{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9b198266-63ba-4d62-891b-6528d9ea171a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import QuantumCircuit, QuantumRegister\n",
    "from qiskit_ibm_runtime import QiskitRuntimeService\n",
    "service = QiskitRuntimeService.save_account(channel=\"ibm_quantum\", token=\"HIER IHR TOKEN EINSETZEN\", set_as_default=True, overwrite=True)\n",
    "from qiskit.providers.basic_provider import BasicSimulator\n",
    "backend = BasicSimulator()\n",
    "\n",
    "import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "173d3c73-08e5-463d-99cc-d76f73e03caf",
   "metadata": {},
   "outputs": [],
   "source": [
    "def Uf(qubits,secret):\n",
    "    for q in range(n):\n",
    "        if a[q]:\n",
    "            qubits.cx(q, n)\n",
    "    return qubits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fa201599-fe0b-4990-b254-b31324e74522",
   "metadata": {},
   "outputs": [],
   "source": [
    "n=5\n",
    "a=[random.randint(0,1) for _ in range(n)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f5f570fd-134c-4082-b73e-ade526788d45",
   "metadata": {},
   "outputs": [],
   "source": [
    "circuit = QuantumCircuit(n+1,n)\n",
    "circuit.x(n)\n",
    "circuit.barrier()\n",
    "circuit.h(n)\n",
    "for i in range(n):\n",
    "    circuit.h(i)\n",
    "circuit.barrier()\n",
    "Uf(circuit,a)\n",
    "circuit.barrier()\n",
    "for i in range(n):\n",
    "    circuit.h(i)\n",
    "for i in range(n):\n",
    "    circuit.measure(n-1-i, i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1ab96d5f-d7dd-42d5-9ffa-0105f09578a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'10010': 1024}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "erg = backend.run(circuit, shots=1024).result()\n",
    "erg.get_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7e5b6745-6e3e-446f-a3c1-7e756f954839",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 0, 0, 1, 0]\n"
     ]
    }
   ],
   "source": [
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4ebdaba4-cfdb-49de-ba0f-14b193c0d2d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1207.22x618.722 with 1 Axes>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.draw('mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c4f0b439-3110-421c-b62d-75e425c0ad36",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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