{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f1c7ce88",
   "metadata": {},
   "source": [
    "# IBM Optimizations using Qiskit"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "varied-shame",
   "metadata": {},
   "source": [
    "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Infleqtion/client-superstaq/blob/main/docs/source/optimizations/ibm/ibmq_compile_qss.ipynb) [![Launch Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Infleqtion/client-superstaq/HEAD?labpath=docs/source/optimizations/ibm/ibmq_compile_qss.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8c25005",
   "metadata": {},
   "source": [
    "Below is a brief tutorial on Superstaq optimizations for IBM Quantum superconducting qubit devices. For more information on IBM Quantum, visit their website [here](https://www.ibm.com/quantum)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9a7d9b5",
   "metadata": {},
   "source": [
    "## Imports and API Token\n",
    "\n",
    "This example tutorial notebook uses `qiskit-superstaq`, our Superstaq client for Qiskit; you can try it out by running `pip install qiskit-superstaq[examples]`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4316dd2c-bad2-42f6-ab39-383a1ba6a6d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    import qiskit\n",
    "    import qiskit_superstaq as qss\n",
    "except ImportError:\n",
    "    print(\"Installing qiskit-superstaq...\")\n",
    "    %pip install --quiet 'qiskit-superstaq[examples]'\n",
    "    print(\"Installed qiskit-superstaq.\")\n",
    "    print(\"You may need to restart the kernel to import newly installed packages.\")\n",
    "    import qiskit\n",
    "    import qiskit_superstaq as qss\n",
    "\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b4d8cf9",
   "metadata": {},
   "source": [
    "To interface Superstaq via Qiskit, we must first instantiate a provider in `qiskit-superstaq` with `SuperstaqProvider()`. We then supply a Superstaq API token (or key) by either providing the API token as an argument of `qss.SuperstaqProvider()` or by setting it as an environment variable (see more details [here](https://superstaq.readthedocs.io/en/latest/get_started/basics/basics_qss.html#Set-up-access-to-Superstaq%E2%80%99s-API))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8d8d329d-5c52-44bd-9e35-3052268a4530",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Provide your Superstaq API key using the \"api_key\" argument\n",
    "provider = qss.SuperstaqProvider()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4828ee8",
   "metadata": {},
   "source": [
    "## Single Circuit Compilation\n",
    "\n",
    "Let us start by creating an example Qiskit circuit that we will then compile and optimize for the 127-qubit IBM Quantum `brisbane` processor."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1e68dcda-f84a-4b93-aea0-f64c1a5108f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 663.998x284.278 with 1 Axes>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a two-qubit qiskit circuit\n",
    "theta = np.random.uniform(0, 4 * np.pi)\n",
    "circuit = qiskit.QuantumCircuit(2)\n",
    "circuit.cx(0, 1)\n",
    "circuit.rz(theta, 1)\n",
    "circuit.cx(0, 1)\n",
    "circuit.measure_all()\n",
    "\n",
    "# Draw circuit for visualization\n",
    "circuit.draw(output=\"mpl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2116e292",
   "metadata": {},
   "source": [
    "We will now compile the above circuit to IBM's `brisbane` processor and visualize the differences by drawing the compiled circuit. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "135bc08f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1290.83x284.278 with 1 Axes>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compile with ibmq compile\n",
    "compiler_output = provider.ibmq_compile(circuit, target=\"ibmq_brisbane_qpu\")\n",
    "\n",
    "# Call circuit from the compiler output to get the corresponding output circuit\n",
    "output_circuit = compiler_output.circuit\n",
    "\n",
    "# Visualize the compiled circuit\n",
    "output_circuit.draw(\"mpl\", idle_wires=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa165427",
   "metadata": {},
   "source": [
    "The resulting output is now a circuit compiled to `brisbane`'s native operations. With Superstaq compilation, you can also observe the gates and gate times for the compiled circuit using Qiskit’s timeline drawer (see [Qiskit Timeline Visualizations Documentation](https://docs.quantum.ibm.com/api/qiskit/qiskit.visualization.timeline_drawer)) by running the following:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3ca9f750",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x300 with 1 Axes>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The pulse gate circuit is obtained via the `pulse_gate_circuit` attribute\n",
    "pulse_circuit = compiler_output.pulse_gate_circuit\n",
    "\n",
    "custom_style = {\"formatter.general.fig_width\": 30, \"formatter.general.fig_unit_height\": 1}\n",
    "style = qiskit.visualization.timeline.IQXStandard(**custom_style)\n",
    "\n",
    "qiskit.visualization.timeline_drawer(pulse_circuit, idle_wires=False, style=style)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30c3a395",
   "metadata": {},
   "source": [
    "## Multiple Circuits Compilation\n",
    "\n",
