├── .gitignore ├── LICENSE ├── Q Notes.pdf ├── Qiskit ├── Q Notes.pdf ├── Qiskit.ipynb ├── README.md ├── Resources.ipynb └── Scratch.ipynb ├── README.md ├── Ryan30 ├── Notes.md ├── ch.1 │ ├── atoms-computation.ipynb │ ├── chapter1-practice-file.ipynb │ └── representing-qubit-states.ipynb └── setting-the-environment.ipynb ├── SunilK ├── BlochSphereAnimation.ipynb ├── Local Module Test.ipynb ├── bloch_anim.gif └── mymodules │ └── hello.py ├── Touny.md └── minhpham ├── Chapter 1 Code.ipynb ├── Chapter 1 Edit.pdf ├── Chapter 2 Edit.pdf ├── Q Notes.pdf ├── Qiskit.ipynb ├── README.md ├── Resources.ipynb └── Scratch.ipynb /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | pip-wheel-metadata/ 24 | share/python-wheels/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | MANIFEST 29 | 30 | # PyInstaller 31 | # Usually these files are written by a python script from a template 32 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 33 | *.manifest 34 | *.spec 35 | 36 | # Installer logs 37 | pip-log.txt 38 | pip-delete-this-directory.txt 39 | 40 | # Unit test / coverage reports 41 | htmlcov/ 42 | .tox/ 43 | .nox/ 44 | .coverage 45 | .coverage.* 46 | .cache 47 | nosetests.xml 48 | coverage.xml 49 | *.cover 50 | *.py,cover 51 | .hypothesis/ 52 | .pytest_cache/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | target/ 76 | 77 | # Jupyter Notebook 78 | .ipynb_checkpoints 79 | 80 | # IPython 81 | profile_default/ 82 | ipython_config.py 83 | 84 | # pyenv 85 | .python-version 86 | 87 | # pipenv 88 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 89 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 90 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 91 | # install all needed dependencies. 92 | #Pipfile.lock 93 | 94 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 95 | __pypackages__/ 96 | 97 | # Celery stuff 98 | celerybeat-schedule 99 | celerybeat.pid 100 | 101 | # SageMath parsed files 102 | *.sage.py 103 | 104 | # Environments 105 | .env 106 | .venv 107 | env/ 108 | venv/ 109 | ENV/ 110 | env.bak/ 111 | venv.bak/ 112 | 113 | # Spyder project settings 114 | .spyderproject 115 | .spyproject 116 | 117 | # Rope project settings 118 | .ropeproject 119 | 120 | # mkdocs documentation 121 | /site 122 | 123 | # mypy 124 | .mypy_cache/ 125 | .dmypy.json 126 | dmypy.json 127 | 128 | # Pyre type checker 129 | .pyre/ 130 | 131 | 132 | # Apple folder stuff 133 | .DS_Store 134 | 135 | *.swp 136 | *.map 137 | 138 | config.rst 139 | *.iml 140 | /.project 141 | /.pydevproject 142 | 143 | package-lock.json 144 | geckodriver.log 145 | *.iml 146 | 147 | # jetbrains IDE stuff 148 | *.iml 149 | .idea/ 150 | 151 | # vscode IDE stuff 152 | *.code-workspace 153 | .history 154 | .vscode 155 | 156 | 157 | /.vs/QCStudyGroup/v16/TestStore/0/000.testlog 158 | /.vs/ProjectSettings.json 159 | /.vs/slnx.sqlite 160 | /.vs/QCStudyGroup/v16/.suo 161 | .vs/VSWorkspaceState.json 162 | 163 | 164 | # temp files for animations 165 | */temp_file.png 166 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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-------------------------------------------------------------------------------- https://raw.githubusercontent.com/sktxdev/Quantum-Computing/2d72a87d4b8268fafed8f1509d558d6625ef3adc/Q Notes.pdf -------------------------------------------------------------------------------- /Qiskit/Q Notes.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sktxdev/Quantum-Computing/2d72a87d4b8268fafed8f1509d558d6625ef3adc/Qiskit/Q Notes.pdf -------------------------------------------------------------------------------- /Qiskit/README.md: -------------------------------------------------------------------------------- 1 | Storing mathematical proofs of circuit components in quantum algorithms. 2 | -------------------------------------------------------------------------------- /Qiskit/Scratch.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "# IMPORT THIS!!!" 8 | ] 9 | }, 10 | { 11 | "cell_type": "code", 12 | "execution_count": 3, 13 | "metadata": {}, 14 | "outputs": [ 15 | { 16 | "name": "stderr", 17 | "output_type": "stream", 18 | "text": [ 19 | "Duplicate key in file '/Users/minhpham/.matplotlib/matplotlibrc' line #2.\n", 20 | "Duplicate key in file '/Users/minhpham/.matplotlib/matplotlibrc' line #3.\n" 21 | ] 22 | } 23 | ], 24 | "source": [ 25 | "import numpy as np\n", 26 | "import matplotlib\n", 27 | "import matplotlib.pyplot as plt\n", 28 | "import scipy.integrate as integrate\n", 29 | "import quadpy\n", 30 | "import random\n", 31 | "import math" 32 | ] 33 | }, 34 | { 35 | "cell_type": "code", 36 | "execution_count": 247, 37 | "metadata": {}, 38 | "outputs": [ 39 | { 40 | "data": { 41 | "text/plain": [ 42 | "(5, 73, 365, 309)" 43 | ] 44 | }, 45 | "execution_count": 247, 46 | "metadata": {}, 47 | "output_type": "execute_result" 48 | } 49 | ], 50 | "source": [ 51 | "p = random.choice(prime_list)\n", 52 | "q = random.choice(prime_list)\n", 53 | "M = p*q\n", 54 | "guess = random.randint(2, M)\n", 55 | "\n", 56 | "p, q, M, guess" 57 | ] 58 | }, 59 | { 60 | "cell_type": "code", 61 | "execution_count": 248, 62 | "metadata": {}, 63 | "outputs": [], 64 | "source": [ 65 | "def Shor(M, guess): \n", 66 | " pf = lambda guess, M: np.array([guess**b%M for b in range(2, 5000)]) \n", 67 | " \n", 68 | " if math.gcd(M, guess) !=1: \n", 69 | " \n", 70 | " return math.gcd(M, guess), int(M/math.gcd(M, guess)) \n", 71 | " \n", 72 | " peak = np.where(pf(guess, M)==1)[0]\n", 73 | " \n", 74 | " r = peak[1]-peak[0] \n", 75 | " return math.gcd(M, int(guess**(r/2)-1)), math.gcd(M, int(guess**(r/2)+1))" 76 | ] 77 | }, 78 | { 79 | "cell_type": "code", 80 | "execution_count": 249, 81 | "metadata": {}, 82 | "outputs": [ 83 | { 84 | "data": { 85 | "text/plain": [ 86 | "(1, 1)" 87 | ] 88 | }, 89 | "execution_count": 249, 90 | "metadata": {}, 91 | "output_type": "execute_result" 92 | } 93 | ], 94 | "source": [ 95 | "Shor(M, guess)" 96 | ] 97 | }, 98 | { 99 | "cell_type": "code", 100 | "execution_count": 246, 101 | "metadata": {}, 102 | "outputs": [ 103 | { 104 | "data": { 105 | "text/plain": [ 106 | "(array([ 2, 6, 10, ..., 4986, 4990, 4994]),)" 107 | ] 108 | }, 109 | "execution_count": 246, 110 | "metadata": {}, 111 | "output_type": "execute_result" 112 | } 113 | ], 114 | "source": [ 115 | "np.where(np.array([guess**r%M for r in range(2, 5000)]) ==1)" 116 | ] 117 | }, 118 | { 119 | "cell_type": "code", 120 | "execution_count": 236, 121 | "metadata": {}, 122 | "outputs": [ 123 | { 124 | "data": { 125 | "text/plain": [ 126 | "1" 127 | ] 128 | }, 129 | "execution_count": 236, 130 | "metadata": {}, 131 | "output_type": "execute_result" 132 | } 133 | ], 134 | "source": [ 135 | "math.gcd(M, 31-1)" 136 | ] 137 | }, 138 | { 139 | "cell_type": "code", 140 | "execution_count": 1, 141 | "metadata": {}, 142 | "outputs": [ 143 | { 144 | "name": "stderr", 145 | "output_type": "stream", 146 | "text": [ 147 | "Duplicate key in file '/Users/minhpham/.matplotlib/matplotlibrc' line #2.\n", 148 | "Duplicate key in file '/Users/minhpham/.matplotlib/matplotlibrc' line #3.\n" 149 | ] 150 | } 151 | ], 152 | "source": [ 153 | "from qiskit import *" 154 | ] 155 | }, 156 | { 157 | "cell_type": "code", 158 | "execution_count": 80, 159 | "metadata": {}, 160 | "outputs": [ 161 | { 162 | "data": { 163 | "text/plain": [ 164 | "" 165 | ] 166 | }, 167 | "execution_count": 80, 168 | "metadata": {}, 169 | "output_type": "execute_result" 170 | } 171 | ], 172 | "source": [ 173 | "circuit = QuantumCircuit(3, 3)\n", 174 | "circuit.h([0, 1, 2])\n", 175 | "circuit.measure([0, 1, 2], [0, 1, 2])" 176 | ] 177 | }, 178 | { 179 | "cell_type": "code", 180 | "execution_count": 81, 181 | "metadata": {}, 182 | "outputs": [], 183 | "source": [ 184 | "%matplotlib inline " 185 | ] 186 | }, 187 | { 188 | "cell_type": "code", 189 | "execution_count": 144, 190 | "metadata": {}, 191 | "outputs": [ 192 | { 193 | "data": { 194 | "image/png": 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\n", 195 | "text/plain": [ 196 | "
