_e6\"}, \"qecScheme\": {\"name\": \"floquet_code\"}}\n", |
| 70 | "])" |
| 71 | ] |
| 72 | }, |
| 73 | { |
| 74 | "cell_type": "markdown", |
| 75 | "metadata": {}, |
| 76 | "source": [ |
| 77 | "And finally, we present all resource estimates in an overview table and space-time plot." |
| 78 | ] |
| 79 | }, |
| 80 | { |
| 81 | "cell_type": "code", |
| 82 | "execution_count": null, |
| 83 | "metadata": {}, |
| 84 | "outputs": [], |
| 85 | "source": [ |
| 86 | "EstimatesOverview(\n", |
| 87 | " estimates,\n", |
| 88 | " colors=[\"#1f77b4\", \"#ff7f0e\", \"blue\", \"red\", \"green\", \"yellow\"],\n", |
| 89 | " runNames=[\"Gate ns e3, surface\", \"Gate ns e4, surface\", \"Gate us e3, surface\", \"Gate us e4, surface\", \"Majorana ns e4, floquet\", \"Majorana ns e6, floquet\"]\n", |
| 90 | ")" |
| 91 | ] |
| 92 | } |
| 93 | ], |
| 94 | "metadata": { |
| 95 | "language_info": { |
| 96 | "name": "python" |
| 97 | } |
| 98 | }, |
| 99 | "nbformat": 4, |
| 100 | "nbformat_minor": 4 |
| 101 | } |
| 102 | |