{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Shared Randomness mit drei Qubits\n", "\n", "Die beiden folgenden Schaltkreise erzeugen zwei verschränkte Qubits\n", "$$\n", "\\frac{1}{\\sqrt{2}} \\left(|000\\rangle + |111\\rangle \\right)\n", "$$\n", "wobei 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": "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": "markdown", "metadata": {}, "source": [ "### Messung in der Standardbasis\n", "\n", "Beachte: Nur die beiden oberen Qubits werden gemessen." ] }, { "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(3,2)\n", "\n", "qc_cb.h(0)\n", "qc_cb.cx(0,1)\n", "qc_cb.cx(0,2)\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": [ "{'00': 520, '11': 480}\n" ] }, { "data": { "image/png": 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wUlcWJklSb9O/k/1vAG4HtgFPA3PL7TOBJ7uwLkmSep1OhWZmficiFgLjgJ9l5qvlRX8AvtDVxUmS1Jt0dk+TzGykdNVsZdtPu6wiSZJ6qU5PbhARl0TE0oh4KSImltuuiohzur48SZJ6j85ObnAF8Hngu0BULHoG+JuuK0uSpN6ns3uanwAuysybgJ0V7YuA6i6rSpKkXqizoflmYEkb7a8AA/e9HEmSeq/OhuZKYHob7e8Glu17OZIk9V6dvXr268C3IuIwSuc06yPiw8D/Aj7W1cVJktSbdPY+zVsjoj9wLXAYpYkOngEuz8y79kN9kiT1Gntzn+ZsYHZEHAEckpkbu74sSZJ6n06H5i6Z+VxXFiJJUm+3x9CMiN8AszJzc0Q8CWR7fTPz+K4sTpKk3qTInua9QHPF+3ZDU5KkvmyPoZmZX6p4/8X9Wo0kSb1YZ6fRezgiDm+jfUhEPNxlVUmS1At1dnKDU4EBbbQfCpyyz9VIktSLFbp6NiIqZwE6PiKer/jcDzgDWNuVhUmS1NsUveWkkdIFQAk81Mby7cBlXVWUJEm9UdHQnEBp2ryVwJ8Dz1Ys2wFszMyWLq5NkqRepVBoZubT5bedfmi1JEl9RZHJDd4P/GtmvlJ+367M/Ocuq0ySpF6myJ7mPcAoYGP5fXuS0kVBkiT1SUUmNzikrfeSJB1sDEFJkgoqek6zEM9pSpL6sqLnNIvwnKYkqU/r1DlNSZIOZgaiJEkFeZ+mJEkFeZ+mJEkFeZ+mJEkFGYKSJBXU6dCMiOkRcVtENJZft7d63qYkSX1Sp0IzIj4E/Bo4Evi38msksCAi/rrry5Mkqfco+jzNXa4BvpCZ11Y2RsTngK8A/9hVhUmS1Nt09vDsm4AftdF+NzCiyAARcUlENEXEyxGxMCJO6aDvrIh4PCI2RcT2iPhdRHymjX4fiIhlEdFc/vOswlskSVJBnQ3NXwKnttF+KvDonlaOiHOBm4BrgROBx4EHIuKodlbZBtwMzASmUdqb/VJEXFIxZj1wF/BPwAnlP++OiLoiGyRJUlGdnbD9AeCrEVEL/KrcdjLwfuCLBX7elcCczJxd/nxZRLwL+CTwudadM3MhsLCiqalczynALeW2K4BfZuY15c/XRMQ7yu0fLFCTJEmF7O2E7ReXX5W+yZ+C7HUiYgDwVuDrrRY9BLytQB1ExInlvl+saK4v/+xK/w78TZExJUkqqjsnbD+C0oxBG1q1bwBO62jFiFhD6Xxqf+BLmfntisWj2hlzVDtj7Q780aNH88gjjwAwceJEBg8ezOLFiwEYPnw41dXVzJ07F4D+/fszY8YMFi1axJYtWwCora1lw4YNwNEdla8DVGNjI9u2bQOgrq6ONWvWsHbtWgCmTp1Kv379WLZsGQCjRo1iwoQJzJ8/H4CBAwdSV1dHQ0MD27dvB6C+vp6mpibWr18PwLRp02hpaWH58uUAjBkzhrFjx9LQ0ADAoEGDqK2tZf78+TQ3NwMwY8YMnnrqKTZu3AjAscceS3NzMytWrABg3LhxjBw5ksbGRgCGDBnC9OnTmTdvHjt37gRg5syZLF26lE2bNgFQU1PD1q1bWblyJQDjx49n2LBhLFq0CIChQ4dSU1PDo48+SmYSEcyaNYvFixezefNmAKZPn87zzz/PqlWrgH37Pq1evRqAyZMnU1VVxZIlSwAYMWIEU6ZMYd68eQBUVVVRX1+/V78nqOrk3wYdCNatW9cl36eORGbux02o+EERo4G1wKzMnFvRfjXwocyc2sG6E4BBlA4Ffw34VGbeXl62A7gwM2+r6H8+MDszO/xm1NbW5q5/XPbFRTfu8xDqhWZf0dMVaH/xO9s3ddV3NiIWZmZtW8s6e8sJETEU+K/AUcCAymWZ+eUOVn0OaKF0X2elkcD6jn5mZjaV3z4ZESMpHZ69vdy2fm/GlCSpszoVmhFxMvBToJnS4dK1lCY6aAZWAe2GZmbuiIiFwOmUblHZ5XTg3k6UcQivPbYyvzzG9a3GfLwTY0qStEed3dO8ntItHZ8CtgB/AbwI3AF8v8D6NwC3R8QC4DHgE8Bo4NsAEXEbQGaeX/58GdAELC+vPxP4DK+94OgmYG5EfBb4MXAW8A5gRie3TZKkDnU2NI8HPp6ZGREtQFVmroyIq4AfUgrUdmXmXRExHPg8pT3UJcC7M/PpcpfW92v2o3QOczywE/gD8FnKIVse8/GIOI/SPZxfLvc5NzMbOrltkiR1qLOhuaPi/QbgzcBvKU1CMLrIAJl5C+3cmpKZp7b6fCNwY4Ex76HjZ31KkrTPOhuai4CTgKeAR4CvlC/M+WvgN11bmiRJvUtn78H8W+CZ8vvPA89SmlhgKK+f7ECSpD6lU3uamdlY8f5ZSreeSJJ0UOj0fZoAEXE0cEz547LMXNl1JUmS1Dt19j7N4ZRuLTkTePVPzfET4GOZuamL65Mkqdfo7DnN7wGTKD1l5NDyayYwAZjdwXqSJB3wOnt49gzgv2Tm/Iq2xyLifwA/77qyJEnqfTq7p/kspRmAWnsJ8NCsJKlP62xofhm4MSLG7Goov/97Oph3VpKkvmCPh2cj4kmg8vlhE4BVEbG2/HkM8DIwgtI5T0mS+qQi5zSdnk6SJAqEZmZ+qTsKkSSpt9vbyQ3+AphG6bDt0sx8pCuLkiSpN+rs5AZjgH8B3sqf5qAdHRGNwFmZ+Uy7K0uSdIDr7NWzNwMtwKTMHJeZ44DJ5babu7o4SZJ6k84enj0dODUzm3Y1lB9CfTnwiy6tTJKkXqaze5rw2ttPOmqTJKlP6Wxo/gL4ZkSM29UQEUcBN+KepiSpj+tsaF4O/BmwMiKejoingT+U2y7v6uIkSepNOntOcxPw58CpwFvKbb/NTCdrlyT1eYVDMyL6AX8EajLzZ8DP9ltVkiT1QoUPz2ZmC/A0MGD/lSNJUu/V2XOa/xu4LiKO2B/FSJLUm3X2nOZnKD3lZG1ErKHVszUz8/iuKkySpN6ms6F5D6V7MmM/1CJJUq9WKDQj4jDgeuAvgTdQuifzssx8bv+VJklS71L0nOaXgI8APwXuAE4D/mE/1SRJUq9U9PDs+4GPZ+adABHxT8BjEdGvfFWtJEl9XtE9zXHA/9v1ITMXADuB0fujKEmSeqOiodkP2NGqbSd7+RBrSZIOREVDL4B/jIjmirZDgdkR8dKuhsw8syuLkySpNykamj9oo+0fu7IQSZJ6u0KhmZkf3d+FSJLU2+3NQ6glSTooGZqSJBVkaEqSVJChKUlSQYamJEkFGZqSJBVkaEqSVJChKUlSQYamJEkFGZqSJBVkaEqSVJChKUlSQYamJEkFGZqSJBVkaEqSVJChKUlSQYamJEkFGZqSJBVkaEqSVJChKUlSQYamJEkFdXtoRsQlEdEUES9HxMKIOKWDvkdGxA8j4ncR0RIRc9ro85GIyDZeh+7XDZEkHXS6NTQj4lzgJuBa4ETgceCBiDiqnVWqgOeA64CGDoZ+CTiy8pWZL3dV3ZIkQffvaV4JzMnM2Zn528y8DFgHfLKtzpm5KjMvz8w5wPMdjJuZub7y1fWlS5IOdt0WmhExAHgr8FCrRQ8Bb9vH4QdGxNMRsSYifhIRJ+7jeJIkvU7/bvxZRwD9gA2t2jcAp+3DuMuBjwGLgcHAp4DHIqImM1e07hwRFwMXA4wePZpHHnkEgIkTJzJ48GAWL14MwPDhw6murmbu3LkA9O/fnxkzZrBo0SK2bNkCQG1tLRs2bACO3ofy1Vs1Njaybds2AOrq6lizZg1r164FYOrUqfTr149ly5YBMGrUKCZMmMD8+fMBGDhwIHV1dTQ0NLB9+3YA6uvraWpqYv360oGQadOm0dLSwvLlywEYM2YMY8eOpaGhdCZi0KBB1NbWMn/+fJqbmwGYMWMGTz31FBs3bgTg2GOPpbm5mRUrSn/Vx40bx8iRI2lsbARgyJAhTJ8+nXnz5rFz504AZs6cydKlS9m0aRMANTU1bN26lZUrVwIwfvx4hg0bxqJFiwAYOnQoNTU1PProo2QmEcGsWbNYvHgxmzdvBmD69Ok8//zzrFq1Cti379Pq1asBmDx5MlVVVSxZsgSAESNGMGXKFObNmwdAVVUV9fX1e/V7Kp35UV+zbt26Lvk+dSQycz9uQsUPihgNrAVmZebcivargQ9l5tQ9rP8T4LnM/Mge+vUDngB+mZmXd9S3trY2d/3jsi8uunGfh1AvNPuKnq5A+4vf2b6pq76zEbEwM2vbWtad5zSfA1qAka3aRwJddg4yM1uARmByV40pSRJ0Y2hm5g5gIXB6q0WnU7qKtktERADHU7rASJKkLtOd5zQBbgBuj4gFwGPAJ4DRwLcBIuI2gMw8f9cKEXFC+e0Q4NXy5x2Zuay8/O+AXwEryn0upxSabV6RK0nS3urW0MzMuyJiOPB5SvdTLgHenZlPl7u0db/mf7T6/F7gaWB8+fPhwHeBUcAfy/1nZuaCLi1eknTQ6+49TTLzFuCWdpad2kZb7GG8TwOf7pLiJEnqgHPPSpJUkKEpSVJBhqYkSQUZmpIkFWRoSpJUkKEpSVJBhqYkSQUZmpIkFWRoSpJUkKEpSVJBhqYkSQUZmpIkFWRoSpJUkKEpSVJBhqYkSQUZmpIkFWRoSpJUkKEpSVJBhqYkSQUZmpIkFWRoSpJUkKEpSVJBhqYkSQUZmpIkFWRoSpJUkKEpSVJBhqYkSQUZmpIkFWRoSpJUkKEpSVJBhqYkSQUZmpIkFWRoSpJUkKEpSVJBhqYkSQUZmpIkFWRoSpJUkKEpSVJBhqYkSQUZmpIkFWRoSpJUkKEpSVJBhqYkSQUZmpIkFWRoSpJUkKEpSVJBhqYkSQUZmpIkFWRoSpJUkKEpSVJBhqYkSQUZmpIkFWRoSpJUkKEpSVJBhqYkSQV1e2hGxCUR0RQRL0fEwog4ZQ/9Z5X7vRwRKyPiE/s6piRJe6NbQzMizgVuAq4FTgQeBx6IiKPa6T8B+LdyvxOBrwLfjIgP7O2YkiTtre7e07wSmJOZszPzt5l5GbAO+GQ7/T8BPJOZl5X7zwZ+AHxmH8aUJGmvRGZ2zw+KGAC8BHwwM++uaP+/wLGZOauNdeYCT2bmpRVtfwX8EDgMiL0Y82Lg4vLHqcDyLti8g8kRwHM9XYSkwvzOdt6bM/NNbS3o341FHAH0Aza0at8AnNbOOqOAn7fRv395vOjsmJn5XeC7havWa0REY2bW9nQdkorxO9u1vHpWkqSCunNP8zmgBRjZqn0ksL6ddda3039nebzYizElSdor3banmZk7gIXA6a0WnU7pite2zG+nf2NmvrKXY2rfeGhbOrD4ne1C3XYhEOy+PeR24BLgMUpXx34cqM7MpyPiNoDMPL/cfwKwBJgNfAd4O3ALpQt/7i0yZrdtnCSpz+vOw7Nk5l0RMRz4PHAkpUB8d0W4HdWqf1NEvBv4BqVbSJ4BLt8VmAXHlCSpS3TrnqYkSQcyr56VJKkgQ1OSpIIMTUmSCurWC4F0YIqIscAkSvfFvgosz0zvg5V00PFCIHUoIj4JfAyoAV4Efg+sAX4F/Dgzl0fEIZn5ag+WKUndwsOzalf5Vp5rgfso3c5TT+kpMy3A+cDNETEtM1+NiOi5SiUBRMQbImJKRFT1dC19lXuaaldEXAb8dWbWtbFsBqXnm44B/jwzfYqC1MMi4grgGuBHwD8DvwaezcyWij5DKE0U8/PMfKUn6jyQuaepjuwABkfEsQARUVV+xBuZOQ/4EPAy8M6eK1FShXOBBZSuQfgxpalIr4+IGRHxxnKf/w78nYG5dwxNdeQeShf+XBERgzOzOTN3RMQhAJn5n8ALwNgerFESEBFvAl4BZmfmKcCbge8D/w2YCzwcEVcBVwANPVXngc7Ds2pTxTnK9wE3AcMoHfK5BfgPSkE5E/gH4LjMXNUDZUoqi4gjgfOAZZn5762WnQhcWF4+FBiXmWu7v8oDn6GpDkXE4ZTmBH4bcBalcyFQevRaALdn5hd7pDhJrxERA4HMzJcrL87L8j/0EXENpbm5T+ypGg903qep14mIEcCHgf9J6bml2ykdhp0HfB14A6VzJg9m5lM9VKakVjJz+66wzFZ7RBFxGPAB4NaeqK2vcE9TrxMRc4Bq4F+B5ykdmj0OmAJsBD6fmZ4TkXqJ8hWxW1sHZas+h1K6UOiO8rOItRcMTb1G+f9St1I6hDO3ou0ooI7SeZGJwDmZuajHCpW0W0R8h9JVswuApzNzSxt9Ds/MF7q7tr7Gq2fV2jSgidLtJkDpME9mPp2ZPwLeS+lQ7V/1THmSKkXEB4GLgL+nNBHJ9RFxVkQcXT7Huetc5w923T6mveeepl6j/OX6CXAYpVl//tB6irzypAcfz8wTur9CSZUiYjalWbr+D/B+4ALgaGA58G/AL4CpwE2ZOaCn6uwr3NPUa2TmduBvgYHAbcD5ETEuIgbB7osJZgFLeq5KSQAR0Z/SkaEXMnNlZn49M48DTgIepRSgPwK+Cdzec5X2He5pqk3lwzhfAM6kNFH7fOBZ4DRgHXBhZj7ZcxVKAoiIocDIzPxdecauVyovCIqIc4E7gOmZ+UQPldlnGJrqUPn2k/cAf0lpyrwlwN2Z+buerEtS+8qzdkVmtkTERZQOzR7W03X1BYamCvMRYNKBJyKuBPpl5vU9XUtfYGhKUh8WEW8AWvwf3q5haEqSVJBXz0qSVJChKUlSQYamJEkFGZqSJBVkaEqSVJChKUlSQf8fPfEY9CMqV9YAAAAASUVORK5CYII=\n", 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" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "job = execute(qc_cb, backend, shots=1000)\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", "Beachte: Nur die beiden \"oberen\" Qubits werden gemessen " ] }, { "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(3,2)\n", "\n", "qc_hb.h(0)\n", "qc_hb.cx(0,1)\n", "qc_hb.cx(0,2)\n", "qc_hb.barrier()\n", "qc_hb.h(0)\n", "qc_hb.h(1)\n", "\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": [ "{'10': 226, '11': 276, '00': 272, '01': 226}\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "job = execute(qc_hb, backend, shots=1000)\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 }