" 197 | ] 198 | }, 199 | "execution_count": 144, 200 | "metadata": {}, 201 | "output_type": "execute_result" 202 | } 203 | ], 204 | "source": [ 205 | "circuit.draw(output = 'mpl')" 206 | ] 207 | }, 208 | { 209 | "cell_type": "code", 210 | "execution_count": null, 211 | "metadata": {}, 212 | "outputs": [], 213 | "source": [ 214 | "provider = IBMQ.get_provider('ibm-q')\n", 215 | "\n", 216 | "qcomp = provider.get_backend('ibmq_vigo', )\n", 217 | "\n", 218 | "job = execute(circuit, backend = qcomp, shots = 1)\n", 219 | "\n", 220 | "job_monitor(job)\n", 221 | "\n", 222 | "results = job.result()\n", 223 | "\n", 224 | "plot_histogram(results.get_counts(circuit))" 225 | ] 226 | }, 227 | { 228 | "cell_type": "code", 229 | "execution_count": null, 230 | "metadata": {}, 231 | "outputs": [], 232 | "source": [ 233 | "a = list(results.get_counts().keys())[0]\n", 234 | "int(a, 2)" 235 | ] 236 | }, 237 | { 238 | "cell_type": "code", 239 | "execution_count": null, 240 | "metadata": {}, 241 | "outputs": [], 242 | "source": [] 243 | } 244 | ], 245 | "metadata": { 246 | "kernelspec": { 247 | "display_name": "Python 3", 248 | "language": "python", 249 | "name": "python3" 250 | }, 251 | "language_info": { 252 | "codemirror_mode": { 253 | "name": "ipython", 254 | "version": 3 255 | }, 256 | "file_extension": ".py", 257 | "mimetype": "text/x-python", 258 | "name": "python", 259 | "nbconvert_exporter": "python", 260 | "pygments_lexer": "ipython3", 261 | "version": "3.7.4" 262 | } 263 | }, 264 | "nbformat": 4, 265 | "nbformat_minor": 4 266 | } 267 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # QCStudyGroup 2 | QC Study Group Github Repository 3 | 4 | ## Resources 5 | 6 | | Title | Study Resources | Contributor | 7 | | ------| --------------- | ----------- | 8 | | QISKIT Book | https://qiskit.org/textbook/preface.html | | 9 | | Quantum algorithms for NLP: LSA, QSFA and CA | https://www.youtube.com/watch?v=d-Lfdfy-xw8 | | 10 | | Awesome Quantum Machine Learning | https://github.com/krishnakumarsekar/awesome-quantum-machine-learning (Thanks Ryan)| | 11 | | Quantum Logic and Probability Theory | https://plato.stanford.edu/entries/qt-quantlog/ | Ryan30 | 12 | | More Rigorous Overview of the Maths and Computer Science behind the algorithms | https://lapastillaroja.net/wp-content/uploads/2016/09/Intro_to_QC_Vol_1_Loceff.pdf | 13 | |Michael A. Nielsen & Isaac L. Chuang, “Quantum Computation and Quantum Information”| http://mmrc.amss.cas.cn/tlb/201702/W020170224608149940643.pdf | 14 | |Noson S. Yanofsky & Mirco A. Mannucci, “Quantum Computing for Computer Scientist”| https://www.mobt3ath.com/uplode/book/book-71712.pdf | 15 | |Abhijith J., et al., “Quantum Algorithm Implementations for Beginners”|https://arxiv.org/pdf/1804.03719.pdf | 16 | |Professor Vazirani's Video |https://www.youtube.com/channel/UCq9B8tT3oXl8BSyaoBPQXQw/playlists | 17 | |Guest Speaker Scott Aaronson, "Quantum Computing Since Democritus"| https://github.com/dmvaldman/library/blob/master/computer%20science/Aaronson%20-%20Quantum%20Computing%20Since%20Democritus.pdf| 18 | 19 | Add to this list as you see fit. 20 | 21 | 22 | 23 | My technique for learning. 24 | Watch a video on the topic I'm interested on, and do a deep dive if I dont understand something, until I'm satisfyed with my knowledge, then resurface and continue. Sometimes this can turn into as little as one slide or a couple of minutes of watching a segment of the video and a couple of days of filling in background knowledge. 25 | 26 | 27 | ## General 28 | 29 | For code editing I'll try to add juypter notebooks, but will use vscode for editing things like readme's and gitignore etc.,. 30 | 31 | If you wish to contribute on the markdown (this file), feel free to do so. I recommend a markdown previewer such as Markdown Preview Enhanced if you're using vscode. 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | -------------------------------------------------------------------------------- /Ryan30/Notes.md: -------------------------------------------------------------------------------- 1 | #I had access control issues when running the install command but it worked after using 2 | #the --user option 3 | pip3 install qiskit --user 4 | 5 | References: 6 | https://qiskit.org/textbook/ch-prerequisites/setting-the-environment.html 7 | https://qiskit.org/textbook/ch-appendix/linear_algebra.html -------------------------------------------------------------------------------- /Ryan30/ch.1/chapter1-practice-file.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [ 8 | { 9 | "data": { 10 | "text/html": [ 11 | "
     ┌─┐                     \n",
 12 |        "q_0: ┤M├─────────────────────\n",
 13 |        "     └╥┘┌─┐                  \n",
 14 |        "q_1: ─╫─┤M├──────────────────\n",
 15 |        "      ║ └╥┘┌─┐               \n",
 16 |        "q_2: ─╫──╫─┤M├───────────────\n",
 17 |        "      ║  ║ └╥┘┌─┐            \n",
 18 |        "q_3: ─╫──╫──╫─┤M├────────────\n",
 19 |        "      ║  ║  ║ └╥┘┌─┐         \n",
 20 |        "q_4: ─╫──╫──╫──╫─┤M├─────────\n",
 21 |        "      ║  ║  ║  ║ └╥┘┌─┐      \n",
 22 |        "q_5: ─╫──╫──╫──╫──╫─┤M├──────\n",
 23 |        "      ║  ║  ║  ║  ║ └╥┘┌─┐   \n",
 24 |        "q_6: ─╫──╫──╫──╫──╫──╫─┤M├───\n",
 25 |        "      ║  ║  ║  ║  ║  ║ └╥┘┌─┐\n",
 26 |        "q_7: ─╫──╫──╫──╫──╫──╫──╫─┤M├\n",
 27 |        "      ║  ║  ║  ║  ║  ║  ║ └╥┘\n",
 28 |        "c: 8/═╩══╩══╩══╩══╩══╩══╩══╩═\n",
 29 |        "      0  1  2  3  4  5  6  7
" 30 | ], 31 | "text/plain": [ 32 | " ┌─┐ \n", 33 | "q_0: ┤M├─────────────────────\n", 34 | " └╥┘┌─┐ \n", 35 | "q_1: ─╫─┤M├──────────────────\n", 36 | " ║ └╥┘┌─┐ \n", 37 | "q_2: ─╫──╫─┤M├───────────────\n", 38 | " ║ ║ └╥┘┌─┐ \n", 39 | "q_3: ─╫──╫──╫─┤M├────────────\n", 40 | " ║ ║ ║ └╥┘┌─┐ \n", 41 | "q_4: ─╫──╫──╫──╫─┤M├─────────\n", 42 | " ║ ║ ║ ║ └╥┘┌─┐ \n", 43 | "q_5: ─╫──╫──╫──╫──╫─┤M├──────\n", 44 | " ║ ║ ║ ║ ║ └╥┘┌─┐ \n", 45 | "q_6: ─╫──╫──╫──╫──╫──╫─┤M├───\n", 46 | " ║ ║ ║ ║ ║ ║ └╥┘┌─┐\n", 47 | "q_7: ─╫──╫──╫──╫──╫──╫──╫─┤M├\n", 48 | " ║ ║ ║ ║ ║ ║ ║ └╥┘\n", 49 | "c: 8/═╩══╩══╩══╩══╩══╩══╩══╩═\n", 50 | " 0 1 2 3 4 5 6 7 " 51 | ] 52 | }, 53 | "execution_count": 1, 54 | "metadata": {}, 55 | "output_type": "execute_result" 56 | } 57 | ], 58 | "source": [ 59 | "#practice file for the qiskit book: https://qiskit.org/textbook/ch-states/introduction.html\n", 60 | "#Author: Ryan30\n", 61 | "#Date: 2020-10-25\n", 62 | "\n", 63 | "\n", 64 | "#https://qiskit.org/textbook/ch-states/atoms-computation.html\n", 65 | "#ch 1.2 - Atoms of computation\n", 66 | "\n", 67 | "#try the widget out\n", 68 | "#from qiskit_textbook.widgets import binary_widget\n", 69 | "#binary_widget(nbits=6)\n", 70 | "\n", 71 | "#Example 3 - First quantum circuit\n", 72 | "#import QC modules\n", 73 | "from qiskit import QuantumCircuit, execute, Aer\n", 74 | "from qiskit.visualization import plot_histogram\n", 75 | "\n", 76 | "#word of advice dont put a number this large because the server crashed, lol.\n", 77 | "#n = 8000\n", 78 | "\n", 79 | "n = 8\n", 80 | "#this represents the number of qubits in the circuit\n", 81 | "n_q = n\n", 82 | "\n", 83 | "#this represents the number of outputs in the circuit\n", 84 | "n_b = n\n", 85 | "qc_out = QuantumCircuit(n_q,n_b)\n", 86 | "\n", 87 | "for j in range(n):\n", 88 | " qc_out.measure(j,j)\n", 89 | " \n", 90 | "qc_out.draw()\n" 91 | ] 92 | }, 93 | { 94 | "cell_type": "code", 95 | "execution_count": 2, 96 | "metadata": {}, 97 | "outputs": [ 98 | { 99 | "data": { 100 | "image/png": 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\n", 101 | "text/plain": [ 102 | "
" 103 | ] 104 | }, 105 | "execution_count": 2, 106 | "metadata": {}, 107 | "output_type": "execute_result" 108 | } 109 | ], 110 | "source": [ 111 | "#According to the book we have initialized our qubits to output 0 and we can see that the result is all zeroes\n", 112 | "#based on the input so n= 8 has 8 zeros, etc. \n", 113 | "#TODO: read up on the Aer module. It looks like you can swap out your back end which is cool. \n", 114 | "counts = execute(qc_out, Aer.get_backend('qasm_simulator')).result().get_counts()\n", 115 | "plot_histogram(counts)" 116 | ] 117 | }, 118 | { 119 | "cell_type": "code", 120 | "execution_count": 3, 121 | "metadata": {}, 122 | "outputs": [ 123 | { 124 | "data": { 125 | "image/png": 