    "All the functionalities we have seen so far can also be used on a multiple-circuit input as well. To illustrate this, let us create a different example two-qubit circuit: a Bell-state circuit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1520302f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 580.387x284.278 with 1 Axes>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create second circuit\n",
    "bell_circuit = qiskit.QuantumCircuit(2)\n",
    "bell_circuit.h(0)\n",
    "bell_circuit.cx(0, 1)\n",
    "bell_circuit.measure_all()\n",
    "\n",
    "# Draw second circuit for visualization\n",
    "bell_circuit.draw(\"mpl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c055c11",
   "metadata": {},
   "source": [
    "By passing multiple circuits as a list to the `ibmq_compile` endpoint, we can compile all of them individually with a single call to the endpoint. This will return all the corresponding compiled circuits and pulse gate circuits back as a list, like so:  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9fa01c3e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create list of circuits\n",
    "circuit_list = [circuit, bell_circuit]\n",
    "\n",
    "# Compile list of circuits\n",
    "compiler_output_list = provider.ibmq_compile(circuit_list, \"ibmq_brisbane_qpu\")\n",
    "\n",
    "# The list of compiled output circuits is stored in the `circuits` attribute instead of `circuit`. Likewise for\n",
    "# pulse sequences.\n",
    "output_circuits = compiler_output_list.circuits\n",
    "pulse_gate_circuits = compiler_output_list.pulse_gate_circuits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "736f6d27",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Compiled circuit 1 \n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1290.83x284.278 with 1 Axes>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Visualize the first compiled circuit\n",
    "print(\"Compiled circuit 1 \\n\")\n",
    "output_circuits[0].draw(\"mpl\", idle_wires=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4f3c6525",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x300 with 1 Axes>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Visualize the pulse gate circuit for the first compiled circuit\n",
    "qiskit.visualization.timeline_drawer(pulse_gate_circuits[0], idle_wires=False, style=style)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "714c2859",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Compiled circuit 2 \n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 956.385x284.278 with 1 Axes>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Visualize the second compiled circuit\n",
    "print(\"Compiled circuit 2 \\n\")\n",
    "output_circuits[1].draw(\"mpl\", idle_wires=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "91121471",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x300 with 1 Axes>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Visualize the pulse gate circuit for the first compiled circuit\n",
    "qiskit.visualization.timeline_drawer(pulse_gate_circuits[1], idle_wires=False, style=style)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "490036bb",
   "metadata": {},
   "source": [
    "## Using the Superstaq Simulator\n",
    "\n",
    "Lastly, we will show (a) how to execute a circuit on a backend and (b) how to simulate circuit execution. Simulation is available to free trial users, and can be done by passing the `\"dry-run\"` method parameter when calling `run()` on the Superstaq provider."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "331aec28",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'00': 530, '11': 470}\n"
     ]
    }
   ],
   "source": [
    "# Get IBM Quantum backend from provider\n",
    "backend = provider.get_backend(\"ibmq_brisbane_qpu\")\n",
    "job = backend.run(\n",
    "    bell_circuit,\n",
    "    shots=1000,\n",
    "    method=\"dry-run\",  # Specify \"dry-run\" as the method to run Superstaq simulation\n",
    ")\n",
    "\n",
    "# Get the counts from the measurement\n",
    "print(job.result().get_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "324f3dd0",
   "metadata": {},
   "source": [
    "### Addendum: Compiling via Superstaq backend\n",
    "You can also compile circuits via the `compile` method of the backend directly. This is identical to calling `ibmq_compile` on the provider, but more closely matches Qiskit syntax."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b45ebadf",
   "metadata": {},
   "outputs": [],
   "source": [
    "compiler_output = backend.compile(bell_circuit)\n",
    "output_circuit = compiler_output.circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "9eb7512b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 956.385x284.278 with 1 Axes>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Visualize the compiled circuit\n",
    "output_circuit.draw(\"mpl\", idle_wires=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d94c141c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x300 with 1 Axes>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Visualize the pulse gate circuit\n",
    "qiskit.visualization.timeline_drawer(\n",
    "    compiler_output.pulse_gate_circuit, idle_wires=False, style=style\n",
    ")"
   ]
  }
 ],
 "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": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}