QCFD_Examples.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Examples: [I will keep updating the file with more examples]\n",
    "Examples are taken from "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[https://github.com/Qiskit/textbook/blob/main/notebooks/ch-applications/hhl_tutorial.ipynb] "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[https://medium.com/mit-6-s089-intro-to-quantum-computing/hhl-algorithm-solving-systems-of-linear-equations-e4d82d340951]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from qiskit.algorithms import NumPyLinearSolver\n",
    "from qiskit.quantum_info import state_fidelity\n",
    "from scipy.sparse import diags\n",
    "from QCFD import QCFD\n",
    "\n",
    "def Fidelity(QSol_SV, CSol_SV):\n",
    "    QSol_Norm = QSol_SV / np.linalg.norm(QSol_SV)\n",
    "    CSol_Norm = CSol_SV / np.linalg.norm(CSol_SV)\n",
    "    fidelity = state_fidelity(QSol_Norm, CSol_Norm)\n",
    "    print(\"fidelity %f\" % fidelity)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Example 1:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╭────────────┬─────────────┬───────────┬────────────────┬─────────┬─────────┬────────────────╮\n",
      "│   DYNEXJOB │   BLOCK FEE │   ELAPSED │   WORKERS READ │   CHIPS │   STEPS │   GROUND STATE │\n",
      "├────────────┼─────────────┼───────────┼────────────────┼─────────┼─────────┼────────────────┤\n",
      "│       1050 │        0.08 │      1.48 │              2 │    1984 │     200 │       86699.00 │\n",
      "╰────────────┴─────────────┴───────────┴────────────────┴─────────┴─────────┴────────────────╯\n",
      "╭────────────┬─────────────────┬─────────┬───────┬──────────┬──────────────┬─────────────────────────────┬───────────┬──────────╮\n",
      "│     WORKER │         VERSION │   CHIPS │   LOC │   ENERGY │      RUNTIME │                 LAST UPDATE │     STEPS │   STATUS │\n",
      "├────────────┼─────────────────┼─────────┼───────┼──────────┼──────────────┼─────────────────────────────┼───────────┼──────────┤\n",
      "│ dcfd..7dbe │ 2.3.5.OZM.127.L │     992 │    47 │ 86699.00 │ 8.635553367s │ 2023-12-26T08:16:23.791616Z │ 0 (0.00%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "╰────────────┴─────────────────┴─────────┴───────┴──────────┴──────────────┴─────────────────────────────┴───────────┴──────────╯\n",
      "[DYNEX] FINISHED READ AFTER 1.48 SECONDS\n",
      "[DYNEX] SAMPLESET READY\n",
      "[2. 1.]\n",
      "------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "Classical solution: \n",
      "[1.125 0.375]\n",
      "------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "fidelity 0.980000\n"
     ]
    }
   ],
   "source": [
    "matrix = np.array([[1, -1/3], [-1/3, 1]])\n",
    "vector = np.array([1, 0])\n",
    "qcfd = QCFD()\n",
    "#print(\"Q :\", qcfd.Lin2QUBO(matrix,vector))\n",
    "print(\"Quantum Solution:\")\n",
    "sol = qcfd.compute(matrix, vector, compute='dynex')\n",
    "print(\"-\"*150)\n",
    "NPLinear = NumPyLinearSolver()\n",
    "classicRes = NPLinear.solve(matrix, vector)\n",
    "CSol = classicRes.state\n",
    "CSol_SV = np.maximum(np.round(CSol, 5), 0)\n",
    "print(\"Classical solution: \")\n",
    "print(CSol_SV)\n",
    "print(\"-\"*150)\n",
    "Fidelity(sol,CSol_SV)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Example 2:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╭────────────┬─────────────┬───────────┬────────────────┬─────────┬─────────┬────────────────╮\n",
      "│   DYNEXJOB │   BLOCK FEE │   ELAPSED │   WORKERS READ │   CHIPS │   STEPS │   GROUND STATE │\n",
      "├────────────┼─────────────┼───────────┼────────────────┼─────────┼─────────┼────────────────┤\n",
      "│       1052 │        0.08 │      1.50 │              1 │     992 │     200 │      130043.00 │\n",
      "╰────────────┴─────────────┴───────────┴────────────────┴─────────┴─────────┴────────────────╯\n",
      "╭────────────┬─────────────────┬─────────┬───────┬───────────┬───────────────┬─────────────────────────────┬───────────┬──────────╮\n",
      "│     WORKER │         VERSION │   CHIPS │   LOC │    ENERGY │       RUNTIME │                 LAST UPDATE │     STEPS │   STATUS │\n",
      "├────────────┼─────────────────┼─────────┼───────┼───────────┼───────────────┼─────────────────────────────┼───────────┼──────────┤\n",
      "│ 2b2f..4ccd │ 2.3.5.OZM.128.L │     992 │    47 │ 130043.00 │  5.220600227s │ 2023-12-26T08:18:08.178657Z │ 0 (0.00%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼───────┼───────────┼───────────────┼─────────────────────────────┼───────────┼──────────┤\n",