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rQ4cOeVwmPz9fO3bsKDHthx9+qK6IAAxm5DnogwcPaufOnRo5cmSp+/bv36+oqCgFBQXJZrNp4sSJys7O1vbt2zV48GAlJCR4ITFQUnx8vIYMGaIff/xR/fv3r1Q5S/855xwQEKD09HRJ0tNPP63IyMjqjAvAQMYWtCS1aNGixPQzZ87I5XIVH95u1KhR8bk9Sbrpppu0d+/eSq3DZrMxLhkXbxtf2U4mZL70m6zsdrumT58uqeirKA8cOFCp38mLLwibO3euhg8frldffVVBQUGaNm1aqfldLpfXtz+Dwbj8UVlGFnRoaKgkKTs7u8T0WbNm6fDhw4qNjS1zudTUVA0dOrS64wEVuuOOO9S+fXvt3r1bS5YsqdQyl5bzhXPO06dPV0FBgYYPH67mzZtXZ2wAhjGyoMPCwuRwOJSSkqIlS5Zo7dq1SkpK0qJFiySpzIJ+5pln9O2332rWrFmVWodlWYxLxsXbxle2kwmZL71OYvDgwZKkRYsWlchVnvLKWSo6mrR69WoFBATo9ttvL7FcXFyc17c/g8G4/FFZRha03W5XWlqaoqKilJSUpISEBIWGhio5OVl+fn5yOBwl5p8xY4b+/ve/a82aNapbt66XUgNFLryA/Oc//+lx3orK+YLMzMwSjwvg6mDsVdydOnXSunXrSkyLj49XZGRkiY9GfOaZZ7Rq1Sp9+OGHatSoUQ2nBEoLCwuTJH355ZcVzleZcr74cTp06FC1QQEYzdiCLktWVpZ69OhR/PMXX3yhp59+Wh06dFCfPn2Kp7vd7poPB/x/gwcPVr169XTixIkK50tOTq7Uh5Bs2LBBt956q44cOVLVUQEYzGcKOicnR9nZ2Ro/fnzxtKioqMs6ng/UhI0bN1ZqvuHDhys+Pl7z58+vcL5///vf+vjjj6siGgAf4jMFHRISooKCAm/HAKpMbm6ux3IGcPUy8iIxAACudhQ0AAAGoqABADAQBQ0AgIEoaAAADERBAwBgIAoaAAADUdAAABjIZz6oBDCV0+m87GX27D8sSQpr27LE7epeLwDfQUEDP1NqauplLzPluQWSpJmTE0vcBoALOMQNAICBKGgAAAxEQQMAYCAKGgAAA1HQAAAYiIIGAMBAFDQAAAaioAEAMBAFDQCAgShoAAAMREEDAGAgChoAAANR0AAAGIhvswKuQhMnTpTb7fbKup1O5xV9AxhwtaGggauQ2+2Wy+XydgwAFeAQNwAABqKgAQAwEAUNAICBKGgAAAxEQQMAYCAKGgAAA/E2KwAeXXfddbrpppsUExOjJk2aqLCwUP/617+0ZcsWffLJJzp58mSpZR544AHdfffdGjlypPLy8ryQGvBtFDSAct1xxx2aNGmSbr311nLnOX36tN544w3NmjVL3377raSicl64cKHsdruGDBmiFStW1FRkoNYwuqALCws1d+5czZ8/XwcOHFBERITmzZunxMRExcXFacGCBd6OCNRKTZs21Ysvvqh77rlHUlEJ/+Mf/9CWLVv03Xffyc/PTxEREerZs6d69eql3/zmN7r//vs1depU/fjjj3rttddkt9s1efJkyhm4QkYX9Lhx45Senq5p06YpNjZWmZmZGj16tI4ePapJkyZ5Ox5QK7Vt21Zr165VeHi4cnJy9PTTT+vVV18t8zC2JEVERGjq1KmKj4/X3LlzZVmWbDabJk+erFmzZtVweqD2MLagly1bpsWLFysjI0NxcXGSpL59+2rr1q1KT09XTEyMlxMCtU/Dhg310UcfKTw8XFu2bNGIESO0b9++CpfZtWuXfv3rX+v48eN65JFHZLPZtHHjRsoZ+JmMvYo7JSVFAwcOLC7nC8LDwxUQECCHwyFJGjp0qBwOh2688UZ169ZNH330kTfiArXC3Llz1bFjR7ndbvXr189jOV/wwAMPaMKECbLZbDp//rx69uypO+64o3rDArWckQV98OBB7dy5UyNHjix13/79+xUVFaWgoCBJ0uLFi/X5559r27Ztmj9/voYPH66CggKP67DZbIxLxsXbxle2ky9mNiF3WV+U0atXL40dO1Znz57VqFGjyj2kfamLLwibPHmypkyZIkl65ZVX5O9f+iCdy+Xy+vZnMLw5KsvYgpakFi1alJh+5swZuVyuEoe3GzVqVHz7p59+ks1mk2VZNZITqE0mTJggSZozZ4527dpVqWUuLedZs2YpNTVVX3zxhdq0aaOhQ4dWY2KgdjOyoENDQyVJ2dnZJabPmjVLhw8fVmxsbInpycnJCgsL0/Dhw7VixYoyX7VfyrIsxiXj4m3jK9vJFzObkPvSU0cNGjTQsGHDlJ+fr5dfftnj/x+p7HKWit598dJLL0mSEhISSi0XFxfn9e3PYHhzVJaRF4mFhYXJ4XAoJSVFTZo0UatWrbR8+XKtWrVKkkoV9Isvviip6NDZY489pvXr1yskJKTGcwO+KiYmRgEBAfr000916NAhj/OXV84XvPfee3rxxRfVvXv36ooM1HpG7kHb7XalpaUpKipKSUlJSkhIUGhoqJKTk+Xn51d8gdil4uLiZLfbtWHDhhpODPi26OhoSdLWrVs9zuupnKWi01RHjx5V06ZN1bp16yrPC1wNjNyDlqROnTpp3bp1JabFx8crMjJSderUkSTl5OTo2LFjateunSRp27Zt2r17tzp37lzjeQFf9t133+nvf/+7Nm3aVOF8d9xxh8dyvuDdd99V8+bNqzoqcNUwtqDLkpWVpR49ehT/fPr0ad1zzz3KycmRv7+/goODtXTpUrVt29aLKQHfk5aWprS0NI/zZWRkKCMjQx988IHH9zknJiZWVTzgquQzBZ2Tk6Ps7GyNHz++eFrz5s09vuIHUHVyc3N1++23V+qtjAB+Hp8p6JCQEP4oAAbg/yFQM4y8SAwAgKsdBQ0AgIEoaAAADERBAwBgIAoaAAADUdAAABiIggYAwEA+8z5oAFXH6XRe9jJ79h+WJIW1bVnidk2sG7gaUdDAVSg1NfWyl5ny3AJJ0szJiSVuA6geHOIGAMBAFDQAAAaioAEAMBAFDQCAgShoAAAMREEDAGAgChoAAANR0AAAGIiCBgDAQBQ0AAAGoqABADAQBQ0AgIEoaAAADMS3WQHwGRMnTpTb7a7x9Tqdziv6BjDg56CgAfgMt9stl8vl7RhAjeAQNwAABqKgAQAwEAUNAICBKGgAAAxEQQMAYCAKGgAAA1HQAGq14OBgRURE6IYbblCbNm08zj9ixAgFBgbWQDKgYhQ0gFqnTZs2evbZZ7V9+3adOnVKX3/9tXbs2KH9+/fr+PHjWr16tX71q18pICCgxHJTpkxRWlqa3n77bS8lB/7D6IIuLCzU7Nmz1bFjRwUHBys6Oloul0sRERFKTEz0djwAhqlXr57mzZunvXv36ve//70cDodsNpu++eYb7dy5Uz/88IMaN26sgQMH6q233tKePXv0y1/+UlJROf/v//6vCgsLlZ6e7uVnAhj+SWLjxo1Tenq6pk2bptjYWGVmZmr06NE6evSoJk2a5O14AAzSuXNnrVy5Uh06dND58+f19ttv67XXXtPGjRt15syZ4vlatWqlO++8U8nJyYqKitLf//53bdq0ST169FBhYaESEhK0ZMkSLz4ToIixBb1s2TItXrxYGRkZiouLkyT17dtXW7duVXp6umJiYrycEIApIiIi5HK5dM0118jtdmvMmDH6/PPPy5z30KFDevnllzV//nw98sgjmjVrlnr06CHLsjR27FjKGcYw9hB3SkqKBg4cWFzOF4SHhysgIEAOh6PE9AULFshms2n58uU1GROAlwUFBSk9PV3XXHON1qxZo549e5ZbzhcrLCxUcHCwAgICZFmWbDabGjVqVP2BgUoysqAPHjyonTt3auTIkaXu279/v6KiohQUFFQ87ZtvvtHrr7+uHj161GRMAAb4n//5H0VGRurrr7/WsGHDdPbs2Uotd/E55xdeeEFS0Y5Bhw4dqjMuUGnGFrQktWjRosT0M2fOyOVylTi8nZ+fr7Fjx+rll18uUdqe2Gw2xiXj4m3jK9vJFzP7am4TMl/6TVaNGjXSo48+KklKSEgoca65IheXc0JCgh577DEtXbpUdevW1RNPPFFqfpfL5fXtz6g9o7KMLOjQ0FBJUnZ2donps2bN0uHDhxUbG1s87dlnn9WgQYPkdDprMiIAA4wZM0Z169bVhx9+qE2bNlVqmUvL+cI55xkzZkiS7r//fjVo0KDaMgOVZWRBh4WFyeFwKCUlRUuWLNHatWuVlJSkRYsWSVJxQX/66af6+OOPNXny5Mteh2VZjEvGxdvGV7aTL2b21dwmZL70mpQBAwZIkl5//fVK/b8vr5wladeuXcrMzFS9evXUq1evEsvFxcV5ffszas+oLCML2m63Ky0tTVFRUUpKSlJCQoJCQ0OVnJwsPz+/4gvE1q1bp927d6tDhw5q3769Nm3apPHjx2vOnDlefgYAasKFF+sbN270OG9F5XzBhb3wi4/SAd5i7NusOnXqpHXr1pWYFh8fr8jISNWpU0dS0X+4KVOmFN/fp08fPfzwwxoxYkSNZgVQ84KCgtSsWTPl5eVp3759Fc5bmXKWivaiJaldu3ZVHRe4bMYWdFmysrK4UhuAJCkvL0/h4eEeLw718/NT//79K/UhJGlpaVq/fr2OHTtW1XGBy+YzBZ2Tk6Ps7GyNHz++3HkyMjJqLhAAr7IsS7t37/Y4X0FBgYYMGaK4uDitXr26wnlPnDihEydOVFVE4GfxmYIOCQlRQUGBt2MA8EG5ubkeyxkwjZEXiQEAcLWjoAEAMBAFDQCAgShoAAAMREEDAGAgChoAAANR0AAAGMhn3gcNAFfyrXV79h+WJIW1bVnidnWvF/i5KGgAPiM1NfWyl5ny3AJJ0szJiSVuA6bjEDcAAAaioAEAMBAFDQCAgShoAAAMREEDAGAgChoAAANR0AAAGIiCBgDAQBQ0AAAGoqABADAQBQ0AgIEoaAAADERBAwBgIL7NCgCq0cSJE+V2u72ybqfTeUXfAAYzUNAAUI3cbrdcLpe3Y8AHcYgbAAADUdAAABiIggYAwEAUNAAABqKgAQAwEAUNAICBKGgAqAX8/XnXbG3DvygAGMJutysuLk49evSQ0+lUo0aNlJ+fr927d2vLli364IMP9P3335daLjU1VR06dNDw4cOVl5fnheSoDhQ0AHiZv7+/Hn74YU2YMEFhYWHlznf+/Hmlp6dr+vTp+vLLLyUVlfOjjz6qc+fOKSYmRps2baqp2KhmRhd0YWGh5s6dq/nz5+vAgQOKiIjQvHnzlJiYqLi4OC1YsMDbEQHgZ7nhhhu0ZMkS3XjjjZKkPXv2aOXKldqyZYuOHDmioKAgRUZGqlevXho0aJDuueceDR06VM8884xatGihRx55ROfOndPw4cMp51rG6IIeN26c0tPTNW3aNMXGxiozM1OjR4/W0aNHNWnSJG/HA4Cf5aabbtLq1avVoEED7d27V48++qjef/99FRYWlphv5cqVkqRWrVrpqaeeUmJiolJSUiSpuJzff//9Gs+P6mVsQS9btkyLFy9WRkaG4uLiJEl9+/bV1q1blZ6erpiYGC8nBIAr17FjR61atUoNGjTQW2+9pXHjxun06dMVLnPo0CE99NBDatasmYYOHSpJ+uCDDyjnWsrYq7hTUlI0cODA4nK+IDw8XAEBAXI4HJKkPn366LrrrpPT6ZTT6dSUKVO8ERcAKs1ut2vx4sVq2LCh0tPTde+993os5wtSU1M1dOhQ5eXl6fz587rzzjvVr1+/ak4MbzCyoA8ePKidO3dq5MiRpe7bv3+/oqKiFBQUVDzt+eefl9vtltvt1syZMyu1DpvNxrhkXLxtfGU7+WJmX83ti5lNyF3WN1nFx8frpptu0qFDhzRu3LhSh7TLc/EFYcOGDdPTTz8tSXrppZdKPL8LXC6X17c/o/zfSU+MLWhJatGiRYnpZ86ckcvl4vA2AJ82YcIESdLUqVP1448/VmqZi8v5wjnn5557Tvv27VNERIRuu+22akwMbzCyoENDQyVJ2dnZJabPmjVLhw8fVmxsbInpU6dOVZcuXXTXXXfp888/r9Q6LMtiXDIu3ja+sp18MbOv5vbFzCbkvvQ03fXXX6/Y2FgdO3ZMb775ZqX+XpVVzpJUUFBQ/G6WX//616WWi4uL8/r2Z5T/O+mJkReJhYWFyeFwKCUlRU2aNFGrVq20fPlyrVq1SpJKFPSSJUvUpk0b2Ww2vfnmmxowYIC+/fZb1atXz1vxAaBc3bp1kyR9/PHHOnfunMf5yyvnC1avXq2UlBT94he/qJa88B4j96DtdrvS0tIUFRWlpKQkJSQkKDQ0VMnJyfLz8yu+QEyS2rZtW3xMf9SoUQoMDNSuXbu8FR0AKtSlSxdJ0rZt2zzO66mcJemLL77Q+fPnFRERoeDg4CrPC+8xcg9akjp16qR169aVmBYfH6/IyEjVqVNHknT27Fnl5OQUHxJfu3atTp06pfDw8BrPCwCVsWXLFr322mv69NNPK5wvKSnJYzlLRZ8utmDBAvn5+cluN3KfC1fI2IIuS1ZWlnr06FH888mTJzVo0CDl5eXJbrerQYMGeu+999SgQQMvpgSA8r355puVOvf85z//WXfeeaf+7//+z+P7nB9++OGqigeD+ExB5+TkKDs7W+PHjy+e1qxZM23ZssWLqQCgeuTm5mrQoEHejgEv8pmCDgkJUUFBgbdjAABQIzhhAQCAgShoAAAMREEDAGAgChoAAANR0AAAGIiCBgDAQBQ0AAAG8pn3QQOAL3I6nZe9zJ79hyVJYW1blrhdE+uGOShoAKhGqampl73MlOeKvkJy5uTEErdxdeEQNwAABqKgAQAwEAUNAICBKGgAAAxEQQMAYCAKGgAAA1HQAAAYiIIGAMBAFDQAAAaioAEAMBAFDQCAgShoAAAMREEDAGAgvs0KAFDCxIkT5Xa7vbJup9N5Rd8AVhtR0ACAEtxut1wul7djXPU4xA0AgIEoaAAADERBAwBgIAoaAAADUdAAABiIggYAwEAUNACgSoSFhalfv37q37+/YmNjFRQUVO68fn5+euyxxxQYGFiDCX0L74MGAFyxW265RePHj9eAAQPUuHHjEvfl5+dr69ateu211/TGG2/o9OnTkorK+S9/+YtGjx6trl276r777vNGdOMZvQddWFio2bNnq2PHjgoODlZ0dLRcLpciIiKUmJjo7XgAcNVq166dPvroI61fv16jRo1S48aN9f333ysjI0MffvihvvjiC9lsNnXr1k0LFizQnj17NHz48BLlfPLkSf3pT3/y9lMxltF70OPGjVN6erqmTZum2NhYZWZmavTo0Tp69KgmTZrk7XgAcFW644479Oabb6p+/fo6duyYXnrpJb3++uvau3dvifnq1aunu+66S48++qi6deum5cuXa/fu3erQoYNOnjypAQMGaNOmTV56FuYztqCXLVumxYsXKyMjQ3FxcZKkvn37auvWrUpPT1dMTIyXEwLA1WfAgAF69913FRAQoOXLl2v8+PE6evRomfOePn1ab7zxhpYtW6akpCS98MIL6tChg/Ly8jRw4EDK2QNjD3GnpKRo4MCBxeV8QXh4uAICAuRwOCRJeXl5mjRpkjp27KguXbqod+/e3ogLALVeixYt9MYbbyggIEBz587VyJEjyy3ni9ntdt18883y9/eXZVkKDAws/huO8hlZ0AcPHtTOnTs1cuTIUvft379fUVFRxVcHPvnkkzp16pS+/vpr7dixQ2+99VZNxwWAq8JLL72kJk2aaNWqVXr88ccrtcyl55x///vfS5Jmz56tNm3aVGdcn2dsQUtFr9YudubMGblcruLD27m5uZo/f76ef/55+fn5SZJatmxZqXXYbDbGJePibeMr28kXM/tqbl/M7Ku5vZ25rG+y6ty5s+6++27l5ORU+iLdS8t5wIABSklJUXp6ukJCQvTwww+XWsblcnl9+9fUv68nRhZ0aGioJCk7O7vE9FmzZunw4cOKjY2VJH377bdq2LCh5s6dq27duqlHjx56++23azwvANR2v/3tbyVJf/nLX3To0CGP85dVzhfOOc+cOVNS0YXAvA+6fEYWdFhYmBwOh1JSUrRkyRKtXbtWSUlJWrRokSQVF3R+fr4OHTqkli1bavPmzXrzzTc1ceJEbdu2zeM6LMtiXDIu3ja+sp18MbOv5vbFzL6a29uZL732R5JuvfVWSUUF7UlF5SxJn332mXbt2qWmTZsqOjq6xLJxcXFe3/419e/riZEFbbfblZaWpqioKCUlJSkhIUGhoaFKTk6Wn59f8cUFbdu2lSSNGTNGktS+fXv16tVLmzdv9lp2AKht6tatq+uvv17nz5/3uAPkqZwv+PTTTyX9Z4cLpRlZ0JLUqVMnrVu3TqdPn9b+/fv17LPPaseOHYqMjFSdOnUkFR0KHzhwoN5//31J0rFjx7R58+ZSr8gAAFeuefPm8vPz06FDh3T27Nly56tsOUtFpygl6dprr62WzLWBse+DLktWVpZ69OhRYtorr7yicePGafr06bIsS1OmTCk1DwDgyu3bt08hISEezxcHBgaqefPmlfoQkjlz5mjevHnFH/+J0nymoHNycpSdna3x48eXmH7h4+YAANXDsiydPn3aY5meOXNGQ4YMUceOHbV9+/YK583Nza3KiLWSzxR0SEiICgoKvB0DAFCB3Nxcj+WMyjH2HDQAAFczChoAAANR0AAAGIiCBgDAQBQ0AAAGoqABADAQBQ0AgIF85n3QAICa4XQ6r2i5PfsPS5LC2rYscbsm1l0bUdAAgBJSU1OvaLkpzy2QJM2cnFjiNq4Mh7gBADAQBQ0AgIEoaAAADERBAwBgIAoaAAADUdAAABiIggYAwEAUNAAABqKgAQAwEAUNAICBKGgAAAxEQQMAYCAKGgAAA/FtVh48vutLbT91yivrjq5fX3MiIr2ybgDwNRMnTpTb7a7x9Tqdziv+BrCKUNAebD91SutPHPd2DACAB263Wy6Xy9sxqgyHuAEAMBAFDQCAgShoAAAMREEDAGAgChoAAANR0AAAGIiCBgCgkoKDgxUYGFgj6+J90ACAq07Dhg01bNgwdevWTQ6HQ/Xr11deXp6ys7O1ZcsWvfvuu9q9e3eJZYKDg/Xee+8pLy9Pw4YNU15eXrVmpKABAFeNpk2b6tlnn9Wvf/1r1atXr9T9sbGxGj16tGbPnq01a9boySef1LZt24rLuX///vr+++/VqlUr7d27t1qzGn2Iu7CwULNnz1bHjh0VHBys6OhouVwuRUREKDEx0dvxymSdP6/zv31YBfNfLTG94J13df7+MbJycryUDACuboMHD9YXX3yhpKQk1atXT2vXrtWkSZPUt29fORwOde/eXQ8++KCWLFmiM2fOaODAgdq8ebNmzJihlStXFpdzv379qr2cJcP3oMeNG6f09HRNmzZNsbGxyszM1OjRo3X06FFNmjTJ2/HKZAsIkP+UJ5Q/YaJs3X4h+41OWXv3qnDRn+X3h+myhYR4OyIAXHUSEhL02muvyW63KyMjQ+PHj9dXX31Var7Nmzdr4cKFeuyxx/TUU09pwoQJmjp1qiQVl3NZy1UHY/egly1bpsWLF+u9997T7373O/Xt21dTp05Vz549lZ+fr5iYGG9HLJetfTvZx45Rwew/yjp+XPkzn5f9riGyO7p4OxoAXHX69+9fXM7Tpk2rVMkeP35cU6ZM0bZt24qnrV69usbKWTK4oFNSUjRw4EDFxcWVmB4eHq6AgAA5HA79+OOPcjqdxSMyMlI2m007duzwUur/sA+9S7a2bZT/ULLk5yf7mHhvRwKAq06DBg20cOFC2e12TZ8+XTNmzJBlWR6Xu3DOOTY2VseOHVN+fr7GjBmjXr161UDqIkYW9MGDB7Vz506NHDmy1H379+9XVFSUgoKC1KhRI7nd7uIxZcoURUdHq0sXz3uqNputUiMjI+OKnoPNZpPN0UX66SfZb+0nW0DAZT9GRkZGpXNWxbg4++VuJ28NX8zsq7l9MbOv5vbFzCbkLuubrP7rv/5Lbdq00aeffqrp06eXur8sl14Qdsstt2jmzJmy2+2aN29eqfldLtcVbSdPjC1oSWrRokWJ6WfOnJHL5Sr38Parr75qzMVj1t69KnzjTdnvGanCpW/I+uEHb0cCgKtKYGCgfvOb30iSJk2apIKCAo/LXFrOFw6Hz5gxQ0ePHlVMTIy6d+9e3dElGVrQoaGhkqTs7OwS02fNmqXDhw8rNja21DJff/21tm7dqvvuu69S67Asq1KjT58+l53fyjtfdN552FD5jUuQrVdPFTw/V1Zh4WU9Tp8+fSqdsyrGxdvmcreTt4YvZvbV3L6Y2Vdz+2JmE3Jfekq0X79+atasmT7//HNlZmaW+Xf2YuWVsySdO3dOr7/+uiRp9OjRJZaLi4u7ou3kiZEFHRYWJofDoZSUFC1ZskRr165VUlKSFi1aJEllFvSCBQv0q1/9Sg0bNqzpuKUULnpdNn9/2eOLXiz4jf+trO+PqHDFO15OBgBXj65du0qSPvzwQ4/zVlTOF1x4nAuPW92MLGi73a60tDRFRUUpKSlJCQkJCg0NVXJysvz8/ORwOErMf+7cOS1ZssSIw9uF29wqXLVGflP+Szb/onex2erWld/k36lwyVJZNfDeOQCAFBUVJUnavn17hfNVppwlye12l3jc6mbs+6A7deqkdevWlZgWHx+vyMhI1alTp8T0d955Ry1btlTPnj1rMmKZ7Dc6ZX8vvfT0G6JkX8keNADUlPT0dH377bfasmVLhfNNmzbNYzlL0okTJ5SSkqLTp09XR9xSjC3osmRlZalHjx6lpr/66qvFFwIAACBJaWlpSktL8zjfH/7wB4WFhWn69OkVvs+5oKCg+ENLaoLPFHROTo6ys7M1fvz4UvetXbvWC4kAALVBbm5uqQu/TOAzBR0SElKpS+QBAKgNjLxIDACAqx0FDQCAgShoAAAMREEDAGAgChoAAANR0AAAGIiCBgDAQD7zPmhvia5f/6pcNwD4GqfTednL7Nl/WJIU1rZlidvVvd7KoKA9mBMR6e0IAIBKSE1Nvexlpjy3QJI0c3Jiidsm4BA3AAAGoqABADAQBQ0AgIEoaAAADERBAwBgIAoaAAADUdAAABiIggYAwEAUNAAABqKgAQAwEAUNAICBKGgAAAxEQQMAYCAKGgAAA1HQAAAYiIIux9KlS+VwOOR0OnXLLbdo165d3o5ktIyMDEVFRSk8PFwPPvigCgoKvB3Jo0cffVStW7eWv79vfS36gQMHdOutt6pz586KiorSf//3f3s7UqXcfvvtcjqd6tKli0aMGKGTJ096O1KlJScn+9TvSfv27RUVFSWn0ymn06kdO3Z4O5JHp0+f1pgxYxQREaHrr79e8+fP93Ykj3744Yfibex0OtWiRQvdfffdVfb4FHQZcnNz9eijj+rjjz+W2+3Wfffdp9///vfejmWswsJCPfjgg0pLS9O3336rkydPaunSpd6O5dHIkSOVlZXl7RiXzd/fX88995y++uorbdu2Tf/85z/1t7/9zduxPEpLS5Pb7daOHTvUunVrzZ0719uRKuWTTz5RTk6Ot2Nctg8++EBut1tut1tdunTxdhyPHn/8cUVFRWnXrl366quvqrToqkuzZs2Kt7Hb7dYNN9ygkSNHVtnjU9BlKCwslGVZxf8pf/rpJ7Vs2dLLqcz12Wef6dprr1VkZKQkady4cVqxYoWXU3l28803q0WLFt6Ocdlatmyprl27SpICAwN14403av/+/V5O5VnDhg0lFf3/Onv2rGw2m5cTeXbu3DlNmTJFs2fP9naUWu3UqVN67733NGnSJEmSzWZTs2bNvJzq8nz33XfKysrS0KFDq+wxbZZlWVX2aLXIG2+8ocTERDVs2FANGzbUxo0bi//A1BbHfzypv777kQr//6/A4R+OSZJaNmta4rYk+dntuv/u/mrUIKTU46xYsULp6en661//Kkn66quvdO+992rbtm3VknvlR5nac+Cwx8yS5IwMV1z36Aofz9/fX/n5+dWS9YJD3/9by1e7in+uKHdQYIB+PXyA6gYHeXzc48ePy+l06h//+Ieuv/76Ks1sWZbe+vs6Hfn3CY+ZJalX7A3q6oio8DHvvvtuffLJJ+rSpYtWrlypkJDSv08/V/aeA1rt2lz8c0W569ero/hhtyugnMPXU6dOVYcOHTR27Nhq/T3JLyjQ0nc+1E+nTnvMLEm339JVncPblft47du3V+PGjWVZln75y1/q6aefVkBAQJXn3vbFN1q/+fPinyvKfU2Thhp1562yl/HCbPv27XrggQfUvXt3bd68We3atVNqaqratSv/OV6ps+fy9OcVH+jsuTyPmSXp7ttvVttWzT0+7pw5c7Rjxw4tXry4yrKyB12G8+fP66WXXtJnn32mQ4cOacSIEZo8ebK3Y1W5Jo0aqFNYGx3+4VjxL6akUrcP/3BMnTu2K7OcpaI/5DXp5l900fEfT3rMfObsOXV3dq7RbOVp1SJUrZqHVmpbx97QqVLlnJeXpxEjRujRRx+t8nKWivZiendz6Id/n/CYWZKcUeEeH/Odd97Rd999p9atW2v58uVVnlmSOl7XWg1C6lZqW98Ue0O55fz555/r008/VUJCQrXkvJi/n596db2hUpnr1QlWRIe2FT7eJ598om3btmnDhg3atWtXtR0BcFzfQX52u8fcR44e1y3dHGWWsyTl5+fL7XZrxIgR2rp1q4YMGaKxY8dWS+bgoEB1i76+Utu6eWjjSpWzVHTd0v3331+lWSnoMrjdblmWpc6di/64jxo1SpmZmV5OVT1u7RWja5s3rXCettc2U58eznLvb9OmjQ4cOFD88/79+9W6deuqilhK44b1dedtvSqcxyZp5C/7KDgosNpyXK7Bt/ZU44b1K5ync3g7j3uhklRQUKB7771XTqdTjz/+eFVFLOXa5qHqf0vXCufx87PrnsF95e/nV6nHDAwM1KhRo/TOO+9URcRSbDabhg+K8/gip7uzs66voOg2bNigL7/8Utddd53at2+vgoICtW/fvtoubuvYvrVuir2hwnmCgwI14o64covugjZt2kiS6tWrpwcffLDa/n75+dn1q8F95e9f8b99v5ti1KZl+YesW7duraZNm+q2226TVPQ3d8uWLVWa9WLOyHB1ibiuwnka1q+nu/pX/Hfmgi+//FJHjx5Vv379qiJeMQq6DK1bt9auXbt06NAhSdKHH35YfH61tvH389M9g/uV+8c1IMBfvxrcV3728n9VunbtqoMHD+rLL7+UJC1cuFDDhg2rlrwXxNzQUVGd2pd7/82/cKhD22urNcPlCg4K1K9+2Ufl/WmtVzdYwwf2rtS52cTERNWvX19z5syp2pBl6N3NoXYV7EUM6N1NLa5pUuFjnDp1SocPF52WKCws1HvvvaeoqKgqzXmxBiF1dfeAW8q9v2mjBrqjb48KHyMpKUnfffed9u3bp3379snPz0/79u1TgwYNqjpusUFx3XRNk0bl3j/09pvLPZJ1wenTp4tfRBQUFGjFihVyOBxVGbOEZk0baVCf7uXe37rlNerb88YKH6N58+aKiorS1q1bJRX9za3O3w+bzaahA25R/ZC65c4z8o4+qlOJI1mS9Je//EX33nuv7BX8nbwSFHQZWrZsqZkzZ6p///6Kjo7WypUrNWvWLEk1fzi3JjQPbayBcd3KvG9wvx4KbVzxuXc/Pz+99tprGjFihDp06KCQkBDFx8dXR9RiNptNdw+4RSH16pS6r3loY93eu+K9Pkl66KGH1Lp1axUUFKh169ZKTk6ujqglXNempXqXc0582MDeZT6fS23YsEGLFi1SVlaWbrzxRjmdTs2bN6+qoxaz24v2kgIDS5/DvK5NS938C89XCJ86dUp33nmnHA6HHA6H8vPzq/2dEV2uD9ONUR1LTbfZbPrV4L4KKuP5eFtAgL/uGdxXdnvpF2mO68MU3bmDx8c4cuSIevfuXbytLcvS1KlTqyNusZ4xUerYvlWp6QH+frrnl33l5+e5al5++WUlJyfL4XBozpw5eu2116ojarF6dYI1YmDvMu/r1fUGhZfxfMpiWZbeeOONKj+8LXGR2GXL2OTWoe+P6p4h5e91+qJCy9LCt97X7n99VzwtIqyNHhgx0Oirbb/evV+Ll68p/tnPblfyr4fq2uahXkxVsfz8Av3fknf0/dHjxdO6donQiDvivJjKs83bv1b6mvXFPwcFBmji2BEeD9t709lzefrjwrTii68kqW/PGzWg9y+8mMqztRu26sN//uctgPVD6uqxsSNUt06wF1NV7KdTp/XHhWnFF19J0l39e6lnTPXtCVeFd//xT23a9mXxz82aNtKEMcMUEOD9972zB30Zzp3L0/pPtyvvfH6tKmdJsttsGnnHf87Z1q0TpOGD4owuZ0m6vkNbdYv+zwVS/W/panQ5S5K/v59GDelXvFfRpGF9Dbm1p5dTefYLR4Q6h//nnO2dt/UyupylC6cV+hb/3Kp5qG7tFePFRJXTp6ezxDnbkYPijC5nqeic7d2331z8c6frWqvHjeafGryjT/fio4R2u033DO5nRDlLtaCgd+zYoeHDhys0NFTBwcHq2LFjtR3Oydz6hXLPntNtvWKr5fG9rVGDkOKLIu4ecIsaVHB+xiS/7NdTTRs1ULtWzdW7W/Wda6tKLa5pottv+UXxxWxBBl3MVh6bzaZhA3urXt1gRXVqr5gbSh8+NlGHdtfq5q5d5O/nV3RBkw+8uPazF114FxDgrx43RqpTWBtvR6qU6MhwRXfuoDrBQRrhAy/wJSkwMKDo2hCbTbf1ilWrFua8wPfpQ9xbtmxR79691aZNG02ePFnt2rXT3r17lZmZqYULF1a47JTnFtRQSgAA/mPm5MRKzWfGfvwVevzxx1WvXj19+umnJT5EZNy4cV5MBQDAz+eze9C5ubmqX7++Hn74Yb3wwgvVuq5z5/L03CvL1ObaZkoYOaha1wUAgOTDe9AnTpxQYWHhFX8gxpUc4t615wCHxgEAP0tlD3H77EVijRs3lt1uL/4wEQAAahOfPcQtSX379tWXX36pb775pto+3Wfdxm36YP1nSo4fqjbX+ta3qwAAfJfP7kFL0uzZs5WTk6MePXpo8eLFWrdunf785z/rwQcfrJLHP3cuT59s/lwRYW0oZwBAjfLZc9CSFBsbq40bN2ratGl67LHHdPbsWbVp00ajRo2qksc//tMp1akTVGvf9wwAMJdPH+KuCYWFhVX+AegAAHhCQQMAYCB2DQEAMBAFDQCAgShoAAAMREEDAGAgChoAAANR0AAAGIiCBgDAQBQ0AAAGoqABADAQBQ0AgIEoaAAADERBAwBgIAoaAAADUdAAABiIggYAwEAUNAAABqKgAQAwEAUNAICBKGgAAAxEQQMAYCAKGgAAA1HQAAAYiIIGAMBAFDQAAAaioAEAMBAFDQCAgShoAAAM9P8AqsBsSDcWQsYAAAAASUVORK5CYII=\n", 126 | "text/plain": [ 127 | "
" 128 | ] 129 | }, 130 | "execution_count": 3, 131 | "metadata": {}, 132 | "output_type": "execute_result" 133 | } 134 | ], 135 | "source": [ 136 | "#Example 4.1 - Encoding an input\n", 137 | "#Not gate - most basic operation which flips the bits\n", 138 | "#I had to manually install a missing module named pylatexenc:\n", 139 | "#The class MatplotlibDrawer needs pylatexenc. to install, run \"pip install pylatexenc\".\n", 140 | "\n", 141 | "qc_encode = QuantumCircuit(n)\n", 142 | "qc_encode.x(7)\n", 143 | "qc_encode.draw()\n", 144 | "qc = qc_encode + qc_out\n", 145 | "qc.draw(output='mpl',justify='none')\n" 146 | ] 147 | }, 148 | { 149 | "cell_type": "code", 150 | "execution_count": 4, 151 | "metadata": {}, 152 | "outputs": [ 153 | { 154 | "data": { 155 | "image/png": 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\n", 156 | "text/plain": [ 157 | "
" 158 | ] 159 | }, 160 | "execution_count": 4, 161 | "metadata": {}, 162 | "output_type": "execute_result" 163 | } 164 | ], 165 | "source": [ 166 | "counts = execute(qc,Aer.get_backend('qasm_simulator')).result().get_counts()\n", 167 | "plot_histogram(counts)" 168 | ] 169 | }, 170 | { 171 | "cell_type": "code", 172 | "execution_count": 5, 173 | "metadata": {}, 174 | "outputs": [ 175 | { 176 | "data": { 177 | "text/html": [ 178 | "
          \n",
179 |        "q_0: ─────\n",
180 |        "     ┌───┐\n",
181 |        "q_1: ┤ X ├\n",
182 |        "     └───┘\n",
183 |        "q_2: ─────\n",
184 |        "          \n",
185 |        "q_3: ─────\n",
186 |        "          \n",
187 |        "q_4: ─────\n",
188 |        "     ┌───┐\n",
189 |        "q_5: ┤ X ├\n",
190 |        "     └───┘\n",
191 |        "q_6: ─────\n",
192 |        "          \n",
193 |        "q_7: ─────\n",
194 |        "
