{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "8f78906c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ibmqfactory.load_account:WARNING:2021-06-23 12:32:29,545: Credentials are already in use. The existing account in the session will be replaced.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "# Importing standard Qiskit libraries\n",
    "from qiskit import QuantumCircuit, transpile, Aer, IBMQ, assemble, execute\n",
    "from qiskit.tools.jupyter import *\n",
    "from qiskit.visualization import *\n",
    "from ibm_quantum_widgets import *\n",
    "\n",
    "# Loading your IBM Quantum account(s)\n",
    "provider = IBMQ.load_account()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8dc70004",
   "metadata": {},
   "source": [
    "Let's implement some simple circuits\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d1535089",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 193.726x144.48 with 1 Axes>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Hadamard gate\n",
    "qc = QuantumCircuit(1,1)\n",
    "qc.h(0)\n",
    "qc.measure(0,0)\n",
    "qc.draw()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e028fa42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 253.926x144.48 with 1 Axes>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Measurement in x basis\n",
    "def x_measurement(qc, qubit, cbit):\n",
    "    \"\"\"Measure 'qubit' in the X-basis, and store the result in 'cbit'\"\"\"\n",
    "    qc.h(qubit)\n",
    "    qc.measure(qubit, cbit)\n",
    "    return qc\n",
    "initial_state = [1,0]\n",
    "\n",
    "# Initialize our qubit and measure it\n",
    "qc = QuantumCircuit(1,1)\n",
    "qc.initialize(initial_state, 0)\n",
    "x_measurement(qc, 0, 0)  # measure qubit 0 to classical bit 0\n",
    "qc.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "340a4030",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#simulating the circuit to obtain results. This is a qasm_simulator.\n",
    "qasmsim = Aer.get_backend('qasm_simulator')  # Tell Qiskit how to simulate our circuit  # Assemble circuit into a Qobj that can be run\n",
    "job = execute(qc, qasmsim, shots=1000)\n",
    "result = job.result()\n",
    "\n",
    "# Return counts\n",
    "counts = result.get_counts()  # Do the simulation, returning the state vector\n",
    "plot_histogram(counts)  # Display the output on measurement of state vector"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3e5ed9c",
   "metadata": {},
   "source": [
    "To load account in IBM an do circuit implementation on an actuall quantum computer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c1d7cc57",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ibmqfactory.load_account:WARNING:2021-06-23 06:06:41,331: Credentials are already in use. The existing account in the session will be replaced.\n"
     ]
    }
   ],
   "source": [
    "IBMQ.load_account()\n",
    "provider = IBMQ.get_provider('ibm-q')\n",
    "qcomp = provider.get_backend('ibmq_armonk')\n",
    "job = execute(qc, backend = qcomp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c75b8723",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Job Status: job has successfully run\n"
     ]
    }
   ],
   "source": [
    "from qiskit.tools.monitor import job_monitor\n",
    "job_monitor(job)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "49f00c2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = job.result()\n",
    "plot_histogram(result.get_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ac0366d",
   "metadata": {},
   "source": [
    "Now we can compare this with our simulator results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1ce7e9d",
   "metadata": {},
   "source": [
    "# We should now implement some complicated circuits."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "5af3a6f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 387.452x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Implementing CNOT(cx) gate using ch and cz gate\n",
    "from qiskit.circuit import gate\n",
    "c=0\n",
    "t=1\n",
    "qc = QuantumCircuit(2,1)\n",
    "intial_control = [1,0]\n",
    "intial_target = [0,1]\n",
    "qc.initialize(intial_control,c)\n",
    "qc.initialize(intial_target,t)\n",
    "qc.ch(c,t)\n",
    "qc.cz(c,t)\n",
    "qc.ch(c,t)\n",
    "qc.measure(1,0)\n",
    "qc.draw()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "f54606cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'1': 1}\n"
     ]
    }
   ],
   "source": [
    "simul = Aer.get_backend('qasm_simulator')\n",
    "result = execute(qc, backend = simul, shots = 1).result()\n",
    "print(result.get_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79e47656",
   "metadata": {},
   "source": [
