{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Project 4: Amplitude damping\n",
    "\n",
    "# Solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Imports\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from datetime import datetime\n",
    "import json\n",
    "import copy\n",
    "\n",
    "# Main qiskit imports\n",
    "from qiskit import QuantumRegister, ClassicalRegister\n",
    "from qiskit import QuantumCircuit, execute, Aer, IBMQ\n",
    "\n",
    "# Error mitigation\n",
    "from qiskit.ignis.mitigation.measurement import (complete_meas_cal, \n",
    "                                                CompleteMeasFitter, \n",
    "                                                MeasurementFilter)\n",
    "\n",
    "# Utility functions\n",
    "from qiskit.tools.jupyter import *\n",
    "from qiskit.tools.monitor import job_monitor\n",
    "from qiskit.providers.jobstatus import JobStatus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We use ibmq_vigo\n",
    "IBMQ.load_account()\n",
    "backend = IBMQ.get_provider(hub='ibm-q', group='open', project='main').get_backend('ibmq_quito')\n",
    "\n",
    "# Local simulator and vector simulator\n",
    "simulator = Aer.get_backend('qasm_simulator')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Task 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def c1(R,t):\n",
    "    \"\"\"Returns the coherence factor in the amplitude damping channel\n",
    "    \n",
    "    Args:\n",
    "        R (float): value of R = \\gamma_0/\\lambda\n",
    "        t (float): value of the time variable\n",
    "    \n",
    "    Returns:\n",
    "        A float number\n",
    "    \"\"\"\n",
    "    \n",
    "    if R < 0.5:\n",
    "        c1 = np.exp(- t / 2.0) * (np.cosh(t * np.sqrt(1.0 - 2.0 * R) / 2.0) + 1.0 / np.sqrt(1.0 - 2.0 * R) * np.sinh(t * np.sqrt(1.0 - 2.0 * R) / 2.0))\n",
    "    else:\n",
    "        c1 = np.exp(- t / 2.0) * (np.cos(t * np.sqrt(2.0 * R - 1.0) / 2.0) + 1.0 / np.sqrt(2.0 * R - 1.0) * np.sin(t * np.sqrt(2.0 * R - 1.0) / 2.0))\n",
    "    \n",
    "    return c1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def amplitude_damping_channel(q, c, sys, env, R, t):\n",
    "    \"\"\"Returns a QuantumCircuit implementing the amplitude damping channel on the system qubit\n",
    "    \n",
    "    Args:\n",
    "        q (QuantumRegister): the register to use for the circuit\n",
    "        c (ClassicalRegister): the register to use for the measurement of the system qubit\n",
    "        sys (int): index for the system qubit\n",
    "        env (int): index for the environment qubit\n",
    "        R (float): value of R = \\gamma_0/\\lambda\n",
    "        t (float): value of the time variable\n",
    "    \n",
    "    Returns:\n",
    "        A QuantumCircuit object\n",
    "    \"\"\"\n",
    "    ad = QuantumCircuit(q, c)\n",
    "    \n",
    "    # Rotation angle\n",
    "    theta = np.arccos(c1(R, t))\n",
    "    \n",
    "    # Channel (notice the extra factor of 2 due to the definition\n",
    "    # of the unitary gate in qiskit)\n",
    "    ad.cu(2.0 * theta, 0.0, 0.0, 0.0, q[sys], q[env])\n",
    "    ad.cx(q[env], q[sys])\n",
    "    \n",
    "    # Masurement in the computational basis\n",
    "    ad.measure(q[sys], c[0])\n",
    "    \n",
    "    return ad\n",
    "\n",
    "# We choose to add the initial condition elsewhere\n",
    "def initial_state(q, sys):\n",
    "    \"\"\"Returns a QuantumCircuit implementing the initial condition for the amplitude damping channel\n",
    "    \n",
    "    Args:\n",
    "        q (QuantumRegister): the register to use for the circuit\n",
    "        sys (int): index for the system qubit\n",
    "    \n",
    "    Returns:\n",
    "        A QuantumCircuit object\n",
    "    \"\"\"\n",
    "    # Create circuit\n",
    "    ic = QuantumCircuit(q)\n",
    "    \n",
    "    # System in |1>\n",
    "    ic.x(q[sys])\n",
    "    \n",
    "    return ic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "SHOTS = 8192\n",
    "\n",