" 195 | ], 196 | "text/plain": [ 197 | " \n", 198 | "q_0: ─────\n", 199 | " ┌───┐\n", 200 | "q_1: ┤ X ├\n", 201 | " └───┘\n", 202 | "q_2: ─────\n", 203 | " \n", 204 | "q_3: ─────\n", 205 | " \n", 206 | "q_4: ─────\n", 207 | " ┌───┐\n", 208 | "q_5: ┤ X ├\n", 209 | " └───┘\n", 210 | "q_6: ─────\n", 211 | " \n", 212 | "q_7: ─────\n", 213 | " " 214 | ] 215 | }, 216 | "execution_count": 5, 217 | "metadata": {}, 218 | "output_type": "execute_result" 219 | } 220 | ], 221 | "source": [ 222 | "qc_encode = QuantumCircuit(n)\n", 223 | "qc_encode.x(1)\n", 224 | "qc_encode.x(5)\n", 225 | "\n", 226 | "qc_encode.draw()" 227 | ] 228 | }, 229 | { 230 | "cell_type": "code", 231 | "execution_count": 6, 232 | "metadata": {}, 233 | "outputs": [ 234 | { 235 | "data": { 236 | "text/html": [ 237 | "
          \n",
238 |        "q_0: ──■──\n",
239 |        "     ┌─┴─┐\n",
240 |        "q_1: ┤ X ├\n",
241 |        "     └───┘
" 242 | ], 243 | "text/plain": [ 244 | " \n", 245 | "q_0: ──■──\n", 246 | " ┌─┴─┐\n", 247 | "q_1: ┤ X ├\n", 248 | " └───┘" 249 | ] 250 | }, 251 | "execution_count": 6, 252 | "metadata": {}, 253 | "output_type": "execute_result" 254 | } 255 | ], 256 | "source": [ 257 | "# 1.2 - Example 4.3 - Adding with Qiskit\n", 258 | "\n", 259 | "#bit addition samples from the book:\n", 260 | "\n", 261 | "#0+0 = 00\n", 262 | "#0+1 = 01\n", 263 | "#1+0 = 01\n", 264 | "#1+1 = 10\n", 265 | "\n", 266 | "#create a circuit with two qubits and try out the controlled-NOT gate (CNOT)\n", 267 | "# XOR gate\n", 268 | "qc_cnot = QuantumCircuit(2)\n", 269 | "qc_cnot.cx(0,1)\n", 270 | "qc_cnot.draw()\n", 271 | "\n", 272 | "#The first bit acts as the control bit with the black square (dot in the book)\n", 273 | "#q1 acts as the target bit with the box with X in side (+ inside a circle in the book)" 274 | ] 275 | }, 276 | { 277 | "cell_type": "code", 278 | "execution_count": 7, 279 | "metadata": {}, 280 | "outputs": [ 281 | { 282 | "data": { 283 | "text/html": [ 284 | "
     ┌───┐     ┌─┐   \n",
285 |        "q_0: ┤ X ├──■──┤M├───\n",
286 |        "     └───┘┌─┴─┐└╥┘┌─┐\n",
287 |        "q_1: ─────┤ X ├─╫─┤M├\n",
288 |        "          └───┘ ║ └╥┘\n",
289 |        "c: 2/═══════════╩══╩═\n",
290 |        "                0  1
" 291 | ], 292 | "text/plain": [ 293 | " ┌───┐ ┌─┐ \n", 294 | "q_0: ┤ X ├──■──┤M├───\n", 295 | " └───┘┌─┴─┐└╥┘┌─┐\n", 296 | "q_1: ─────┤ X ├─╫─┤M├\n", 297 | " └───┘ ║ └╥┘\n", 298 | "c: 2/═══════════╩══╩═\n", 299 | " 0 1 " 300 | ] 301 | }, 302 | "execution_count": 7, 303 | "metadata": {}, 304 | "output_type": "execute_result" 305 | } 306 | ], 307 | "source": [ 308 | "\n", 309 | "qc = QuantumCircuit(2,2)\n", 310 | "qc.x(0)\n", 311 | "qc.cx(0,1)\n", 312 | "qc.measure(0,0)\n", 313 | "qc.measure(1,1)\n", 314 | "qc.draw()\n", 315 | "\n", 316 | "#table from the book:\n", 317 | "#Input (q1 q0)\tOutput (q1 q0)\n", 318 | "#00\t00\n", 319 | "#01\t11\n", 320 | "#10\t10\n", 321 | "#11\t01" 322 | ] 323 | }, 324 | { 325 | "cell_type": "code", 326 | "execution_count": 8, 327 | "metadata": {}, 328 | "outputs": [ 329 | { 330 | "data": { 331 | "text/html": [ 332 | "
     ┌───┐ ░            ░       \n",
333 |        "q_0: ┤ X ├─░───■────────░───────\n",
334 |        "     ├───┤ ░   │        ░       \n",
335 |        "q_1: ┤ X ├─░───┼────■───░───────\n",
336 |        "     └───┘ ░ ┌─┴─┐┌─┴─┐ ░ ┌─┐   \n",
337 |        "q_2: ──────░─┤ X ├┤ X ├─░─┤M├───\n",
338 |        "           ░ └───┘└───┘ ░ └╥┘┌─┐\n",
339 |        "q_3: ──────░────────────░──╫─┤M├\n",
340 |        "           ░            ░  ║ └╥┘\n",
341 |        "c: 2/══════════════════════╩══╩═\n",
342 |        "                           0  1
" 343 | ], 344 | "text/plain": [ 345 | " ┌───┐ ░ ░ \n", 346 | "q_0: ┤ X ├─░───■────────░───────\n", 347 | " ├───┤ ░ │ ░ \n", 348 | "q_1: ┤ X ├─░───┼────■───░───────\n", 349 | " └───┘ ░ ┌─┴─┐┌─┴─┐ ░ ┌─┐ \n", 350 | "q_2: ──────░─┤ X ├┤ X ├─░─┤M├───\n", 351 | " ░ └───┘└───┘ ░ └╥┘┌─┐\n", 352 | "q_3: ──────░────────────░──╫─┤M├\n", 353 | " ░ ░ ║ └╥┘\n", 354 | "c: 2/══════════════════════╩══╩═\n", 355 | " 0 1 " 356 | ] 357 | }, 358 | "execution_count": 8, 359 | "metadata": {}, 360 | "output_type": "execute_result" 361 | } 362 | ], 363 | "source": [ 364 | "#4.3 continued - Using two CNOT gates\n", 365 | "\n", 366 | "#create a circuit with 4 input and two outputs\n", 367 | "qc_halfadder = QuantumCircuit(4,2)\n", 368 | "\n", 369 | "#now we need to encode the qubits 0 and 1\n", 370 | "qc_halfadder.x(0)\n", 371 | "qc_halfadder.x(1)\n", 372 | "qc_halfadder.barrier()\n", 373 | "\n", 374 | "#make use of the CNOT gates \n", 375 | "#write XOR of the given inputs on q2\n", 376 | "#q0 to q2\n", 377 | "qc_halfadder.cx(0,2)\n", 378 | "\n", 379 | "#q1 to q2\n", 380 | "qc_halfadder.cx(1,2)\n", 381 | "qc_halfadder.barrier()\n", 382 | "\n", 383 | "#now for the outputs of this circuit\n", 384 | "#q2 to output\n", 385 | "qc_halfadder.measure(2,0) # this is the XOR value we want\n", 386 | "qc_halfadder.measure(3,1)\n", 387 | "\n", 388 | "qc_halfadder.draw()" 389 | ] 390 | }, 391 | { 392 | "cell_type": "code", 393 | "execution_count": 9, 394 | "metadata": {}, 395 | "outputs": [ 396 | { 397 | "data": { 398 | "text/html": [ 399 | "
          \n",
400 |        "q_0: ──■──\n",
401 |        "       │  \n",
402 |        "q_1: ──■──\n",
403 |        "     ┌─┴─┐\n",
404 |        "q_2: ┤ X ├\n",
405 |        "     └───┘
" 406 | ], 407 | "text/plain": [ 408 | " \n", 409 | "q_0: ──■──\n", 410 | " │ \n", 411 | "q_1: ──■──\n", 412 | " ┌─┴─┐\n", 413 | "q_2: ┤ X ├\n", 414 | " └───┘" 415 | ] 416 | }, 417 | "execution_count": 9, 418 | "metadata": {}, 419 | "output_type": "execute_result" 420 | } 421 | ], 422 | "source": [ 423 | "#4.3 - Toffoli - AND/NAND gate\n", 424 | "#https://qiskit.org/textbook/ch-gates/more-circuit-identities.html#ccx\n", 425 | "#AND if the initial state of the target was |0>\n", 426 | "#NAND if target was |1>\n", 427 | "\n", 428 | "qc = QuantumCircuit(3)\n", 429 | "#a and b are the control bits\n", 430 | "a = 0\n", 431 | "b = 1\n", 432 | "#t is the target bit\n", 433 | "t = 2\n", 434 | "\n", 435 | "qc.ccx(a,b,t)\n", 436 | "qc.draw()" 437 | ] 438 | }, 439 | { 440 | "cell_type": "code", 441 | "execution_count": 15, 442 | "metadata": {}, 443 | "outputs": [ 444 | { 445 | "data": { 446 | "text/html": [ 447 | "
     ┌───┐ ░                 ░       \n",
448 |        "q_0: ┤ X ├─░───■─────────■───░───────\n",
449 |        "     ├───┤ ░   │         │   ░       \n",
450 |        "q_1: ┤ X ├─░───┼────■────■───░───────\n",
451 |        "     └───┘ ░ ┌─┴─┐┌─┴─┐  │   ░ ┌─┐   \n",
452 |        "q_2: ──────░─┤ X ├┤ X ├──┼───░─┤M├───\n",
453 |        "           ░ └───┘└───┘┌─┴─┐ ░ └╥┘┌─┐\n",
454 |        "q_3: ──────░───────────┤ X ├─░──╫─┤M├\n",
455 |        "           ░           └───┘ ░  ║ └╥┘\n",
456 |        "c: 2/═══════════════════════════╩══╩═\n",
457 |        "                                0  1
" 458 | ], 459 | "text/plain": [ 460 | " ┌───┐ ░ ░ \n", 461 | "q_0: ┤ X ├─░───■─────────■───░───────\n", 462 | " ├───┤ ░ │ │ ░ \n", 463 | "q_1: ┤ X ├─░───┼────■────■───░───────\n", 464 | " └───┘ ░ ┌─┴─┐┌─┴─┐ │ ░ ┌─┐ \n", 465 | "q_2: ──────░─┤ X ├┤ X ├──┼───░─┤M├───\n", 466 | " ░ └───┘└───┘┌─┴─┐ ░ └╥┘┌─┐\n", 467 | "q_3: ──────░───────────┤ X ├─░──╫─┤M├\n", 468 | " ░ └───┘ ░ ║ └╥┘\n", 469 | "c: 2/═══════════════════════════╩══╩═\n", 470 | " 0 1 " 471 | ] 472 | }, 473 | "execution_count": 15, 474 | "metadata": {}, 475 | "output_type": "execute_result" 476 | } 477 | ], 478 | "source": [ 479 | "qc_ha = QuantumCircuit(4,2)\n", 480 | "# encode inputs in qubits 0 and 1\n", 481 | "qc_ha.x(0) # For a=0, remove the this line. For a=1, leave it.\n", 482 | "qc_ha.x(1) # For b=0, remove the this line. For b=1, leave it.