Notebook_9.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b4386340-74f7-4569-9eb9-eafa1a0371d6",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Notebook 9 \n",
    "# Sunint Bindra"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a714bdf2-f616-451c-995e-a0177a4d498d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Libraries imported successfully!\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "# Importing standard Qiskit libraries\n",
    "from qiskit import QuantumCircuit, execute, transpile, Aer, IBMQ\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()\n",
    "print('Libraries imported successfully!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8c7dbab5-aff4-4b5c-94f9-f7b4d737a00c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 146.652x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Quantum circuit with 2 qubits and 2 classical bits. \n",
    "# Adding an H gate to qubit 0, and an X gate to qubit 1\n",
    "qc = QuantumCircuit(2,2)\n",
    "qc.h(0)\n",
    "qc.x(1)\n",
    "qc.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a9155783-2c2f-4395-a5fa-3d895e4237b2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 267.052x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Adding measurements to the circuit \n",
    "qc.measure([0,1],[0,1])\n",
    "qc.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2492fe5e-29bc-43bc-862e-063107791ce1",
   "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": [
    "# Simulating circuit using the QASM simulator and plotting histogram \n",
    "backend = Aer.get_backend('qasm_simulator') \n",
    "job = execute(qc,backend, shots = 1024) \n",
    "result = job.result()\n",
    "\n",
    "counts = result.get_counts()\n",
    "plot_histogram(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "97a2011a-b0fb-4fdc-818c-48b73eb08d6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 327.252x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Quantum circuit with 2 qubits and 2 classical bits \n",
    "# Adding an H gate to qubit 0 and an CX gate with qubit 0 as control and qubit 1 as target \n",
    "qc = QuantumCircuit(2,2)\n",
    "qc.h(0)\n",
    "qc.cx(0,1)\n",
    "qc.measure([0,1],[0,1]) # Adding measurements to circuit \n",
    "qc.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "229598d7-216c-47ac-9089-f1dcb039404f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Simulating circuit using the QASM simulator and plotting histogram \n",
    "backend = Aer.get_backend('qasm_simulator') \n",
    "job = execute(qc,backend, shots = 1024) \n",
    "result = job.result()\n",
    "\n",
    "counts = result.get_counts()\n",
    "plot_histogram(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b41b1064-8993-4913-9c51-27383216960a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ibmq_manila\n"
     ]
    }
   ],
   "source": [
    "# Block 6: Finding least busy quantum computer\n",
    "from qiskit.providers.ibmq import least_busy\n",
    "backend = least_busy(provider.backends(filters=lambda x: x.configuration().n_qubits >= 2 and \n",
    "                                        not x.configuration().simulator and x.status().operational==True))\n",
    "print(backend)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c316b922-7661-48a0-8a94-d2e574a7c3e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Block 7: Running  circuit using least busy QC and plotting histogram\n",
    "job = execute(qc,backend, shots = 1024) \n",
    "result = job.result()\n",
    "\n",
    "counts = result.get_counts()\n",
    "plot_histogram(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "25f44762-f27b-4260-b304-320e134ab650",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 447.797x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Quantum circuit with 3 qubits and 3 classical bits\n",
    "qc = QuantumCircuit(3,3)\n",
    "qc.h(0) # Adding an H gate to qubit 0 \n",
    "qc.cx(0,1 ) # Adding a CX gate with qubit 0 as control and 1 as target \n",
    "qc.cx(1,2) # Adding another CX with qubit 1 as control and 2 as target\n",
    "qc.measure([0,1,2],[0,1,2]) # Adding measurements to all 3 qubits and draw the circuit\n",
    "qc.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5d882dfa-c731-4b22-bef7-ffaea09e2dba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Simulating circuit using QASM simulator and plotting histogram\n",
    "backend = Aer.get_backend('qasm_simulator') \n",
    "job = execute(qc,backend, shots = 1024) \n",
    "\n",
    "counts = result.get_counts()\n",
    "plot_histogram(counts)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Qiskit v0.34.2 (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"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}