QAOA_2Qubit_EXPERIMENT.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import time\n",
    "from collections import namedtuple\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import qiskit as q\n",
    "import qiskit.tools.jupyter\n",
    "from qiskit.pulse import pulse_lib as _  # only want to call pulse_lib as q.pulse.pulse_lib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pulse_compiler_helper_fns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AccountProvider for IBMQ(hub='ibm-q', group='open', project='main')>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q.IBMQ.load_account() # Load account from disk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/alijavadi/Desktop/ajavadia-terra/qiskit/pulse/channels/pulse_channel_spec.py:87: DeprecationWarning: The PulseChannelSpec is deprecated. Use backend.configuration() instead. The supported methods require some migrations; check out the release notes for the complete details.\n",
      "  DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "provider = q.IBMQ.get_provider(group='qiskit-terra', project='pulse-testing')\n",
    "backend = provider.get_backend('alt_almaden')\n",
    "system = q.pulse.PulseChannelSpec.from_backend(backend)\n",
    "config = backend.configuration()\n",
    "cmd_def = q.pulse.CmdDef.from_defaults(backend.defaults().cmd_def, backend.defaults().pulse_library)\n",
    "measure = cmd_def.get('measure', qubits=backend.configuration().meas_map[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "beta = 3 * np.pi / 4\n",
    "gamma = np.pi / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "schedules = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "HH = cmd_def.get('u2', qubits=[0], P0=0, P1=np.pi) | cmd_def.get('u2', qubits=[1], P0=0, P1=np.pi)\n",
    "CNOT_RZ_CNOT = cmd_def.get('cx', qubits=[0, 1])\n",
    "CNOT_RZ_CNOT |= cmd_def.get('u1', qubits=[1], P0=gamma) << CNOT_RZ_CNOT.duration\n",
    "CNOT_RZ_CNOT |= cmd_def.get('cx', qubits=[0, 1]) << CNOT_RZ_CNOT.duration\n",
    "# RX(beta) = U3(beta, 3*pi/2, pi/2), hence line below\n",
    "RXRX = cmd_def.get('u3', qubits=[0], P0=beta, P1=3*np.pi/2, P2=np.pi/2) | cmd_def.get('u3', qubits=[1], P0=beta, P1=3*np.pi/2, P2=np.pi/2)\n",
    "\n",
    "schedule = HH\n",
    "schedule |= CNOT_RZ_CNOT << schedule.duration\n",
    "schedule |= RXRX << schedule.duration\n",
    "schedule |= measure << schedule.duration\n",
    "\n",
    "schedules.append(schedule)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Optimized Way: zz_interaction decomposes directly to cross resonancefor theta in thetas:\n",
    "circuit = q.QuantumCircuit(2)\n",
    "circuit.h(0)\n",
    "circuit.h(1)\n",
    "circuit.zz_interaction(gamma, 0, 1)\n",
    "circuit.rx(beta, 0)\n",
    "circuit.rx(beta, 1)\n",
    "\n",
    "decomposed_circuit = circuit.decompose()\n",
    "\n",
    "pulse_compiler_helper_fns.update_basis_gates_and_cmd_def(decomposed_circuit, backend, system, cmd_def)\n",
    "transpiled_circuit = q.transpile(decomposed_circuit, backend, optimization_level=1)\n",
    "\n",
    "schedule = q.schedule(transpiled_circuit, backend=backend, cmd_def=cmd_def)\n",
    "schedule |= measure << schedule.duration\n",
    "schedules.append(schedule)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/alijavadi/Desktop/ajavadia-terra/qiskit/providers/models/backendconfiguration.py:399: UserWarning: The control channel appropriate for an interaction should be determined from the hamiltonian. This will be determined for you in the future.\n",
      "  warnings.warn(\"The control channel appropriate for an interaction should be determined \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x864 with 2 Axes>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "schedules[0].draw(channels=[config.drive(0), config.drive(1), config.control(0)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x864 with 2 Axes>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "schedules[1].draw(channels=[config.drive(0), config.drive(1), config.control(0)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "job is 5dd99c272efcfc00184eb6f5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/ipywidgets/widgets/widget_layout.py:84: DeprecationWarning: Layout properties overflow_x and overflow_y have been deprecated and will be dropped in a future release. Please use the overflow shorthand property instead\n",
      "  warnings.warn(\"Layout properties overflow_x and overflow_y have been deprecated and will be dropped in a future release. Please use the overflow shorthand property instead\", DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "shots = 8000\n",
    "job = q.execute(schedules, backend=backend, shots=shots)\n",