\n", 483 | "qc_ha.barrier()\n", 484 | "# use cnots to write the XOR of the inputs on qubit 2\n", 485 | "qc_ha.cx(0,2)\n", 486 | "qc_ha.cx(1,2)\n", 487 | "# use ccx to write the AND of the inputs on qubit 3\n", 488 | "qc_ha.ccx(0,1,3)\n", 489 | "qc_ha.barrier()\n", 490 | "# extract outputs\n", 491 | "qc_ha.measure(2,0) # extract XOR value\n", 492 | "qc_ha.measure(3,1) # extract AND value\n", 493 | "\n", 494 | "qc_ha.draw()" 495 | ] 496 | }, 497 | { 498 | "cell_type": "code", 499 | "execution_count": 16, 500 | "metadata": {}, 501 | "outputs": [ 502 | { 503 | "data": { 504 | "image/png": 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sOQr9AdVjyN4L3BMR52TmvfUxxw4z57FDTRgRC6gvxNDT08OKFSsAmDFjBpMnT2bdunUATJkyhVmzZrFy5UoAJk6cSF9fH2vXrmXHjh0A1Go1BgcHgRNH3XlJ0oG1detW1q9fD8D06dPp7e2lv78fgEmTJlGr1Vi1ahU7d+4EoK+vjw0bNrBt2zYAZs+evbdvOFGtvX7gRUQP1aPEzsnMlQ3t1wDvzsxXFs6zDHg2My+of94FvD8zlzaMmQcsycwXjjRXrVbLgYGBkYYUuez6/Z5CkrSfllzZnnkiYk1m1obq29fFDd4E/B7Vz7Y/zswVBZs9TvVklKlN7VOBR1v4+n7gXQ2fH23DnJIkjaqlC4EiYnpErAbupnoc2Eepfi7trx9JDiszdwFrgLlNXXOprqItdQrVz7Z7rGrDnJIkjarVI83/TnW0ODMzHwaIiBnAV+p97xhl++uAW+vBex9wOdUjxb5Qn2spQGbOq3++Evg58GOqc5rvAd4GXNQw5w3Ayoj4KPBN4O3AG4G+FvdNkqQRtRqac4E5ewITIDMfiohFwD2jbZyZt9WX4vs41f2WDwLnZ+am+pDm+zUPBT4L9AJPUYXnWzJzWcOc90fEu4BPUt328jPg4szsb3HfJEka0b6c0xzqyqHiq4ky80bgxmH65jR9/gzwmYI5b6d9V/lKkjSkVhc3uAf4fEQct6ehvprP9RQcaUqS9HzWamguAl4MPBQRmyJiE9XPoS+u90mSdNBq9efZfwFeD8wB9iya/tPM/Id2FiVJUicqDs2ImAD8CnhNZt5NdduJJEldo/jn2foi6ZuormiVJKnrtHpO878AfxkRRx+IYiRJ6mStntP8CNVTTrZExGaanq2ZmSe3qzBJkjpNq6F5O9U9mXEAapEkqaMVhWZEHE61Ms/bgBdQ3ZN5RWY+fuBKkySps5Se01wMzAe+A/wt1fMv/+cBqkmSpI5U+vPshcD7MvN/A0TEV4H7ImJC/apaSZIOeqVHmscB9+75kJmrgWepnlAiSVJXKA3NCcCuprZn2ceHWEuS9HxUGnoBfCUidja0HQYsiYgn9zRk5gXtLE6SpE5SGpq3DNH2lXYWIklSpysKzcz84wNdiCRJna7VZfQkSepahqYkSYUMTUmSChmakiQVMjQlSSpkaEqSVMjQlCSpkKEpSVIhQ1OSpEKGpiRJhQxNSZIKGZqSJBUyNCVJKmRoSpJUyNCUJKmQoSlJUiFDU5KkQoamJEmFDE1JkgoZmpIkFTI0JUkqZGhKklTI0JQkqZChKUlSIUNTkqRChqYkSYUMTUmSChmakiQVMjQlSSpkaEqSVGjMQzMiPhARD0fE0xGxJiLOGmHshRGxPCIei4hfR0R/RFzQNGZ+ROQQr8MO/N5IkrrJmIZmRFwM3ABcC5wK3A/cERHHD7PJOcB3gbfUxy8DvjFE0D4JTGt8ZebT7d8DSVI3mzjG33cVcHNmLql/viIi/hBYCHyseXBmfqipaXFEvAV4G3Dvvx2ajx6AeiVJ2mvMjjQj4lDgdcDypq7lwJktTDUZ2N7U9qKI2BQRmyPi7yPi1P0oVZKkIY3lkebRwARgsKl9EHhzyQQR8SdAL3BrQ/N64FJgHVWgfgi4LyJek5kbh5hjAbAAoKenhxUrVgAwY8YMJk+ezLp16wCYMmUKs2bNYuXKlQBMnDiRvr4+1q5dy44dOwCo1WoMDg4CJ5aUL0k6gLZu3cr69esBmD59Or29vfT39wMwadIkarUaq1atYufOnQD09fWxYcMGtm3bBsDs2bP39g0nMvMA7kLDF0X0AFuAczJzZUP7NcC7M/OVo2x/EVVYXpyZ3x5h3ATgn4DvZeaikeas1Wo5MDBQvhPDuOz6/Z5CkrSfllzZnnkiYk1m1obqG8sLgR4HdgNTm9qnAiOej4yId1AF5ryRAhMgM3cDA8BJ+16qJEnPNWahmZm7gDXA3KauuVRX0Q4pIt5JFZjzM/P20b4nIgI4Gdi679VKkvRcY3317HXArRGxGrgPuBzoAb4AEBFLATJzXv3zu6gC8yPAyog4tj7Prsx8oj7mz4EHgI3AEcAiqtBcOEb7JEnqEmMampl5W0RMAT5OdT/lg8D5mbmpPqT5fs3LqWq8vv7a4/vAnPr7lwI3AccCvwL+ETg7M1e3fQckSV1trI80ycwbgRuH6Zsz0udhtvkw8OF21CZJ0khce1aSpEKGpiRJhQxNSZIKGZqSJBUyNCVJKmRoSpJUyNCUJKmQoSlJUiFDU5KkQoamJEmFDE1JkgoZmpIkFTI0JUkqZGhKklTI0JQkqZChKUlSIUNTkqRChqYkSYUMTUmSChmakiQVMjQlSSpkaEqSVMjQlCSpkKEpSVIhQ1OSpEKGpiRJhQxNSZIKGZqSJBUyNCVJKmRoSpJUyNCUJKmQoSlJUiFDU5KkQoamJEmFDE1JkgoZmpIkFTI0JUkqZGhKklTI0JQkqZChKUlSIUNTkqRChqYkSYUMTUmSChmakiQVMjQlSSo05qEZER+IiIcj4umIWBMRZ40y/pz6uKcj4qGIuHx/55QkaV+MaWhGxMXADcC1wKnA/cAdEXH8MONfASyrjzsV+DTw+Yi4aF/nlCRpX431keZVwM2ZuSQzf5qZVwBbgYXDjL8ceCQzr6iPXwLcAnxkP+aUJGmfjFloRsShwOuA5U1dy4Ezh9nsjCHG3wXUIuIF+zinJEn7ZOIYftfRwARgsKl9EHjzMNscC/zDEOMn1ueLVueMiAXAgvrH30TE+pLipS5wNPD4eBch7au/+XDbpnr5cB1jGZodITNvAm4a7zqkThMRA5lZG+86pE42lqH5OLAbmNrUPhV4dJhtHh1m/LP1+WIf5pQkaZ+M2TnNzNwFrAHmNnXNpbridSirhhk/kJnP7OOckiTtk7H+efY64NaIWA3cR3V1bA/wBYCIWAqQmfPq478AfDAirge+CLwBmA9cUjqnpGKetpBGMaahmZm3RcQU4OPANOBB4PzM3FQfcnzT+Icj4nzgv1HdQvIIsCgzv97CnJIK1M/3SxpBZOZ41yBJ0vOCa89KklTI0JQkqZChKUlSIUNT6nIREY1/JQ3PC4Ek/Rt7wjP9x0F6jq5bRk9SJSIOAd4KvAw4HNgCfD8zt41rYVIH80hT6kIRMRn4EvBG4HfAZiCBp4HvA7dm5v+LiPCIU/pXHmlK3WkR8EqqhUB+EBGvAmpUq279AfDqiHhfZj42nkVKncYjTakLRcS9wDcy87qm9glUwfkl4GeZ+YfjUZ/Uqbx6VuoyETGRarnJiyLiZfW2CRFxSGbuzsyVVGs490bEa8azVqnTGJpSl8nMZ4FbqB7y/pGImFoPy981DNsAnIAPpZb+DX+elbpM/arZQ4A/Bq6lurbh68BtwD8DJwP/Hvi9zDxtvOqUOpGhKXWxiHgp1eP2/gNwCvBrqitofwB8OjP7x6s2qRMZmlIXiYgjgF833kZSP/I8DJgEzAZ+a1hKQzM0pS4SEV8EVtdfmzJzxxBjjszM7d6jKT2XoSl1iYi4BPgqsAN4ArgbuAv4IbAlM5+KiEnAV4CrM/NH41as1KEMTalLRMQSYDfwGeBC4I+AE4H1wDLgHqoFD27IzEPHq06pkxmaUheo35v5p8ARmfnRhvZZwGXAO6jOa74UuCUz3zcedUqdztCUukREHAlMra8peyjwTNMFQRcDfwu8NjP/aZzKlDqaa89KXSIztwPb6+93wd4rZyMzdwNHAE8bmNLwDE2pizWtAjQZ+PPxqkV6PvDnWUkARMQLgObl9CQ1MDQlSSrkgu2SJBUyNCVJKmRoSpJUyNCUJKmQoSlJUiFDU5KkQv8fAbojUovj32kAAAAASUVORK5CYII=\n", 505 | "text/plain": [ 506 | "
" 507 | ] 508 | }, 509 | "execution_count": 16, 510 | "metadata": {}, 511 | "output_type": "execute_result" 512 | } 513 | ], 514 | "source": [ 515 | "counts = execute(qc_ha,Aer.get_backend('qasm_simulator')).result().get_counts()\n", 516 | "plot_histogram(counts)" 517 | ] 518 | }, 519 | { 520 | "cell_type": "code", 521 | "execution_count": 17, 522 | "metadata": {}, 523 | "outputs": [ 524 | { 525 | "data": { 526 | "text/html": [ 527 | "
                ░                 ░       \n",
528 |        "q_0: ───────────░───■─────────■───░───────\n",
529 |        "     ┌───┐┌───┐ ░   │         │   ░       \n",
530 |        "q_1: ┤ X ├┤ X ├─░───┼────■────■───░───────\n",
531 |        "     └───┘└───┘ ░ ┌─┴─┐┌─┴─┐  │   ░ ┌─┐   \n",
532 |        "q_2: ───────────░─┤ X ├┤ X ├──┼───░─┤M├───\n",
533 |        "                ░ └───┘└───┘┌─┴─┐ ░ └╥┘┌─┐\n",
534 |        "q_3: ───────────░───────────┤ X ├─░──╫─┤M├\n",
535 |        "                ░           └───┘ ░  ║ └╥┘\n",
536 |        "c: 2/════════════════════════════════╩══╩═\n",
537 |        "                                     0  1
" 538 | ], 539 | "text/plain": [ 540 | " ░ ░ \n", 541 | "q_0: ───────────░───■─────────■───░───────\n", 542 | " ┌───┐┌───┐ ░ │ │ ░ \n", 543 | "q_1: ┤ X ├┤ X ├─░───┼────■────■───░───────\n", 544 | " └───┘└───┘ ░ ┌─┴─┐┌─┴─┐ │ ░ ┌─┐ \n", 545 | "q_2: ───────────░─┤ X ├┤ X ├──┼───░─┤M├───\n", 546 | " ░ └───┘└───┘┌─┴─┐ ░ └╥┘┌─┐\n", 547 | "q_3: ───────────░───────────┤ X ├─░──╫─┤M├\n", 548 | " ░ └───┘ ░ ║ └╥┘\n", 549 | "c: 2/════════════════════════════════╩══╩═\n", 550 | " 0 1 " 551 | ] 552 | }, 553 | "execution_count": 17, 554 | "metadata": {}, 555 | "output_type": "execute_result" 556 | } 557 | ], 558 | "source": [ 559 | "#mess around with the inputs\n", 560 | "qc_ha = QuantumCircuit(4,2)\n", 561 | "# encode inputs in qubits 0 and 1\n", 562 | "qc_ha.x(1) # For a=0, remove the this line. For a=1, leave it.\n", 563 | "qc_ha.x(1) # For b=0, remove the this line. For b=1, leave it.\n", 564 | "qc_ha.barrier()\n", 565 | "# use cnots to write the XOR of the inputs on qubit 2\n", 566 | "qc_ha.cx(0,2)\n", 567 | "qc_ha.cx(1,2)\n", 568 | "# use ccx to write the AND of the inputs on qubit 3\n", 569 | "qc_ha.ccx(0,1,3)\n", 570 | "qc_ha.barrier()\n", 571 | "# extract outputs\n", 572 | "qc_ha.measure(2,0) # extract XOR value\n", 573 | "qc_ha.measure(3,1) # extract AND value\n", 574 | "\n", 575 | "qc_ha.draw()" 576 | ] 577 | }, 578 | { 579 | "cell_type": "code", 580 | "execution_count": 18, 581 | "metadata": {}, 582 | "outputs": [ 583 | { 584 | "data": { 585 | "image/png": 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\n", 586 | "text/plain": [ 587 | "
" 588 | ] 589 | }, 590 | "execution_count": 18, 591 | "metadata": {}, 592 | "output_type": "execute_result" 593 | } 594 | ], 595 | "source": [ 596 | "counts = execute(qc_ha,Aer.get_backend('qasm_simulator')).result().get_counts()\n", 597 | "plot_histogram(counts)" 598 | ] 599 | }, 600 | { 601 | "cell_type": "code", 602 | "execution_count": 19, 603 | "metadata": {}, 604 | "outputs": [ 605 | { 606 | "data": { 607 | "text/plain": [ 608 | "{'qiskit-terra': '0.16.0',\n", 609 | " 'qiskit-aer': '0.7.0',\n", 610 | " 'qiskit-ignis': '0.5.0',\n", 611 | " 'qiskit-ibmq-provider': '0.11.0',\n", 612 | " 'qiskit-aqua': '0.8.0',\n", 613 | " 'qiskit': '0.23.0'}" 614 | ] 615 | }, 616 | "execution_count": 19, 617 | "metadata": {}, 618 | "output_type": "execute_result" 619 | } 620 | ], 621 | "source": [ 622 | "import qiskit\n", 623 | "qiskit.__qiskit_version__" 624 | ] 625 | }, 626 | { 627 | "cell_type": "code", 628 | "execution_count": null, 629 | "metadata": {}, 630 | "outputs": [], 631 | "source": [] 632 | } 633 | ], 634 | "metadata": { 635 | "kernelspec": { 636 | "display_name": "Python 3", 637 | "language": "python", 638 | "name": "python3" 639 | }, 640 | "language_info": { 641 | "codemirror_mode": { 642 | "name": "ipython", 643 | "version": 3 644 | }, 645 | "file_extension": ".py", 646 | "mimetype": "text/x-python", 647 | "name": "python", 648 | "nbconvert_exporter": "python", 649 | "pygments_lexer": "ipython3", 650 | "version": "3.8.5" 651 | } 652 | }, 653 | "nbformat": 4, 654 | "nbformat_minor": 4 655 | } 656 | -------------------------------------------------------------------------------- /Ryan30/setting-the-environment.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": { 6 | "tags": [ 7 | "remove_cell" 8 | ] 9 | }, 10 | "source": [ 11 | "## Environment Setup Guide to work with Qiskit Textbook" 12 | ] 13 | }, 14 | { 15 | "cell_type": "markdown", 16 | "metadata": {}, 17 | "source": [ 18 | "This is a comprehensive guide for setting up your environment on your personal computer for working with Qiskit Textbook. This will help you reproduce the results as you see them on the textbook website. The Qiskit Textbook is written in [Jupyter notebooks](https://jupyter.org/install). Notebooks and [the website](https://qiskit.org/textbook/preface.html) are the only media in which the Textbook is fully supported." 