{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example 1: Entanglement\n",
    "For this first example, we will create a Bell State -- an entangled state which as an equal superposition of |00> and |11>."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, import the Qiskit stuff. Then create registers and a circuit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit\n",
    "from qiskit import Aer, execute\n",
    "from qiskit.tools.visualization import plot_histogram\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Bell State is created using a Hadamard gate and a CNOT (controlled-X).  We insert these gates into the circuit, and then draw the circuit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'qc' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-1-d515b797a2e6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mqc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'mpl'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'qc' is not defined"
     ]
    }
   ],
   "source": [
    "\n",
    "qc.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We add some measurements, so that we can see how the circuit behaves."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'qc' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-2-b50ac88b3510>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mqc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmeasure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mq\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# measures all qubits in the register\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mqc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'mpl'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'qc' is not defined"
     ]
    }
   ],
   "source": [
    "qc.measure(q[2],c[2])  # measures all qubits in the register\n",
    "\n",
    "qc.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The circuit is done, and we are ready to simulate it.  We use the **qasm_simulator** from the Aer provider.  We display the results in two ways: (1) as a list of counts, and (2) as a histogram."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'100': 117, '000': 395}\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "backend = Aer.get_backend('qasm_simulator')\n",
    "job = execute(qc, backend, shots=512)  # shots default = 1024\n",
    "result = job.result()\n",
    "print(result.get_counts())\n",
    "plot_histogram(result.get_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}