qiskit_basics.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4",
      "authorship_tag": "ABX9TyO+RtkMyKp5AJs3l9Y4mUWF",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/yellomello/Qiskit_Basics/blob/main/qiskit_basics.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install qiskit-aer"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "n8KUXgOSscxU",
        "outputId": "c97b98dc-4f6c-4ba4-f60a-1b424799d5d5"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting qiskit-aer\n",
            "  Downloading qiskit_aer-0.12.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.8 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m12.8/12.8 MB\u001b[0m \u001b[31m44.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting qiskit-terra>=0.21.0 (from qiskit-aer)\n",
            "  Downloading qiskit_terra-0.25.1-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (6.1 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.1/6.1 MB\u001b[0m \u001b[31m84.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: numpy>=1.16.3 in /usr/local/lib/python3.10/dist-packages (from qiskit-aer) (1.23.5)\n",
            "Requirement already satisfied: scipy>=1.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-aer) (1.11.2)\n",
            "Collecting rustworkx>=0.13.0 (from qiskit-terra>=0.21.0->qiskit-aer)\n",
            "  Downloading rustworkx-0.13.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m85.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting ply>=3.10 (from qiskit-terra>=0.21.0->qiskit-aer)\n",
            "  Downloading ply-3.11-py2.py3-none-any.whl (49 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.6/49.6 kB\u001b[0m \u001b[31m7.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: psutil>=5 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra>=0.21.0->qiskit-aer) (5.9.5)\n",
            "Requirement already satisfied: sympy>=1.3 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra>=0.21.0->qiskit-aer) (1.12)\n",
            "Collecting dill>=0.3 (from qiskit-terra>=0.21.0->qiskit-aer)\n",
            "  Downloading dill-0.3.7-py3-none-any.whl (115 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m115.3/115.3 kB\u001b[0m \u001b[31m16.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: python-dateutil>=2.8.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra>=0.21.0->qiskit-aer) (2.8.2)\n",
            "Collecting stevedore>=3.0.0 (from qiskit-terra>=0.21.0->qiskit-aer)\n",
            "  Downloading stevedore-5.1.0-py3-none-any.whl (49 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.6/49.6 kB\u001b[0m \u001b[31m4.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting symengine<0.10,>=0.9 (from qiskit-terra>=0.21.0->qiskit-aer)\n",
            "  Downloading symengine-0.9.2-cp310-cp310-manylinux2010_x86_64.whl (37.5 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m37.5/37.5 MB\u001b[0m \u001b[31m16.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from qiskit-terra>=0.21.0->qiskit-aer) (4.5.0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.0->qiskit-terra>=0.21.0->qiskit-aer) (1.16.0)\n",
            "Collecting pbr!=2.1.0,>=2.0.0 (from stevedore>=3.0.0->qiskit-terra>=0.21.0->qiskit-aer)\n",
            "  Downloading pbr-5.11.1-py2.py3-none-any.whl (112 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m112.7/112.7 kB\u001b[0m \u001b[31m13.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy>=1.3->qiskit-terra>=0.21.0->qiskit-aer) (1.3.0)\n",
            "Installing collected packages: ply, symengine, rustworkx, pbr, dill, stevedore, qiskit-terra, qiskit-aer\n",
            "Successfully installed dill-0.3.7 pbr-5.11.1 ply-3.11 qiskit-aer-0.12.2 qiskit-terra-0.25.1 rustworkx-0.13.1 stevedore-5.1.0 symengine-0.9.2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cwyKmJYZqnAq",
        "outputId": "736d79ae-0424-4fbb-b2c3-9536f88bffd2"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting qiskit\n",
            "  Downloading qiskit-0.44.1-py3-none-any.whl (8.2 kB)\n",
            "Requirement already satisfied: qiskit-terra==0.25.1 in /usr/local/lib/python3.10/dist-packages (from qiskit) (0.25.1)\n",
            "Requirement already satisfied: rustworkx>=0.13.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.25.1->qiskit) (0.13.1)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.25.1->qiskit) (1.23.5)\n",
            "Requirement already satisfied: ply>=3.10 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.25.1->qiskit) (3.11)\n",
            "Requirement already satisfied: psutil>=5 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.25.1->qiskit) (5.9.5)\n",
            "Requirement already satisfied: scipy>=1.5 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.25.1->qiskit) (1.11.2)\n",
            "Requirement already satisfied: sympy>=1.3 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.25.1->qiskit) (1.12)\n",
            "Requirement already satisfied: dill>=0.3 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.25.1->qiskit) (0.3.7)\n",
            "Requirement already satisfied: python-dateutil>=2.8.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.25.1->qiskit) (2.8.2)\n",
            "Requirement already satisfied: stevedore>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.25.1->qiskit) (5.1.0)\n",
            "Requirement already satisfied: symengine<0.10,>=0.9 in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.25.1->qiskit) (0.9.2)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from qiskit-terra==0.25.1->qiskit) (4.5.0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.0->qiskit-terra==0.25.1->qiskit) (1.16.0)\n",
            "Requirement already satisfied: pbr!=2.1.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from stevedore>=3.0.0->qiskit-terra==0.25.1->qiskit) (5.11.1)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy>=1.3->qiskit-terra==0.25.1->qiskit) (1.3.0)\n",
            "Installing collected packages: qiskit\n",
            "Successfully installed qiskit-0.44.1\n"
          ]
        }
      ],
      "source": [
        "!pip install qiskit"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import qiskit\n",
        "print(qiskit.__version__)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1Ze1pxh-qq7W",
        "outputId": "f249982f-a58d-4fb4-825d-c4d198588e38"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.25.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from qiskit import *\n",
        "from qiskit.tools.visualization import plot_histogram\n",
        "%matplotlib inline"
      ],
      "metadata": {
        "id": "jUpz_LKiqzfn"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "b34YzY1Aq7Jd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "qr = QuantumRegister(1) #stores 1 qubit\n",
        "cr = ClassicalRegister(1) #stores 1 classical bit\n",
        "circuit = QuantumCircuit(qr, cr)\n",
        "circuit.h(qr)\n",
        "circuit.measure(qr,cr) #this creates a python object of a circuit"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aEdB97PJq4jT",
        "outputId": "aed22743-6fea-4f6e-d76c-ef49cb65bd1d"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<qiskit.circuit.instructionset.InstructionSet at 0x7c66f49e5090>"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "simulator = Aer.get_backend('qasm_simulator')\n",
        "result = execute(circuit, backend= simulator , shots=102400000).result()\n",
        "plot_histogram(result.get_counts())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 465
        },
        "id": "KQKAnHC0rTO2",
        "outputId": "5ee90c93-1dad-49a3-8df7-1f606163fc0a"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a= result.get_counts()"
      ],
      "metadata": {
        "id": "jqVl5XQYsWsC"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "54iFGEsZtbrt",
        "outputId": "090ea179-87b4-4465-8598-edc4fe3af3d5"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'1': 51190988, '0': 51209012}"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "I3hgEU2eukPS"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}