19 | ] 20 | }, 21 | { 22 | "cell_type": "markdown", 23 | "metadata": {}, 24 | "source": [ 25 | "## Installing the qiskit_textbook Package\n", 26 | "\n", 27 | "The Qiskit Textbook provides some tools and widgets specific to the Textbook. This is not part of Qiskit and is available through the `qiskit_textbook` package. The quickest way to install this with [Pip](http://pypi.org/project/pip/) and [Git](http://git-scm.com/) is through the command:\n", 28 | "\n", 29 | "```\n", 30 | "pip install git+https://github.com/qiskit-community/qiskit-textbook.git#subdirectory=qiskit-textbook-src\n", 31 | "```\n", 32 | "Alternatively, you can download the folder [qiskit-textbook-src](https://github.com/qiskit-community/qiskit-textbook) from the Github and run:\n", 33 | "\n", 34 | "```\n", 35 | "pip install ./qiskit-textbook-src\n", 36 | "```\n", 37 | "\n", 38 | "from the directory that contains this folder.\n" 39 | ] 40 | }, 41 | { 42 | "cell_type": "markdown", 43 | "metadata": {}, 44 | "source": [ 45 | "## Steps to reproduce exact prerendered output as given in qiskit textbook (Optional)" 46 | ] 47 | }, 48 | { 49 | "cell_type": "markdown", 50 | "metadata": {}, 51 | "source": [ 52 | "### 1. Setting up default drawer to MatPlotLib\n", 53 | "\n", 54 | "The default backend for `QuantumCircuit.draw()` or `qiskit.visualization.circuit_drawer()` is the text backend. However, depending on your local environment you may want to change these defaults to something better suited for your use case. This is done with the user config file. By default the user config file should be located in `~/.qiskit/settings.conf` and is a `.ini` file.\n", 55 | "\n", 56 | "Qiskit Textbook uses default circuit drawer as MatPlotLib. To reproduce visualizations as given in qiskit textbook create a `settings.conf` file (usually found in `~/.qiskit/`) with contents:" 57 | ] 58 | }, 59 | { 60 | "cell_type": "markdown", 61 | "metadata": {}, 62 | "source": [ 63 | " [default]\n", 64 | " circuit_drawer = mpl" 65 | ] 66 | }, 67 | { 68 | "cell_type": "markdown", 69 | "metadata": {}, 70 | "source": [ 71 | "### 2. Setting up default image type to svg\n", 72 | "\n", 73 | "Optionally, you can add the following line of code to the `ipython_kernel_config.py` file (usually found in `~/.ipython/profile_default/`) to set the default image format from PNG to the more scaleable SVG format:" 74 | ] 75 | }, 76 | { 77 | "cell_type": "markdown", 78 | "metadata": {}, 79 | "source": [ 80 | " c.InlineBackend.figure_format = 'svg'" 81 | ] 82 | }, 83 | { 84 | "cell_type": "markdown", 85 | "metadata": {}, 86 | "source": [ 87 | "### 3. Syncing with the Qiskit versions used in the Textbook\n", 88 | "\n", 89 | "You will find a code snippet at the end of the most tutorials which will contain the information on which versions of qiskit packages are used in the tutorial. If you find inconsistency in syntax and/or outputs, try to use the same version.\n", 90 | "\n", 91 | "To check the version installed in your computer, run the following in Python shell or Jupyter Notebook:" 92 | ] 93 | }, 94 | { 95 | "cell_type": "markdown", 96 | "metadata": {}, 97 | "source": [ 98 | " import qiskit\n", 99 | " qiskit.__qiskit_version__" 100 | ] 101 | } 102 | ], 103 | "metadata": { 104 | "kernelspec": { 105 | "display_name": "Python 3", 106 | "language": "python", 107 | "name": "python3" 108 | }, 109 | "language_info": { 110 | "codemirror_mode": { 111 | "name": "ipython", 112 | "version": 3 113 | }, 114 | "file_extension": ".py", 115 | "mimetype": "text/x-python", 116 | "name": "python", 117 | "nbconvert_exporter": "python", 118 | "pygments_lexer": "ipython3", 119 | "version": "3.7.6" 120 | } 121 | }, 122 | "nbformat": 4, 123 | "nbformat_minor": 2 124 | } 125 | -------------------------------------------------------------------------------- /SunilK/BlochSphereAnimation.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "# Very nicely done animation\n", 10 | "# https://sites.google.com/site/tanayroysite/articles/bloch-sphere-animation-using-qutip" 11 | ] 12 | }, 13 | { 14 | "cell_type": "code", 15 | "execution_count": 9, 16 | "metadata": {}, 17 | "outputs": [], 18 | "source": [ 19 | "import matplotlib as mpl\n", 20 | "from pylab import *\n", 21 | "from qutip import *\n", 22 | "from matplotlib import cm\n", 23 | "import imageio\n", 24 | "\n", 25 | "def animate_bloch(states, duration=0.1, save_all=False):\n", 26 | "\n", 27 | " b = Bloch()\n", 28 | " b.vector_color = ['r']\n", 29 | " b.view = [-40,30]\n", 30 | " images=[]\n", 31 | " try:\n", 32 | " length = len(states)\n", 33 | " except:\n", 34 | " length = 1\n", 35 | " states = [states]\n", 36 | " ## normalize colors to the length of data ##\n", 37 | " nrm = mpl.colors.Normalize(0,length)\n", 38 | " colors = cm.cool(nrm(range(length))) # options: cool, summer, winter, autumn etc.\n", 39 | "\n", 40 | " ## customize sphere properties ##\n", 41 | " b.point_color = list(colors) # options: 'r', 'g', 'b' etc.\n", 42 | " b.point_marker = ['o']\n", 43 | " b.point_size = [30]\n", 44 | " \n", 45 | " for i in range(length):\n", 46 | " b.clear()\n", 47 | " b.add_states(states[i])\n", 48 | " b.add_states(states[:(i+1)],'point')\n", 49 | " if save_all:\n", 50 | " b.save(dirc='tmp') #saving images to tmp directory\n", 51 | " filename=\"tmp/bloch_%01d.png\" % i\n", 52 | " else:\n", 53 | " filename='temp_file.png'\n", 54 | " b.save(filename)\n", 55 | " images.append(imageio.imread(filename))\n", 56 | " imageio.mimsave('bloch_anim.gif', images, duration=duration)" 57 | ] 58 | }, 59 | { 60 | "cell_type": "code", 61 | "execution_count": 10, 62 | "metadata": {}, 63 | "outputs": [], 64 | "source": [ 65 | "states = []\n", 66 | "thetas = linspace(0,pi,21)\n", 67 | "for theta in thetas:\n", 68 | " states.append((cos(theta/2)*basis(2,0) + sin(theta/2)*basis(2,1)).unit())\n", 69 | "\n", 70 | "animate_bloch(states, duration=0.1, save_all=False)" 71 | ] 72 | }, 73 | { 74 | "cell_type": "markdown", 75 | "metadata": {}, 76 | "source": [ 77 | "![SegmentLocal](bloch_anim.gif \"segment\")" 78 | ] 79 | }, 80 | { 81 | "cell_type": "code", 82 | "execution_count": null, 83 | "metadata": {}, 84 | "outputs": [], 85 | "source": [] 86 | } 87 | ], 88 | "metadata": { 89 | "kernelspec": { 90 | "display_name": "Python 3", 91 | "language": "python", 92 | "name": "python3" 93 | }, 94 | "language_info": { 95 | "codemirror_mode": { 96 | "name": "ipython", 97 | "version": 3 98 | }, 99 | "file_extension": ".py", 100 | "mimetype": "text/x-python", 101 | "name": "python", 102 | "nbconvert_exporter": "python", 103 | "pygments_lexer": "ipython3", 104 | "version": "3.8.3" 105 | } 106 | }, 107 | "nbformat": 4, 108 | "nbformat_minor": 4 109 | } 110 | -------------------------------------------------------------------------------- /SunilK/Local Module Test.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "# create a hello module inside a folder called mymodules (you name this folder anything you want)\n", 10 | "# bring up a terminal or command line prompt in that folder\n", 11 | "# Create your module. e.g., hello.py\n", 12 | "# def hello():\n", 13 | "# print ('hello')\n", 14 | "# return\n", 15 | "#\n", 16 | "# run this: python -m py_compile hello.py\n", 17 | "# Create a new notebook like this" 18 | ] 19 | }, 20 | { 21 | "cell_type": "code", 22 | "execution_count": 18, 23 | "metadata": {}, 24 | "outputs": [], 25 | "source": [ 26 | "# import the module\n", 27 | "from mymodules import hello" 28 | ] 29 | }, 30 | { 31 | "cell_type": "code", 32 | "execution_count": 19, 33 | "metadata": {}, 34 | "outputs": [ 35 | { 36 | "name": "stdout", 37 | "output_type": "stream", 38 | "text": [ 39 | "hello\n" 40 | ] 41 | } 42 | ], 43 | "source": [ 44 | "#call the module\n", 45 | "hello.hello()" 46 | ] 47 | }, 48 | { 49 | "cell_type": "code", 50 | "execution_count": null, 51 | "metadata": {}, 52 | "outputs": [], 53 | "source": [] 54 | }, 55 | { 56 | "cell_type": "code", 57 | "execution_count": null, 58 | "metadata": {}, 59 | "outputs": [], 60 | "source": [] 61 | } 62 | ], 63 | "metadata": { 64 | "kernelspec": { 65 | "display_name": "Python 3", 66 | "language": "python", 67 | "name": "python3" 68 | }, 69 | "language_info": { 70 | "codemirror_mode": { 71 | "name": "ipython", 72 | "version": 3 73 | }, 74 | "file_extension": ".py", 75 | "mimetype": "text/x-python", 76 | "name": "python", 77 | "nbconvert_exporter": "python", 78 | "pygments_lexer": "ipython3", 79 | "version": "3.8.3" 80 | } 81 | }, 82 | "nbformat": 4, 83 | "nbformat_minor": 4 84 | } 85 | -------------------------------------------------------------------------------- /SunilK/bloch_anim.