202403_LiangCPSC3999_Ex04_3QubitGHZ_NoisySimulator.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/hongqin/quantum_sandbox/blob/main/202403_LiangCPSC3999_Ex04_3QubitGHZ_NoisySimulator.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Exercise 04: Show the 3-qubit GHZ state on ideal and noisy aer Simulator\n",
        "\n",
        "https://qiskit.github.io/qiskit-aer/tutorials/2_device_noise_simulation.html"
      ],
      "metadata": {
        "id": "N96NUv_klfgu"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## PART 1: Import the library"
      ],
      "metadata": {
        "id": "lOUoF2_TYgXJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install qiskit ipywidgets --quiet"
      ],
      "metadata": {
        "id": "SrUCOrFClTZH",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d7aa0817-f7ec-49ec-87b8-1bf844629ffa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.6/5.6 MB\u001b[0m \u001b[31m16.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.1/2.1 MB\u001b[0m \u001b[31m54.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m9.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.7/49.7 kB\u001b[0m \u001b[31m3.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m39.4/39.4 MB\u001b[0m \u001b[31m10.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.6/1.6 MB\u001b[0m \u001b[31m23.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m107.5/107.5 kB\u001b[0m \u001b[31m10.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "\n",
        "# Import Qiskit\n",
        "from qiskit import QuantumCircuit\n",
        "from qiskit import transpile\n",
        "from qiskit.visualization import plot_histogram, plot_state_city\n",
        "# from matplotlib import style\n",
        "%matplotlib inline\n",
        "import qiskit.quantum_info as qi"
      ],
      "metadata": {
        "id": "q7AIXH1gKraQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Part 2: Define the Quantum Circuit"
      ],
      "metadata": {
        "id": "YqtWZiePY-tW"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 2.1: Create the circuit"
      ],
      "metadata": {
        "id": "9WtYxOa5TugK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Create circuit\n",
        "circ = QuantumCircuit(3, 3)\n",
        "circ.h(0)\n",
        "circ.cx(0, 1)\n",
        "circ.cx(1, 2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YtUXcrBpRD51",
        "outputId": "7788951a-ca2c-4c46-f953-961b740c18b5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<qiskit.circuit.instructionset.InstructionSet at 0x793e64be5990>"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 2.2: Measure and show the circuit"
      ],
      "metadata": {
        "id": "MOY0Pn_PTnxl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "circ.measure([0,1,2],[0,1,2])\n",
        "circ.draw()"
      ],
      "metadata": {
        "id": "hQmBSftNRj1E",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 156
        },
        "outputId": "d8f892b7-b4f4-4de8-b5f9-9ef2116a182a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     ┌───┐          ┌─┐      \n",
              "q_0: ┤ H ├──■───────┤M├──────\n",
              "     └───┘┌─┴─┐     └╥┘┌─┐   \n",
              "q_1: ─────┤ X ├──■───╫─┤M├───\n",
              "          └───┘┌─┴─┐ ║ └╥┘┌─┐\n",
              "q_2: ──────────┤ X ├─╫──╫─┤M├\n",
              "               └───┘ ║  ║ └╥┘\n",
              "c: 3/════════════════╩══╩══╩═\n",
              "                     0  1  2 "
            ],
            "text/html": [
              "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">     ┌───┐          ┌─┐      \n",
              "q_0: ┤ H ├──■───────┤M├──────\n",
              "     └───┘┌─┴─┐     └╥┘┌─┐   \n",
              "q_1: ─────┤ X ├──■───╫─┤M├───\n",
              "          └───┘┌─┴─┐ ║ └╥┘┌─┐\n",
              "q_2: ──────────┤ X ├─╫──╫─┤M├\n",
              "               └───┘ ║  ║ └╥┘\n",
              "c: 3/════════════════╩══╩══╩═\n",
              "                     0  1  2 </pre>"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Part 3: Transpile and run on aer simulator"
      ],
      "metadata": {
        "id": "NwQHk3X9ZLOj"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 3.1: Setup the Ideal aer simulator"
      ],
      "metadata": {
        "id": "DRtmW4sn4-lS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install qiskit-aer --quiet\n",
        "from qiskit_aer import Aer\n",
        "\n",
        "Aer.backends()\n",
        "\n",
        "simulator = Aer.get_backend('aer_simulator')"
      ],
      "metadata": {
        "id": "-yOwRW6F5h9R",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6b7edf33-040d-44b6-a16f-1c3b4c93e021"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m12.3/12.3 MB\u001b[0m \u001b[31m28.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 3.2: Transpile and run the circuit on aer simulator"
      ],
      "metadata": {
        "id": "15QkOEBo5Iwn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Transpile for simulator\n",
        "simulator = Aer.get_backend('aer_simulator')\n",
        "circ = transpile(circ, simulator)\n",
        "\n",
        "# Run and get counts\n",
        "result = simulator.run(circ).result()\n",
        "counts = result.get_counts(circ)\n",
        "plot_histogram(counts, title='GHZ-State counts with ideal simulator')"
      ],
      "metadata": {
        "id": "5SM6Na7tQ4fm",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 495
        },
        "outputId": "ccd45917-27a9-43ff-a322-84d0af563a9f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## PART 4: Transpile and run on an noisy simulator"
      ],
      "metadata": {
        "id": "QyY3lGAU4vat"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 4.1: Set up the aer noisy simulator"
      ],
      "metadata": {
        "id": "J4m2DOgk7CMu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# !pip install qiskit-ibmq-provider"
      ],
      "metadata": {
        "id": "C3auXQtH_oD0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from qiskit.providers.fake_provider import FakeVigo\n",
        "device_backend = FakeVigo()"
      ],
      "metadata": {
        "id": "0ESlqJLN7Rxm",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c52c7adf-b1e3-4494-cb89-db79b5e07f0f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ImportError",
          "evalue": "cannot import name 'FakeVigo' from 'qiskit.providers.fake_provider' (/usr/local/lib/python3.10/dist-packages/qiskit/providers/fake_provider/__init__.py)",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mImportError\u001b[0m                               Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-8-5b00451e5a37>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mqiskit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mproviders\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfake_provider\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mFakeVigo\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mdevice_backend\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mFakeVigo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mImportError\u001b[0m: cannot import name 'FakeVigo' from 'qiskit.providers.fake_provider' (/usr/local/lib/python3.10/dist-packages/qiskit/providers/fake_provider/__init__.py)",
            "",
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0;32m\nNOTE: If your import is failing due to a missing package, you can\nmanually install dependencies using either !pip or !apt.\n\nTo view examples of installing some common dependencies, click the\n\"Open Examples\" button below.\n\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n"
          ],
          "errorDetails": {
            "actions": [
              {
                "action": "open_url",
                "actionText": "Open Examples",
                "url": "/notebooks/snippets/importing_libraries.ipynb"
              }
            ]
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sim_vigo = AerSimulator.from_backend(device_backend)"
      ],
      "metadata": {
        "id": "iaezPfHK45JX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 4.2: transpile and run on the noisy simulator"
      ],
      "metadata": {
        "id": "_uf4dJ6L7Ivv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Transpile the circuit for the noisy basis gates\n",
        "tcirc = transpile(circ, sim_vigo)\n",
        "\n",
        "# Execute noisy simulation and get counts\n",
        "result_noise = sim_vigo.run(tcirc).result()\n",
        "counts_noise = result_noise.get_counts(0)\n",
        "plot_histogram(counts_noise,\n",
        "               title=\"Counts for 3-qubit GHZ state with device noise model\")"
      ],
      "metadata": {
        "id": "Q0i7M5pK8YJA"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}