Dynamic_Circuits_&_If_Statements.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/OJB-Quantum/Notebooks/blob/main/Dynamic_Circuits_%26_If_Statements.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "d3195c89",
      "metadata": {
        "tags": [],
        "id": "d3195c89",
        "outputId": "f079c823-ef2c-44fc-cfbb-2ea83809423d"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 305.929x200.667 with 1 Axes>"
            ]
          },
          "execution_count": 92,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister\n",
        "\n",
        "qr = QuantumRegister(1)\n",
        "cr = ClassicalRegister(1)\n",
        "qc = QuantumCircuit(qr, cr)\n",
        "\n",
        "qc.h(qr[0])\n",
        "qc.measure(qr[0], cr[0])\n",
        "\n",
        "\n",
        "qc.draw(\"mpl\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "10d6953d",
      "metadata": {
        "id": "10d6953d",
        "outputId": "42ed3e55-6fed-4aec-cf50-40856d3255d5"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 556.56x284.278 with 1 Axes>"
            ]
          },
          "execution_count": 95,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "from qiskit import QuantumCircuit\n",
        "from qiskit.circuit import QuantumRegister, ClassicalRegister\n",
        "\n",
        "qr = QuantumRegister(1)\n",
        "cr = ClassicalRegister(2)\n",
        "qc = QuantumCircuit(qr, cr)\n",
        "\n",
        "# unpack the qubit and classical bits from the registers\n",
        "(q0,) = qr\n",
        "b0, b1 = cr\n",
        "\n",
        "# apply Hadamard\n",
        "qc.h(q0)\n",
        "# measure\n",
        "qc.measure(q0, b0)\n",
        "\n",
        "# begin if test block. the contents of the block are executed if b0 == 1\n",
        "with qc.if_test((b0, 1)):\n",
        "    # if the condition is satisfied (b0 == 1), then flip the bit back to 0\n",
        "    qc.x(q0)\n",
        "# finally, measure q0 again\n",
        "qc.measure(q0, b1)\n",
        "\n",
        "qc.draw(output=\"mpl\", idle_wires=False)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "06a4eee8",
      "metadata": {
        "id": "06a4eee8",
        "outputId": "38033582-e38f-44f6-9f0d-631d95f70cea"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Counts: {'00': 528, '01': 496}\n"
          ]
        }
      ],
      "source": [
        "from qiskit_aer import AerSimulator\n",
        "\n",
        "# initialize the simulator\n",
        "backend_sim = AerSimulator()\n",
        "\n",
        "# run the circuit\n",
        "reset_sim_job = backend_sim.run(qc)\n",
        "# get the results\n",
        "reset_sim_result = reset_sim_job.result()\n",
        "# retrieve the bitstring counts\n",
        "reset_sim_counts = reset_sim_result.get_counts()\n",
        "\n",
        "print(f\"Counts: {reset_sim_counts}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "439359c9",
      "metadata": {
        "id": "439359c9",
        "outputId": "c2710f41-af93-488c-c173-7aec7ab61cde"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ]
          },
          "execution_count": 97,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "from qiskit.visualization import *\n",
        "\n",
        "# plot histogram\n",
        "plot_histogram(reset_sim_counts)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "97acd850",
      "metadata": {
        "id": "97acd850",
        "outputId": "73061007-ab2b-4043-dedb-ae6bdf9cb775"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 574.993x367.889 with 1 Axes>"
            ]
          },
          "execution_count": 98,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "qr = QuantumRegister(2)\n",
        "cr = ClassicalRegister(2)\n",
        "qc = QuantumCircuit(qr, cr)\n",
        "\n",
        "q0, q1 = qr\n",
        "b0, b1 = cr\n",
        "\n",
        "qc.h(q0)\n",
        "qc.measure(q0, b0)\n",
        "\n",
        "####### your code goes here #######\n",
        "# begin if test block. the contents of the block are executed if b0 == 0\n",
        "with qc.if_test((b0, 0)):\n",
        "    # if the condition is satisfied (b0 == 0), then flip the bit back to 1\n",
        "    qc.x(q1)\n",
        "# finally, measure q1 again\n",
        "\n",
        "qc.measure(q1, b1)\n",