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sktxdev/Quantum-Computing/2d72a87d4b8268fafed8f1509d558d6625ef3adc/SunilK/bloch_anim.gif -------------------------------------------------------------------------------- /SunilK/mymodules/hello.py: -------------------------------------------------------------------------------- 1 | def hello(): 2 | print ('hello') 3 | return 4 | -------------------------------------------------------------------------------- /Touny.md: -------------------------------------------------------------------------------- 1 | ### Quantum Phase Estimation 2 | For week 18 oct ~ 24 oct, I would like to talk about _Quantum Phase Estimation_. It is a critical promising subroutine for quantum algorithms. My apologies, but due to my limited time I won't be able to write full details here. However, We might discuss in details during the presentation. Here are some useful links, 3 | - [wikipedia](https://en.wikipedia.org/wiki/Quantum_phase_estimation_algorithm) 4 | - [QuTech Academy](https://www.youtube.com/watch?v=v1AUILJz3RU) 5 | -------------------------------------------------------------------------------- /minhpham/Chapter 1 Edit.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sktxdev/Quantum-Computing/2d72a87d4b8268fafed8f1509d558d6625ef3adc/minhpham/Chapter 1 Edit.pdf -------------------------------------------------------------------------------- /minhpham/Chapter 2 Edit.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sktxdev/Quantum-Computing/2d72a87d4b8268fafed8f1509d558d6625ef3adc/minhpham/Chapter 2 Edit.pdf -------------------------------------------------------------------------------- /minhpham/Q Notes.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sktxdev/Quantum-Computing/2d72a87d4b8268fafed8f1509d558d6625ef3adc/minhpham/Q Notes.pdf -------------------------------------------------------------------------------- /minhpham/README.md: -------------------------------------------------------------------------------- 1 | Storing mathematical proofs of circuit components in quantum algorithms. 2 | -------------------------------------------------------------------------------- /minhpham/Scratch.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "# IMPORT THIS!!!" 8 | ] 9 | }, 10 | { 11 | "cell_type": "code", 12 | "execution_count": 3, 13 | "metadata": {}, 14 | "outputs": [ 15 | { 16 | "name": "stderr", 17 | "output_type": "stream", 18 | "text": [ 19 | "Duplicate key in file '/Users/minhpham/.matplotlib/matplotlibrc' line #2.\n", 20 | "Duplicate key in file '/Users/minhpham/.matplotlib/matplotlibrc' line #3.\n" 21 | ] 22 | } 23 | ], 24 | "source": [ 25 | "import numpy as np\n", 26 | "import matplotlib\n", 27 | "import matplotlib.pyplot as plt\n", 28 | "import scipy.integrate as integrate\n", 29 | "import quadpy\n", 30 | "import random\n", 31 | "import math" 32 | ] 33 | }, 34 | { 35 | "cell_type": "code", 36 | "execution_count": 247, 37 | "metadata": {}, 38 | "outputs": [ 39 | { 40 | "data": { 41 | "text/plain": [ 42 | "(5, 73, 365, 309)" 43 | ] 44 | }, 45 | "execution_count": 247, 46 | "metadata": {}, 47 | "output_type": "execute_result" 48 | } 49 | ], 50 | "source": [ 51 | "p = random.choice(prime_list)\n", 52 | "q = random.choice(prime_list)\n", 53 | "M = p*q\n", 54 | "guess = random.randint(2, M)\n", 55 | "\n", 56 | "p, q, M, guess" 57 | ] 58 | }, 59 | { 60 | "cell_type": "code", 61 | "execution_count": 248, 62 | "metadata": {}, 63 | "outputs": [], 64 | "source": [ 65 | "def Shor(M, guess): \n", 66 | " pf = lambda guess, M: np.array([guess**b%M for b in range(2, 5000)]) \n", 67 | " \n", 68 | " if math.gcd(M, guess) !=1: \n", 69 | " \n", 70 | " return math.gcd(M, guess), int(M/math.gcd(M, guess)) \n", 71 | " \n", 72 | " peak = np.where(pf(guess, M)==1)[0]\n", 73 | " \n", 74 | " r = peak[1]-peak[0] \n", 75 | " return math.gcd(M, int(guess**(r/2)-1)), math.gcd(M, int(guess**(r/2)+1))" 76 | ] 77 | }, 78 | { 79 | "cell_type": "code", 80 | "execution_count": 249, 81 | "metadata": {}, 82 | "outputs": [ 83 | { 84 | "data": { 85 | "text/plain": [ 86 | "(1, 1)" 87 | ] 88 | }, 89 | "execution_count": 249, 90 | "metadata": {}, 91 | "output_type": "execute_result" 92 | } 93 | ], 94 | "source": [ 95 | "Shor(M, guess)" 96 | ] 97 | }, 98 | { 99 | "cell_type": "code", 100 | "execution_count": 246, 101 | "metadata": {}, 102 | "outputs": [ 103 | { 104 | "data": { 105 | "text/plain": [ 106 | "(array([ 2, 6, 10, ..., 4986, 4990, 4994]),)" 107 | ] 108 | }, 109 | "execution_count": 246, 110 | "metadata": {}, 111 | "output_type": "execute_result" 112 | } 113 | ], 114 | "source": [ 115 | "np.where(np.array([guess**r%M for r in range(2, 5000)]) ==1)" 116 | ] 117 | }, 118 | { 119 | "cell_type": "code", 120 | "execution_count": 236, 121 | "metadata": {}, 122 | "outputs": [ 123 | { 124 | "data": { 125 | "text/plain": [ 126 | "1" 127 | ] 128 | }, 129 | "execution_count": 236, 130 | "metadata": {}, 131 | "output_type": "execute_result" 132 | } 133 | ], 134 | "source": [ 135 | "math.gcd(M, 31-1)" 136 | ] 137 | }, 138 | { 139 | "cell_type": "code", 140 | "execution_count": 1, 141 | "metadata": {}, 142 | "outputs": [ 143 | { 144 | "name": "stderr", 145 | "output_type": "stream", 146 | "text": [ 147 | "Duplicate key in file '/Users/minhpham/.matplotlib/matplotlibrc' line #2.\n", 148 | "Duplicate key in file '/Users/minhpham/.matplotlib/matplotlibrc' line #3.\n" 149 | ] 150 | } 151 | ], 152 | "source": [ 153 | "from qiskit import *" 154 | ] 155 | }, 156 | { 157 | "cell_type": "code", 158 | "execution_count": 80, 159 | "metadata": {}, 160 | "outputs": [ 161 | { 162 | "data": { 163 | "text/plain": [ 164 | "" 165 | ] 166 | }, 167 | "execution_count": 80, 168 | "metadata": {}, 169 | "output_type": "execute_result" 170 | } 171 | ], 172 | "source": [ 173 | "circuit = QuantumCircuit(3, 3)\n", 174 | "circuit.h([0, 1, 2])\n", 175 | "circuit.measure([0, 1, 2], [0, 1, 2])" 176 | ] 177 | }, 178 | { 179 | "cell_type": "code", 180 | "execution_count": 81, 181 | "metadata": {}, 182 | "outputs": [], 183 | "source": [ 184 | "%matplotlib inline " 185 | ] 186 | }, 187 | { 188 | "cell_type": "code", 189 | "execution_count": 144, 190 | "metadata": {}, 191 | "outputs": [ 192 | { 193 | "data": { 194 | "image/png": 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\n", 195 | "text/plain": [ 196 | "
" 197 | ] 198 | }, 199 | "execution_count": 144, 200 | "metadata": {}, 201 | "output_type": "execute_result" 202 | } 203 | ], 204 | "source": [ 205 | "circuit.draw(output = 'mpl')" 206 | ] 207 | }, 208 | { 209 | "cell_type": "code", 210 | "execution_count": null, 211 | "metadata": {}, 212 | "outputs": [], 213 | "source": [ 214 | "provider = IBMQ.get_provider('ibm-q')\n", 215 | "\n", 216 | "qcomp = provider.get_backend('ibmq_vigo', )\n", 217 | "\n", 218 | "job = execute(circuit, backend = qcomp, shots = 1)\n", 219 | "\n", 220 | "job_monitor(job)\n", 221 | "\n", 222 | "results = job.result()\n", 223 | "\n", 224 | "plot_histogram(results.get_counts(circuit))" 225 | ] 226 | }, 227 | { 228 | "cell_type": "code", 229 | "execution_count": null, 230 | "metadata": {}, 231 | "outputs": [], 232 | "source": [ 233 | "a = list(results.get_counts().keys())[0]\n", 234 | "int(a, 2)" 235 | ] 236 | }, 237 | { 238 | "cell_type": "code", 239 | "execution_count": null, 240 | "metadata": {}, 241 | "outputs": [], 242 | "source": [] 243 | } 244 | ], 245 | "metadata": { 246 | "kernelspec": { 247 | "display_name": "Python 3", 248 | "language": "python", 249 | "name": "python3" 250 | }, 251 | "language_info": { 252 | "codemirror_mode": { 253 | "name": "ipython", 254 | "version": 3 255 | }, 256 | "file_extension": ".py", 257 | "mimetype": "text/x-python", 258 | "name": "python", 259 | "nbconvert_exporter": "python", 260 | "pygments_lexer": "ipython3", 261 | "version": "3.7.4" 262 | } 263 | }, 264 | "nbformat": 4, 265 | "nbformat_minor": 4 266 | } 267 | --------------------------------------------------------------------------------