      "│ de22..96cb │ 2.3.5.OZM.127.L │     992 │    45 │ 130043.00 │  9.744376675s │ 2023-12-26T08:18:03.654882Z │ 0 (0.00%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼───────┼───────────┼───────────────┼─────────────────────────────┼───────────┼──────────┤\n",
      "│ cb87..7b46 │ 2.3.5.OZM.127.L │     992 │    -1 │     -1.00 │ 10.282641402s │ 2023-12-26T08:18:03.116618Z │ 0 (0.00%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "╰────────────┴─────────────────┴─────────┴───────┴───────────┴───────────────┴─────────────────────────────┴───────────┴──────────╯\n",
      "[DYNEX] FINISHED READ AFTER 1.50 SECONDS\n",
      "[DYNEX] SAMPLESET READY\n",
      "[6. 5.]\n",
      "------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "Classical solution: \n",
      "[3. 2.]\n",
      "------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "fidelity 0.988651\n"
     ]
    }
   ],
   "source": [
    "matrix = np.array([[1, -1/2], [-1/2, 1]])\n",
    "vector = np.array([2, 1/2])\n",
    "qcfd = QCFD()\n",
    "#print(\"Q :\", qcfd.Lin2QUBO(matrix,vector))\n",
    "print(\"Quantum Solution:\")\n",
    "sol = qcfd.compute(matrix, vector, compute='dynex')\n",
    "print(\"-\"*150)\n",
    "NPLinear = NumPyLinearSolver()\n",
    "classicRes = NPLinear.solve(matrix, vector)\n",
    "CSol = classicRes.state\n",
    "CSol_SV = np.maximum(np.round(CSol, 5), 0)\n",
    "print(\"Classical solution: \")\n",
    "print(CSol_SV)\n",
    "print(\"-\"*150)\n",
    "Fidelity(sol,CSol_SV)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Example 3:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Quantum Solution:\n",
      "[1. 1. 1. 1.]\n",
      "------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "Classical solution: \n",
      "[5. 5. 5. 5.]\n",
      "------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "fidelity 1.000000\n"
     ]
    }
   ],
   "source": [
    "matrix = np.array([[4, -1, -1, 0],\n",
    "              [-1, 4, 0, -1],\n",
    "              [-1, 0, 4, -1],\n",
    "              [0, -1, -1, 4]])\n",
    "vector = np.array([10, 10, 10, 10])\n",
    "\n",
    "print(\"Quantum Solution:\")\n",
    "qcfd = QCFD()\n",
    "sol = qcfd.compute(matrix, vector, compute='local')\n",
    "print(\"-\"*150)\n",
    "NPLinear = NumPyLinearSolver()\n",
    "classicRes = NPLinear.solve(matrix, vector)\n",
    "CSol = classicRes.state\n",
    "CSol_SV = np.maximum(np.round(CSol, 5), 0)\n",
    "print(\"Classical solution: \")\n",
    "print(CSol_SV)\n",
    "print(\"-\"*150)\n",
    "Fidelity(sol,CSol_SV)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Example 4: (advanced)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This example is taken from SimScale (Cloud-based CFD Computing), the project is based on simulating airflow through superstream EVO (car) to analyze the structure of the design related to the Air. The initial conditions are ([U]Velocity, [k]Kinetic Energy, [P]Pressure, [A]Air-flow)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This example was exported to OpenFOAM (Open-source CFD) to extract all the parameters and conditions then exported to MATLAB to calculate the linear Matrix and Vector (There is no straightforwad export method).\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Dynex solution has been exported back to MATLAB to reflect the solution on the parameters and conditions then converted to OpenFOAM and finally rendered in SimScale (post-processing) [See \"imgs\" folder]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╭────────────┬─────────────┬───────────┬────────────────┬─────────┬─────────┬────────────────╮\n",
      "│   DYNEXJOB │   BLOCK FEE │   ELAPSED │   WORKERS READ │   CHIPS │   STEPS │   GROUND STATE │\n",
      "├────────────┼─────────────┼───────────┼────────────────┼─────────┼─────────┼────────────────┤\n",
      "│       1086 │       72.62 │      4.97 │              2 │    1984 │     500 │   835048345.00 │\n",
      "╰────────────┴─────────────┴───────────┴────────────────┴─────────┴─────────┴────────────────╯\n",
      "╭────────────┬─────────────────┬─────────┬────────┬──────────────┬───────────────┬─────────────────────────────┬──────────────┬──────────╮\n",
      "│     WORKER │         VERSION │   CHIPS │    LOC │       ENERGY │       RUNTIME │                 LAST UPDATE │        STEPS │   STATUS │\n",
