{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Entanglement Distillation\n", "\n", "Simulation eines \"Entanglement Distillation\"" ] }, { "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.circuit import QuantumCircuit,Parameter\n", "from qiskit.tools.visualization import circuit_drawer\n", "from qiskit.visualization import plot_histogram\n", "\n", "#import python stuff\n", "import matplotlib.pyplot as plt\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "|Psi> = alpha |0> + beta |1>\n", "alpha^2 : 0.750000\n", "beta^2 : 0.250000\n" ] } ], "source": [ "backend = Aer.get_backend('qasm_simulator')\n", "phi = Parameter('Phi')\n", "\n", "phi_value = np.pi/6 \n", "print(\"|Psi> = alpha |0> + beta |1>\")\n", "print(\"alpha^2 : {:>5f}\".format(np.cos(phi_value)**2) )\n", "print(\"beta^2 : {:>5f}\".format(np.sin(phi_value)**2) )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Erzeugung eines Zustand\n", "\n", "$$\n", "|\\Psi\\rangle = \\sqrt{\\frac{3}{4}} |0\\rangle + \\sqrt{\\frac{1}{4}} |1\\rangle\n", "$$\n", "\n", "Beachte: Der Zustand entspricht keiner gleichmäßigen Superposition!" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "circuit1 = QuantumCircuit(1,1)\n", "circuit1.ry(2*phi,0)\n", "circuit1.measure([0],[0])\n", "circuit1.draw('mpl')" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'0': 7500, '1': 2500}\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "runcircuit1 = circuit1.bind_parameters({phi: phi_value })\n", "\n", "job = execute(runcircuit1, backend, shots=10000)\n", "result = job.result()\n", "counts = result.get_counts(runcircuit1)\n", "print(counts)\n", "plot_histogram(counts)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Erzeugung eines verschränkten Zustands\n", "\n", "Das Qubit $q_0$ ist hier nicht in einer gleichmäßigen Superposition. Somit erhält man auch keinen Bell-Zustand (maximal verschränkten Zustand)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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n+D6FWbNmAfVzCpbU0lwgNMwhvPvuu5w7d47g4GAiIyPJy8tr3C42NhaDwWDdJ4OdhkJAQABDhw4lLS2NHj160KdPH7Zv387u3bsBrBIKnU0fb2UoWIt/D+u36eiio6MB2Lt3b5vrthYIACaTCYPBQGJiItHR0YpQsBW77PtptVq2bdvWOJaaN28eer2e1NRUdDpd4ySjsFxgT9u0G2Cjdh2Vi4sLQUFB1NbW8sUXrR/I0VYgNGj4qrewsDBblNyEXfYUAIKDg9m3b59iWWJiIqGhoXTp0kWlqhxX9AB4J7/+UGdr6feT+h6IUHr88cfRaDTU1rZ8goiTkxPbt29vMxAADhw4wKpVqzh06JCtSlbW1i57sZLc3FxiYmIUy1auXMmrr77KhQsXOHbsGEuXLsVoNBIYGKhSlfapmyvEBEDWl9ZrMy7Uem11FDU1NTz11FNtrldbW8vMmTNZtGgRKSkprR6HkJOTY/FHmtZgl8OH5lRWVlJYWNjkoKVVq1ZRUlJCdXU1Fy9epKSkRAKhBVOHQfem59vcliF+EO5vnbY6q5ycHObNm9euByZZwmF6Cu7u7phMVuz7dkJuzvDr0fDSxy0PIyz51EHvDvePsNmnnEJlDtNTENYR0BNSxoHrbb4d/NQDUieCh0zrdFgSCp1QsA/8Lh4G3uJpz2OC4Le/AO9utqlL2AeHGT4I69J7wKIJcPx8/Re3nvwamjvMxkUHkf1hTDD4yTEJnYKEQiem1cBgv/pb9TU4/33917XVmuuHF77e9d/mrJP+ZKcioSAAcHWun2+Qg5GEvAcIIRQkFIQQCjJ8EOJHioiIuOVtTheXAhDQt7fivq33awkJBSF+pJu//MQSDad5P7M8RXHfHsjwQQihIKEghFCQUBBCKEgoCCEUJBSEEAoSCkIIBQkFIYSChIIQQkFCQQihIKEghFCQUBBCKEgoCCEUJBSEEAoSCkIIBQkFIYSChEIzzp07x4QJExg0aBBhYWE8+uijapckbMRgMBAWFsbAgQNJTk52iAsOLVmyBD8/P5ycbPN1KBIKzXBycuLZZ5/lxIkTfP7552RlZbFz5061yxJWZjabSU5OZtu2bRQVFVFeXs6WLVvULqtNM2bMIDc312btSyg0o3fv3kRHRwP1lxYfNmwYxcXFKlclrC0nJwdfX19CQ+uvlJuUlMSbb76pclVtGzNmDD4+PjZrX76OrQ2XLl3irbfe4oMPPlC7FAGY6+r45zsf8+3FMsXy5199s9n7Y4YPIWpwcLNtlZSU4O9//Sq5ffv25dy5c9Yt+N9Onipmz/6mV45urm5P964k/moSTk46m9TSFukptKKmpobp06ezZMkS7rjjDrXLEYBWo2HsiHC++e4Spd9ebFx+8/3Sby+i0UD4oJavQF5X19w1sWwjJMAf965dGmtr0Fzdo6IGqxYIIKHQIpPJxOzZs4mIiGDZsmVqlyNu0MdHz8TRUa2u46TTMXPqeJx0Lf9x+fv7K3oGxcXF+Pn5Wa3OG2k0GqbHx9LFzbXV9WKGhRIS4N/qOrYmodCClJQUPDw8eO6559QuRTQjNiaCvr4tX85qcuwIeum9W20jOjqakpISjh8/DsDGjRu59957rVrnjbw8ujFt0pgWH9d7exE/bqTN9m8pCYVmfPLJJ7zyyivk5uYybNgwIiIi+Mtf/gK0b5dTtEyn1XL/1DicnZtOiwX282VU9OC229DpyMjIYPr06QQGBuLu7k5iYqItym0UPiiQiNCBTZZrNRrunxqHi4tzm20sWLAAPz8/TCYTfn5+pKamWrVGTZ38