{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Shared Randomness mit zwei verschränkten Qubits\n", "\n", "Die beiden folgenden Schaltkreise erzeugen zwei verschränkte Qubits\n", "$$\n", "\\frac{1}{\\sqrt{2}} \\left(|00\\rangle + |11\\rangle \\right)\n", "$$\n", "die dann anschließend in zwei verschiedenen Basen gemessen werden. Einmal in der Standardbasis und einmal in der Hadamard-Basis (Anwendung von Hadamard vor der Messung)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Messung in der Standardbasis" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import qiskit\n", "from qiskit import QuantumCircuit, ClassicalRegister, QuantumRegister, transpile, execute, Aer, IBMQ\n", "from qiskit.tools.visualization import circuit_drawer\n", "from qiskit.visualization import plot_histogram\n", "\n", "import matplotlib.pyplot as plt\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "backend = Aer.get_backend('qasm_simulator')" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "qc_cb = QuantumCircuit(2,2)\n", "\n", "qc_cb.h(0)\n", "qc_cb.cx(0,1)\n", "qc_cb.barrier()\n", "qc_cb.measure([1,0],[0,1])\n", "qc_cb.draw('mpl')" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'11': 4997, '00': 5003}\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Simmulation von 10000 Messungen\n", "job = execute(qc_cb, backend, shots=10000)\n", "result = job.result()\n", "counts = result.get_counts(qc_cb)\n", "print(counts)\n", "plot_histogram(counts)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Messung in der Hadamard-Basis\n", "\n", "Vor den jeweiligen Messungen wird Hadamard angewendet." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "qc_hb = QuantumCircuit(2,2)\n", "\n", "qc_hb.h(0)\n", "qc_hb.cx(0,1)\n", "qc_hb.barrier()\n", "# Anwendung von Hadamard vor der Messung\n", "qc_hb.h(0)\n", "qc_hb.h(1)\n", "qc_hb.measure([1,0],[0,1])\n", "qc_hb.draw('mpl')" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'00': 4972, '11': 5028}\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Simmulation von 10000 Messungen\n", "job = execute(qc_hb, backend, shots=10000)\n", "result = job.result()\n", "counts = result.get_counts(qc_hb)\n", "print(counts)\n", "plot_histogram(counts)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.8.12" } }, "nbformat": 4, "nbformat_minor": 2 }