    "# The values for R and corresponding times\n",
    "R_values = [0.2, 100.0, 200.0, 400.0]\n",
    "npoints = 30\n",
    "t_values = {}\n",
    "for R in R_values:\n",
    "    t_values[R] = np.linspace(0.0, 6.0 * np.pi / np.sqrt(abs(2.0 * R - 1.0)), npoints)\n",
    "\n",
    "# We create the quantum circuits\n",
    "q = QuantumRegister(5, name=\"q\")\n",
    "c = ClassicalRegister(1, name=\"c\")\n",
    "\n",
    "## Indices of the system and environment qubits\n",
    "sys = 1\n",
    "env = 2\n",
    "\n",
    "## For values of R and thirty values of t for each\n",
    "circuits = {}\n",
    "for R in R_values:\n",
    "    circuits[R] = []\n",
    "    for t in t_values[R]:\n",
    "        circuits[R].append(initial_state(q, sys)\n",
    "                           + amplitude_damping_channel(q, c, sys, env, R, t))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
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\n"
     },
     "metadata": {},
     "execution_count": 6
    }
   ],
   "source": [
    "circuits[0.2][1].draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 720x864 with 4 Axes>",
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "# Execute the circuits on the local simulator\n",
    "jobs_sim = {}\n",
    "for R in R_values:\n",
    "    jobs_sim[R] = execute(circuits[R], backend = simulator, shots = SHOTS)\n",
    "\n",
    "# Analyse the outcomes\n",
    "populations_sim = {}\n",
    "for R in R_values:\n",
    "    populations_sim[R] = []\n",
    "    current_job_res = jobs_sim[R].result()\n",
    "    for i in range(npoints):\n",
    "        counts = current_job_res.get_counts(i)\n",
    "        if '1' in counts:\n",
    "            sm = counts['1']/float(SHOTS)\n",
    "        populations_sim[R].append(sm)\n",
    "\n",
    "# Plot the results\n",
    "fig_idx = 221\n",
    "plt.figure(figsize=(10,12))\n",
    "for R in R_values:\n",
    "    plt.subplot(fig_idx)\n",
    "    plt.plot(t_values[R], populations_sim[R], label=f\"R = {R}\")\n",
    "    plt.xlabel('t')\n",
    "    plt.ylabel('Population')\n",
    "    plt.legend()\n",
    "    fig_idx += 1\n",
    "    plt.grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Homework (without non-Markovianity witness)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calibration circuits\n",
    "cal_circuits, state_labels = complete_meas_cal([sys], q, c)\n",
    "# Run the calibration job\n",
    "calibration_job = execute(cal_circuits, backend, shots=SHOTS)\n",
    "\n",
    "# Run the circuits and save the jobs\n",
    "jobs = {}\n",
    "for R in R_values:\n",
    "    jobs[R] = execute(circuits[R], backend = backend, shots = SHOTS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x864 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Use the calibration job to implement the error mitigation\n",
    "meas_fitter = CompleteMeasFitter(calibration_job.result(), state_labels)\n",
    "meas_filter = meas_fitter.filter\n",
    "\n",
    "# Analyse the outcomes\n",
    "populations = {}\n",
    "for R in jobs:\n",
    "    populations[R] = []\n",
    "    current_job_res = jobs[R].result()\n",
    "    for i in range(npoints):\n",
    "        counts = meas_filter.apply(current_job_res).get_counts(i)\n",
    "        if '1' in counts:\n",
    "            sm = counts['1']/float(SHOTS)\n",
    "        populations[R].append(sm)\n",
    "\n",
    "# Plot the results\n",
    "fig_idx = 221\n",
    "plt.figure(figsize=(10,12))\n",
    "for R in R_values:\n",
    "    plt.subplot(fig_idx)\n",
    "    plt.plot(t_values[R], populations[R], label='Experiment')\n",
    "    plt.plot(t_values[R], populations_sim[R], label='Simulation')\n",
    "    plt.xlabel('t')\n",
    "    plt.ylabel('Population')\n",
    "    fig_idx += 1\n",
    "    plt.grid()\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Task 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def amplitude_damping_channel_witness(q, c, sys, env, anc, observable, R, t):\n",
    "    \"\"\"Returns a QuantumCircuit implementing the amplitude damping channel on the system qubit with non-Markovianity witness\n",