        "qc.draw(output=\"mpl\", idle_wires=False)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "a5587d76",
      "metadata": {
        "id": "a5587d76"
      },
      "outputs": [],
      "source": [
        "from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister\n",
        "from qiskit import transpile\n",
        "\n",
        "controls = QuantumRegister(2, name=\"control\")\n",
        "target = QuantumRegister(1, name=\"target\")\n",
        "\n",
        "mid_measure = ClassicalRegister(2, name=\"mid\")\n",
        "final_measure = ClassicalRegister(1, name=\"final\")\n",
        "\n",
        "base = QuantumCircuit(controls, target, mid_measure, final_measure)\n",
        "circuit = base"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "fc47a87d",
      "metadata": {
        "id": "fc47a87d",
        "outputId": "2b36f28c-732a-4976-df8c-db69d52aa633"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 787.878x535.111 with 1 Axes>"
            ]
          },
          "execution_count": 103,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "def trial(circuit, target, controls, measures):\n",
        "    \"Probabilistically perform Rx(theta) on the target, where cos(theta) = 3/5.\"\n",
        "\n",
        "    \n",
        "    ####### your code goes here #######\n",
        "    circuit.h(target)\n",
        "    circuit.h(controls)\n",
        "    circuit.ccx(*controls, target)\n",
        "    circuit.s(target)\n",
        "    circuit.ccx(*controls, target)\n",
        "    circuit.h(controls)\n",
        "    circuit.h(target)\n",
        "    circuit.measure(controls, measures)\n",
        "\n",
        "qc = base.copy_empty_like()\n",
        "trial(qc, target, controls, mid_measure)\n",
        "qc.draw(\"mpl\", cregbundle=False)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "73ba4506",
      "metadata": {
        "id": "73ba4506",
        "outputId": "96025967-8d3d-425f-c772-1789c6c54e6c"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1289.54x535.111 with 1 Axes>"
            ]
          },
          "execution_count": 109,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "def reset_controls(circuit:QuantumCircuit,controls:QuantumRegister,measures:ClassicalRegister):\n",
        "    \"\"\"Reset the control qubits if they are in |1>.\"\"\"\n",
        "\n",
        "    ####### your code goes here #######\n",
        "    with circuit.if_test((mid_measure[0], 1)):\n",
        "    # if the condition is satisfied (mid_measure[0] == 1), then flip control qubit 1\n",
        "        circuit.x(controls[0])\n",
        "\n",
        "    with circuit.if_test((mid_measure[1], 1)):\n",
        "    # if the condition is satisfied (mid_measure[0] == 1), then flip control qubit 2\n",
        "        circuit.x(controls[1])\n",
        "# finally, measure control qubit again, where the if_test started\n",
        "\n",
        "#qc.measure(controls[0], mid_measure[0])    \n",
        "    \n",
        "qc = base.copy_empty_like()\n",
        "trial(qc, target, controls, mid_measure)\n",
        "reset_controls(qc, controls, mid_measure)\n",
        "qc.measure(controls, mid_measure)\n",
        "qc.draw(\"mpl\", cregbundle=False)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "3bf0cfa3-67f1-4c62-beab-560645e78ba7",
      "metadata": {
        "tags": [],
        "id": "3bf0cfa3-67f1-4c62-beab-560645e78ba7",
        "outputId": "9a970118-b1b6-4f66-f973-111d926e117f"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 1540.38x535.111 with 1 Axes>"
            ]
          },
          "execution_count": 115,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Set the maximum number of trials\n",
        "max_trials = 2\n",
        "\n",
        "# Create a clean circuit with the same structure (bits, registers, etc)\n",
        "# as the initial base we set up.\n",
        "circuit = base.copy_empty_like()\n",
        "\n",
        "# The first trial does not need to reset its inputs, since the controls\n",
        "# are guaranteed to start in the |0> state.\n",
        "trial(circuit, target, controls, mid_measure)\n",
        "\n",
        "# Manually add the rest of the trials.  In the future, we will be\n",
        "# able to use a dynamic `while` loop to do this, but for now, we\n",