L78lb3+YjclkYtqkMWg0GrXL6fQO5R9nx56sxp/dXF1YOn863T3dVayqdVeuVpO+cTvllZcbl00YFcldd0arWNV10lO4BWXllRzKP05dXZ0Egp0YET5IMQb/5V2j7ToQALq6uTJjSmzjz34+P2X8qEgVK1Jy+FA4duwY9913H3q9Hjc3N4KCgnjsscdssi/Dp/nU1dUR97NhNmlf3DqNRsP0X8TStYsrQ0IGNNs1t0dB/f0aP2W4f2ocOp39/Ck69PAhLy+PsWPH4u/vz/Lly+nXrx9nzpwhOzubjRs3trptw6W6hOgsLL0snUMfvLRs2TK6devGoUOH8PLyalyelJSkYlVCODaH7SlcuXIFDw8PFi9ezPPPP2/TfZWVV7Lm5deJGhzMvZPH2nRfQqjNYXsK33//PWaz+bYPNrmd4cPhIyc5fOTkbe1PCLVZOnywn9mNW+Tt7Y1Wq+X8+fNqlyJEh+KwwweAuLg4jh8/zpdffomnp6dN9vHWB1kcPnKC36Uk4O3lYZN9CGFPHLanALB27VoqKyuJiYlh06ZN7Nu3j82bN5OcnGyV9svKK8k5epLoISESCKLTcNg5BYCoqCgOHjzIypUrefjhh7l69Sr+/v4kJCRYpf2LZeV4dOsqxyWITsWhhw/twWw2o9U6dIdKiFsioSCEUJC3QCGEgoSCEEJBQkEIoSChIIRQkFAQQihIKAghFCQUhBAKEgpCCAUJBSGEgoSCEEJBQkEIoSChIIRQkFAQQihIKAghFCQUhBAKEgpCCAUJBSGEgoSCEEJBQkEIoSChIIRQkFAQQihIKAghFCQUhBAKEgpCCAUJBSGEgoSCEEJBQkEIofD//D4DgOBHRvoAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "circuit2 = QuantumCircuit(2,2)\n", "circuit2.ry(2*phi,0)\n", "circuit2.cx(0,1)\n", "circuit2.measure([0,1],[0,1])\n", "circuit2.draw('mpl')" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'11': 2579, '00': 7421}\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "runcircuit2 = circuit2.bind_parameters({phi: phi_value })\n", "\n", "job = execute(runcircuit2, backend, shots=10000)\n", "result = job.result()\n", "counts = result.get_counts(runcircuit2)\n", "print(counts)\n", "plot_histogram(counts)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Führe Distillation aus\n", "\n", "Eingabe sind hier zwei nicht gleichmäßig superpositionierte Zustände." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n", "qc = QuantumCircuit()\n", "qr = QuantumRegister(3,'a')\n", "qc.add_register( qr )\n", "\n", "crResult = ClassicalRegister(2,'result')\n", "qc.add_register( crResult )\n", "crCond = ClassicalRegister(1,'cond')\n", "qc.add_register( crCond )\n", "\n", "qc.ry(2*phi,0)\n", "qc.ry(2*phi,1)\n", "qc.cx(1,2)\n", "qc.barrier()\n", "qc.cx(0,1)\n", "\n", "qc.barrier()\n", "qc.measure(qr[1],crCond[0])\n", "\n", "# Transform to |ERP> state: |00> + |11>\n", "# qc.barrier()\n", "# qc.x(qr[0])\n", "\n", "qc.barrier()\n", "qc.measure(qr[0],crResult[0])\n", "qc.measure(qr[2],crResult[1])\n", "\n", "qc.draw('mpl')" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "qc = qc.bind_parameters({phi: phi_value })" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'0 00': 5546, '1 10': 1893, '1 01': 1927, '0 11': 634}\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "job = execute(qc, backend, shots=10000)\n", "result = job.result()\n", "counts = result.get_counts(qc)\n", "print(counts)\n", "plot_histogram(counts)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Interpretation des Diagramms\n", "\n", "Wir für $a_1$ der Wert 1 gemessen, dann sind $|a_0a_3\\rangle$ in einem Bell-Zustand $\\frac{1}{\\sqrt{2}}(|01\\rangle \\pm |10\\rangle$, wurde der Wert 0 gemessen, dann hat man eine Zustand $|a_0a_3\\rangle$ erhalten, der noch \"weniger gleichmäßig superpositioniert\" ist." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Vergleich der Koeffizienten\n", "\n", "Analystische Bestimmung der Koeffizienten" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Measurement values\n", " |0>|00> => 0.562500\n", " |0>|11> => 0.062500\n", " |1>|01> => 0.187500\n", " |1>|10> => 0.187500\n" ] } ], "source": [ "alpha = np.cos(phi_value)\n", "beta = np.sin(phi_value)\n", "\n", "print(\"Measurement values\")\n", "print(\" |0>|00> => {:>5f}\".format( (alpha**2)**2 ) )\n", "print(\" |0>|11> => {:>5f}\".format( (beta**2)**2 ) )\n", "print(\" |1>|01> => {:>5f}\".format( (alpha*beta)**2 ) )\n", "print(\" |1>|10> => {:>5f}\".format( (alpha*beta)**2 ) )" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "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 }