    "    \n",
    "    Args:\n",
    "        q (QuantumRegister): the register to use for the circuit\n",
    "        c (ClassicalRegister): the register to use for the measurement of the system and ancilla qubits\n",
    "        sys (int): index for the system qubit\n",
    "        env (int): index for the environment qubit\n",
    "        anc (int): index for the ancillary qubit\n",
    "        observable (str): the observable to be measured\n",
    "        R (float): value of R = \\gamma_0/\\lambda\n",
    "        t (float): value of the time variable\n",
    "    \n",
    "    Returns:\n",
    "        A QuantumCircuit object\n",
    "    \"\"\"\n",
    "    ad = QuantumCircuit(q, c)\n",
    "    \n",
    "    # Rotation angle\n",
    "    theta = 2.0 * np.arccos(c1(R, t))\n",
    "    \n",
    "    # Channel\n",
    "    ad.cu3(theta, 0.0, 0.0, q[sys], q[env])\n",
    "    ad.cx(q[env], q[sys])\n",
    "    \n",
    "    # Masurement of the corresponding observable\n",
    "    if observable == 'xx':\n",
    "        ad.h(sys)\n",
    "        ad.h(anc)\n",
    "    elif observable == 'yy':\n",
    "        ad.sdg(sys)\n",
    "        ad.h(sys)\n",
    "        ad.sdg(anc)\n",
    "        ad.h(anc)\n",
    "    ad.measure(sys,c[0])\n",
    "    ad.measure(anc,c[1])\n",
    "    \n",
    "    return ad\n",
    "\n",
    "# We set the initial entangled state separately\n",
    "def initial_state_witness(q, sys, anc):\n",
    "    \"\"\"Returns a QuantumCircuit implementing the initial condition for the amplitude damping channel with non-Markovianity witness\n",
    "    \n",
    "    Args:\n",
    "        q (QuantumRegister): the register to use for the circuit\n",
    "        sys (int): index for the system qubit\n",
    "        anc (int): index for the ancilla qubit\n",
    "    \n",
    "    Returns:\n",
    "        A QuantumCircuit object\n",
    "    \"\"\"\n",
    "    # Create circuit\n",
    "    ic = QuantumCircuit(q)\n",
    "    \n",
    "    # System and ancilla in |\\psi^+>\n",
    "    ic.h(q[sys])\n",
    "    ic.cx(q[sys], q[anc])\n",
    "    \n",
    "    return ic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "SHOTS = 8192\n",
    "\n",
    "# The values for R and corresponding times,\n",
    "# as well as the observables needed for the witness\n",
    "observables = ['xx', 'yy', 'zz']\n",
    "R_values = [0.2, 100.0]\n",
    "npoints = 30\n",
    "t_values = {}\n",
    "for R in R_values:\n",
    "    t_values[R] = np.linspace(0.0, 6.0 * np.pi / np.sqrt(abs(2.0 * R - 1.0)), npoints)\n",
    "\n",
    "# We create the quantum circuits\n",
    "q = QuantumRegister(5, name=\"q\")\n",
    "c = ClassicalRegister(2, name=\"c\")\n",
    "\n",
    "## Indices of the system, environment and ancillary qubits\n",
    "sys = 1\n",
    "env = 2\n",
    "anc = 3\n",
    "\n",
    "## Two values of R and thirty values of t for each\n",
    "## The witness requires measuring three observables per point\n",
    "circuits = {}\n",
    "for R in R_values:\n",
    "    circuits[R] = {}\n",
    "    for observable in observables:\n",
    "        circuits[R][observable] = []\n",
    "        for t in t_values[R]:\n",
    "            circuits[R][observable].append(initial_state_witness(q, sys, anc)\n",
    "                               +amplitude_damping_channel_witness(q, c, sys, env, anc, observable, R, t))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 638.12x385.28 with 1 Axes>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuits[0.2]['yy'][1].draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Execute the circuits on the local simulator\n",
    "jobs_sim = {}\n",
    "for R in R_values:\n",
    "    jobs_sim[R] = {}\n",
    "    for observable in observables:\n",
    "        jobs_sim[R][observable] = execute(circuits[R][observable], backend = simulator, shots = SHOTS)\n",
    "\n",
    "# Analyse the outcomes\n",
    "## Compute expected values\n",
    "expected_sim = {}\n",
    "for R in R_values:\n",