        "# statically add each loop iteration with a manual condition check\n",
        "# on each one.  This involves more classical synchronizations than\n",
        "# the while loop, but will suffice for now.\n",
        "for _ in range(max_trials - 1):\n",
        "    reset_controls(circuit, controls, mid_measure)\n",
        "    with circuit.if_test((mid_measure, 0b00)) as else_:\n",
        "        # This is the success path, but Qiskit can't directly\n",
        "        # represent a negative condition yet, so we have an\n",
        "        # empty `true` block in order to use the `else` branch.\n",
        "        pass\n",
        "    with else_:\n",
        "        # First reset the target.\n",
        "        circuit.x(target)\n",
        "        # Then repeat the trial.\n",
        "        trial(circuit, target, controls, mid_measure)\n",
        "\n",
        "# We need to measure the control qubits again to ensure we\n",
        "# get their final results; this is a hardware limitation.\n",
        "circuit.measure(controls, mid_measure)\n",
        "\n",
        "# Finally, let's measure our target, to check that we're\n",
        "# getting the rotation we desired.\n",
        "circuit.measure(target, final_measure)\n",
        "\n",
        "circuit.draw(\"mpl\", cregbundle=False)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "f576413c",
      "metadata": {
        "id": "f576413c",
        "outputId": "e91a836e-e8b6-403a-9206-87f415b1b11c"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ]
          },
          "execution_count": 117,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "sim = AerSimulator()\n",
        "job = sim.run(circuit, shots=1000)\n",
        "result = job.result()\n",
        "counts = result.get_counts()\n",
        "\n",
        "plot_histogram(counts)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "f917e10b",
      "metadata": {
        "id": "f917e10b"
      },
      "outputs": [],
      "source": [
        "from qiskit_ibm_provider import IBMProvider\n",
        "\n",
        "provider = IBMProvider()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "691dd8d8",
      "metadata": {
        "id": "691dd8d8",
        "outputId": "1792f8cd-e0ec-44de-f4ef-1e65d80fe1dd"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "The quantum computer for this session now is ibm_peekskill\n"
          ]
        }
      ],
      "source": [
        "# here the provider details can be modified based on the accessible machines of interest.\n",
        "from qiskit.providers.ibmq import IBMQ\n",
        "hub = \"qc-spring-23-3\"\n",
        "group = \"group-4\"\n",
        "project = \"recKKLk8qrlM6pfXX\"\n",
        "\n",
        "backend_name = \"ibm_peekskill\"\n",
        "backend = provider.get_backend(backend_name, instance=f\"qc-spring-23-3/group-4/recKKLk8qrlM6pfXX\")\n",
        "#ibmq_backend = 'ibm_peekskill'\n",
        "\n",
        "print(\"The quantum computer for this session now is\",ibmq_backend)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "57735462",
      "metadata": {
        "id": "57735462"
      },
      "outputs": [],
      "source": [
        "from qiskit import transpile\n",
        "from qiskit.transpiler import Target, InstructionProperties\n",
        "from qiskit.circuit import Parameter"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "69d7a731-c7f9-45dd-973e-1e147a42703b",
      "metadata": {
        "tags": [],
        "id": "69d7a731-c7f9-45dd-973e-1e147a42703b"
      },
      "outputs": [],
      "source": [
        "qc_transpiled = transpile(circuit, backend)\n",
        "job = backend.run(qc_transpiled, shots=1000, dynamic=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "7ee1c832",
      "metadata": {
        "id": "7ee1c832",
        "outputId": "8cccf194-06cb-4d83-8493-0db400662369"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ]
          },
          "execution_count": 122,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "counts = job.result().get_counts()\n",
        "\n",
        "plot_histogram(counts)"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3 (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": "3.10.8"
    },
    "colab": {
      "provenance": [],
      "include_colab_link": true
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}