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Basic QRNG Implementation
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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"id": "88aa4ff3", | |
"metadata": {}, | |
"source": [ | |
"# Quantum Random Number Generator" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "23645a59", | |
"metadata": {}, | |
"source": [ | |
"## Imports" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"id": "8b59b39c", | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"from qiskit import Aer, execute, QuantumCircuit\n", | |
"from random import random, randint" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "ab6012b5", | |
"metadata": {}, | |
"source": [ | |
"## Helper Functions" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"id": "4a372a5b", | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"def execute_qc(qc):\n", | |
" backend_sim = Aer.get_backend('qasm_simulator')\n", | |
" sim = execute(qc, backend_sim, shots=1)\n", | |
" sim_result = sim.result()\n", | |
" counts = sim_result.get_counts(qc)\n", | |
" return int(list(counts.keys())[0].split(' ')[0], 2)\n", | |
"\n", | |
"def qrng(num_qubits):\n", | |
" qc = QuantumCircuit(num_qubits, num_qubits)\n", | |
" qc.h(range(num_qubits))\n", | |
" qc.measure_all()\n", | |
" return execute_qc(qc)\n", | |
"\n", | |
"def qrandom():\n", | |
" num_qubits = 10\n", | |
" qrn = qrng(num_qubits)\n", | |
" return qrn / int('1' * num_qubits, 2)\n", | |
"\n", | |
"def qrandint(a, b):\n", | |
" _min = 0\n", | |
" _max = b - a\n", | |
" num_qubits = len(bin(_max)[2:])\n", | |
" qrn = _max + 1\n", | |
" while qrn > _max:\n", | |
" qrn = qrng(num_qubits)\n", | |
" return a + qrn" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "82c6557c", | |
"metadata": {}, | |
"source": [ | |
"## Random Number Generation" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"id": "eb9171c8", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"1" | |
] | |
}, | |
"execution_count": 3, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"randint(1,10)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"id": "af8e5c83", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"1" | |
] | |
}, | |
"execution_count": 4, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"qrandint(1,10)" | |
] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.8.8" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 5 | |
} |
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