    "Implementing teleportation circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "6a0fba4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 869.197x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 869.197x264.88 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#teleportation circuit(teleport state |1> from q0 to q2 )\n",
    "circuit = QuantumCircuit(3, 3)\n",
    "circuit.x(0)\n",
    "circuit.barrier()\n",
    "circuit.h(1)\n",
    "circuit.cx(1, 2)\n",
    "circuit.cx(0, 1)\n",
    "circuit.h(0)\n",
    "circuit.barrier()\n",
    "circuit.measure([0, 1], [0, 1])\n",
    "circuit.barrier()\n",
    "circuit.cx(1, 2)\n",
    "circuit.cz(0, 2)\n",
    "circuit.measure(2, 2)\n",
    "%matplotlib inline\n",
    "circuit.draw(output = 'mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "d012da9b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'110': 265, '101': 215, '100': 259, '111': 285}\n"
     ]
    }
   ],
   "source": [
    "simulator = Aer.get_backend('qasm_simulator')\n",
    "result = execute(circuit, backend = simulator).result()\n",
    "counts = result.get_counts()\n",
    "print(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "1d1721cf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter your secret number in binary01001001011\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1423.98x806.68 with 1 Axes>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1423.98x806.68 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Bernstein-Vazrani Algorithm(find my secret number in 1 shot)\n",
    "secretnumber = input(\"Enter your secret number in binary\")\n",
    "circuit = QuantumCircuit(len(secretnumber)+1, len(secretnumber))\n",
    "circuit.h(range(len(secretnumber)))\n",
    "circuit.x(len(secretnumber))\n",
    "circuit.h(len(secretnumber))\n",
    "\n",
    "circuit.barrier()\n",
    "\n",
    "for ii , yesno in enumerate (reversed(secretnumber)):\n",
    "    if yesno == '1':\n",
    "        circuit.cx(ii , len(secretnumber))\n",
    "\n",
    "circuit.h(range(len(secretnumber)))\n",
    "\n",
    "circuit.barrier()\n",
    "\n",
    "circuit.measure(range(len(secretnumber)), range(len(secretnumber)))\n",
    "\n",
    "circuit.draw(output = 'mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "399fe916",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'01001001011': 1}\n"
     ]
    }
   ],
   "source": [
    "simulator = Aer.get_backend('qasm_simulator')\n",
    "result = execute(circuit, backend = simulator, shots = 1).result()\n",
    "print(result.get_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7163aa99",
   "metadata": {},
   "source": [
    "# Implement my Quantum Fourier transform(QFT) circuit.\n",
    "## Note : Qiskit already has a QFT library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "d2b2e1ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1049.8x264.88 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1110x264.88 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1049.8x264.88 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1110x264.88 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from qiskit.circuit.library import QFT\n",
    "pi = np.pi    \n",
    "#defining my QFT function\n",
    "def myQFT(qubits):\n",
    "    qftcir = QuantumCircuit(qubits)\n",
    "    for i in range(qubits):\n",
    "        qftcir.h(i)\n",
    "        for j in range(i+1, qubits):\n",
    "            qftcir.cp(pi/(2**(j-i)), j, i)   #cu1 is control unitary roration function, takes in (phase,target, control bit)\n",
    "    return qftcir\n",
    "\n",
    "display(myQFT(4).draw())\n",
    "display(QFT(4).draw())      #We can check that myQFT and QFT does the same  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37eed7ac",
   "metadata": {},
   "source": [
    "## Now Implement Quantum Phase Estimation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "2ade99ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1591.6x686.28 with 1 Axes>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#defining 1st part of circuit\n",
    "from qiskit.circuit.library import QFT\n",
    "pi = np.pi\n",
    "def qpe(nqubits):\n",
    "    t=1\n",
    "    qpe_0 = QuantumCircuit(nqubits+t,nqubits)\n",
    "    for i in range(nqubits):\n",
    "        qpe_0.h(i)\n",
    "    repetitions = 1\n",
    "    for counting_qubit in range(nqubits):\n",
    "        for i in range(repetitions):\n",
    "            qpe_0.cp(pi/4, counting_qubit, nqubits); # This is C-U\n",
    "        repetitions *= 2\n",
    "    qpe_1 = QFT(nqubits, 0, True, True)\n",
    "    l = [*range(nqubits)]\n",
    "    qpe = qpe_0.compose(qpe_1, l)\n",
    "    qpe.measure(l,l)\n",
    "    return qpe\n",
    "    \n",
    "qpe(3).draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8aa2934a",
   "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": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}