    "    expected_sim[R] = {}\n",
    "    for observable in observables:\n",
    "        expected_sim[R][observable] = []\n",
    "        current_job_res = jobs_sim[R][observable].result()\n",
    "        for i in range(npoints):\n",
    "            counts = current_job_res.get_counts(i)\n",
    "            expc = 0.0\n",
    "            for outcome in counts:\n",
    "                if outcome[0] == outcome[1]:\n",
    "                    expc += counts[outcome]/float(SHOTS)\n",
    "                else:\n",
    "                    expc -= counts[outcome]/float(SHOTS)\n",
    "            expected_sim[R][observable].append(expc)\n",
    "\n",
    "## Compute witness\n",
    "witness_sim = {}\n",
    "for R in R_values:\n",
    "    witness_sim[R] = []\n",
    "    for i in range(npoints):\n",
    "        w = 0.25*(1.0+expected_sim[R]['xx'][i]-expected_sim[R]['yy'][i]+expected_sim[R]['zz'][i])\n",
    "        witness_sim[R].append(w)\n",
    "\n",
    "# Plot the results\n",
    "fig_idx = 221\n",
    "plt.figure(figsize=(10,12))\n",
    "for R in R_values:\n",
    "    plt.subplot(fig_idx)\n",
    "    plt.plot(t_values[R], witness_sim[R])\n",
    "    plt.xlabel('t')\n",
    "    plt.ylabel('Population')\n",
    "    fig_idx += 1\n",
    "    plt.grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Homework (implementation of non-Markovianity witness)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calibration circuits\n",
    "cal_circuits, state_labels = complete_meas_cal([sys, anc], q, c)\n",
    "# Run the calibration job\n",
    "calibration_job = execute(cal_circuits, backend, shots=SHOTS)\n",
    "\n",
    "# Run the circuits and save the jobs\n",
    "jobs = {}\n",
    "for R in R_values:\n",
    "    jobs[R] = {}\n",
    "    for observable in observables:\n",
    "        jobs[R][observable] = execute(circuits[R][observable], backend = backend, shots = SHOTS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Use the calibration job to implement the error mitigation\n",
    "meas_fitter = CompleteMeasFitter(calibration_job.result(), state_labels)\n",
    "meas_filter = meas_fitter.filter\n",
    "\n",
    "# Analyse the outcomes\n",
    "## Compute expected values\n",
    "expected = {}\n",
    "for R in R_values:\n",
    "    expected[R] = {}\n",
    "    for observable in observables:\n",
    "        expected[R][observable] = []\n",
    "        current_job_res = jobs[R][observable].result()\n",
    "        mitigated_res = meas_filter.apply(current_job_res)\n",
    "        for i in range(npoints):\n",
    "            counts = mitigated_res.get_counts(i)\n",
    "            expc = 0.0\n",
    "            for outcome in counts:\n",
    "                if outcome[0] == outcome[1]:\n",
    "                    expc += counts[outcome]/float(SHOTS)\n",
    "                else:\n",
    "                    expc -= counts[outcome]/float(SHOTS)\n",
    "            expected[R][observable].append(expc)\n",
    "\n",
    "## Compute witness\n",
    "witness = {}\n",
    "for R in R_values:\n",
    "    witness[R] = []\n",
    "    for i in range(npoints):\n",
    "        w = 0.25*(1.0+expected[R]['xx'][i]-expected[R]['yy'][i]+expected[R]['zz'][i])\n",
    "        witness[R].append(w)\n",
    "\n",
    "# Plot the results\n",
    "fig_idx = 221\n",
    "plt.figure(figsize=(10,12))\n",
    "for R in R_values:\n",
    "    plt.subplot(fig_idx)\n",
    "    plt.plot(t_values[R], witness[R], label='Experiment')\n",
    "    plt.plot(t_values[R], witness_sim[R], label='Simulation')\n",
    "    plt.xlabel('t')\n",
    "    plt.ylabel('Witness')\n",
    "    fig_idx += 1\n",
    "    plt.grid()\n",
    "plt.legend();"
   ]
  }
 ],
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  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3.8.5 64-bit ('oqs-jupyterbook-_Llz9vLR-py3.8': venv)"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  },
  "interpreter": {
   "hash": "a183628b7c25cbe14b32706b25a1d360b2cc05412b0aa00bca3856a97dc6cea8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}