    "print('job is %s' % job.job_id())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<JobStatus.VALIDATING: 'job is being validated'>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job.status()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run a mitigation cal job"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import qiskit.ignis.mitigation.measurement as mit\n",
    "meas_qcs, meas_labels = mit.complete_meas_cal(qubit_list=[0,1])\n",
    "meas_qcs_transpiled = q.transpile(meas_qcs, backend, basis_gates=['x'])\n",
    "meas_schedules = q.schedule(meas_qcs_transpiled, backend=backend, cmd_def=cmd_def)\n",
    "job_mit = q.execute(meas_schedules, backend)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<JobStatus.VALIDATING: 'job is being validated'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_mit.status()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-----\n",
    "## Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit.result import marginal_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "result = job.result()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.95410156, 0.08300781, 0.08300781, 0.0078125 ],\n",
       "       [0.02832031, 0.90039062, 0.00195312, 0.05371094],\n",
       "       [0.01660156, 0.00195312, 0.89257812, 0.09960938],\n",
       "       [0.00097656, 0.01464844, 0.02246094, 0.83886719]])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mitigate results\n",
    "result_mit = marginal_counts(job_mit.result(), [0,1])\n",
    "readout_fitter = mit.CompleteMeasFitter(result_mit, meas_labels)\n",
    "readout_fitter.cal_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before mitigation:\n",
      "{'00': 584, '01': 3958, '10': 3318, '11': 140}\n",
      "\n",
      "\n",
      "\n",
      " after mitigation:\n",
      "{'00': 9.306905529044516e-10, '01': 4340.499596429236, '10': 3659.5004035698817}\n"
     ]
    }
   ],
   "source": [
    "standard_counts = marginal_counts(result.get_counts(0), [0,1])\n",
    "print('before mitigation:')\n",
    "print(standard_counts)\n",
    "\n",
    "standard_counts = readout_fitter.filter.apply(standard_counts)\n",
    "print('\\n\\n\\n after mitigation:')\n",
    "print(standard_counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before mitigation:\n",
      "{'00': 543, '01': 3864, '10': 3473, '11': 120}\n",
      "\n",
      "\n",
      "\n",
      " after mitigation:\n",
      "{'00': 3.2117147307346117e-09, '01': 4201.575210406215, '10': 3798.4247895903336, '11': 2.401224165590816e-10}\n"
     ]
    }
   ],
   "source": [
    "optimized_counts = marginal_counts(result.get_counts(1), [0,1])\n",
    "print('before mitigation:')\n",
    "print(optimized_counts)\n",
    "\n",
    "optimized_counts = readout_fitter.filter.apply(optimized_counts)\n",
    "print('\\n\\n\\n after mitigation:')\n",
    "print(optimized_counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sanitize data and plot\n",
    "for key in standard_counts:\n",
    "    standard_counts[key] = int(standard_counts[key])\n",
    "for key in optimized_counts:\n",
    "    optimized_counts[key] = int(optimized_counts[key])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'00': 0, '01': 4340, '10': 3659, '11': 0}"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "standard_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'00': 0, '01': 4201, '10': 3798, '11': 0}"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "optimized_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram([standard_counts, optimized_counts], legend=['standard', 'optimized'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "ideal_counts = {'01': 4000, '10': 4000}\n",
    "standard_counts = {'00': 9.306905529044516e-10, '01': 4340.499596429236, '10': 3659.5004035698817}\n",
    "optimized_counts = {'00': 3.2117147307346117e-09, '01': 4201.575210406215, '10': 3798.4247895903336, '11': 2.401224165590816e-10}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.003636315014408073\n",
      "0.001271382715601354\n"
     ]
    }
   ],
   "source": [
    "print(pulse_compiler_helper_fns.kl_divergence(ideal_counts, standard_counts))\n",
    "print(pulse_compiler_helper_fns.kl_divergence(ideal_counts, optimized_counts))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6967834955743533\n",
      "0.6944185632755467\n"
     ]
    }
   ],
   "source": [
    "print(pulse_compiler_helper_fns.cross_entropy(ideal_counts, standard_counts))\n",
    "print(pulse_compiler_helper_fns.cross_entropy(ideal_counts, optimized_counts))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9698696167697216\n",
      "0.9821760223952822\n"
     ]
    }
   ],
   "source": [
    "print(q.quantum_info.hellinger_fidelity(ideal_counts, standard_counts))\n",
    "print(q.quantum_info.hellinger_fidelity(ideal_counts, optimized_counts))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}