      "├────────────┼─────────────────┼─────────┼────────┼──────────────┼───────────────┼─────────────────────────────┼──────────────┼──────────┤\n",
      "│ 8392..fdad │ 2.3.5.OZM.126.W │     992 │      0 │         0.00 │   50.2676046s │ 2023-12-27T09:30:17.744922Z │    0 (0.00%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼────────┼──────────────┼───────────────┼─────────────────────────────┼──────────────┼──────────┤\n",
      "│ 33a3..a2b7 │ 2.3.5.BZM.v19.0 │     992 │ 233288 │         0.00 │  9.949531386s │ 2023-12-27T09:30:58.062997Z │ 296 (59.20%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼────────┼──────────────┼───────────────┼─────────────────────────────┼──────────────┼──────────┤\n",
      "│ 67a6..6e6e │ 2.3.5.OZM.127.W │     992 │  55693 │ 834984070.00 │  3.628573092s │ 2023-12-27T09:31:04.383956Z │ 284 (56.80%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼────────┼──────────────┼───────────────┼─────────────────────────────┼──────────────┼──────────┤\n",
      "│ 5ed8..bc65 │ 2.3.5.OZM.127.L │     992 │  55824 │ 835028783.00 │  2.656496688s │ 2023-12-27T09:31:05.356033Z │    0 (0.00%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼────────┼──────────────┼───────────────┼─────────────────────────────┼──────────────┼──────────┤\n",
      "│ afbd..f9bb │ 2.3.5.OZM.127.W │     992 │  55808 │ 835029233.00 │  7.844706453s │ 2023-12-27T09:31:00.167825Z │ 265 (53.00%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼────────┼──────────────┼───────────────┼─────────────────────────────┼──────────────┼──────────┤\n",
      "│ cd96..c01f │ 2.3.5.OZM.127.W │     992 │  55735 │ 835046706.00 │  5.734875082s │ 2023-12-27T09:31:02.277657Z │ 242 (48.40%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼────────┼──────────────┼───────────────┼─────────────────────────────┼──────────────┼──────────┤\n",
      "│ ecaa..ceea │ 2.3.5.OZM.128.L │     992 │  55820 │ 835048345.00 │   9.24855972s │ 2023-12-27T09:30:58.763973Z │    0 (0.00%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼────────┼──────────────┼───────────────┼─────────────────────────────┼──────────────┼──────────┤\n",
      "│ cbea..ae02 │ 2.3.5.OZM.127.W │     992 │  55799 │ 835051908.00 │  7.844708306s │ 2023-12-27T09:31:00.167825Z │ 235 (47.00%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼────────┼──────────────┼───────────────┼─────────────────────────────┼──────────────┼──────────┤\n",
      "│ fc70..840a │ 2.3.5.OZM.127.W │     992 │  55756 │ 835059651.00 │  3.628578017s │ 2023-12-27T09:31:04.383956Z │    0 (0.00%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼────────┼──────────────┼───────────────┼─────────────────────────────┼──────────────┼──────────┤\n",
      "│ 7f8c..fdb1 │ 2.3.5.OZM.127.W │     992 │  55711 │ 835096236.00 │  5.734877579s │ 2023-12-27T09:31:02.277657Z │ 245 (49.00%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼────────┼──────────────┼───────────────┼─────────────────────────────┼──────────────┼──────────┤\n",
      "│ cb99..72d9 │ 2.3.5.OZM.127.W │     992 │  55709 │ 835097086.00 │  1.318683293s │ 2023-12-27T09:31:06.693852Z │    0 (0.00%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼────────┼──────────────┼───────────────┼─────────────────────────────┼──────────────┼──────────┤\n",
      "│ b8a1..0022 │ 2.3.5.OZM.127.W │     992 │  55799 │ 835106757.00 │  5.734878911s │ 2023-12-27T09:31:02.277657Z │ 239 (47.80%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼────────┼──────────────┼───────────────┼─────────────────────────────┼──────────────┼──────────┤\n",
      "│ 4683..ca46 │ 2.3.5.OZM.127.W │     992 │  55805 │ 835119945.00 │ 14.761312576s │ 2023-12-27T09:30:53.251224Z │ 198 (39.60%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼────────┼──────────────┼───────────────┼─────────────────────────────┼──────────────┼──────────┤\n",
      "│ 03ae..8014 │ 2.3.5.OZM.127.W │     992 │  55799 │ 835168052.00 │  3.628581183s │ 2023-12-27T09:31:04.383956Z │    0 (0.00%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "├────────────┼─────────────────┼─────────┼────────┼──────────────┼───────────────┼─────────────────────────────┼──────────────┼──────────┤\n",
      "│ 8bd1..de2b │ 2.3.5.OZM.127.W │     992 │  55792 │ 835174100.00 │  9.949542146s │ 2023-12-27T09:30:58.062997Z │ 200 (40.00%) │  \u001b[1;31mSTOPPED\u001b[0m │\n",
      "╰────────────┴─────────────────┴─────────┴────────┴──────────────┴───────────────┴─────────────────────────────┴──────────────┴──────────╯\n",
      "[DYNEX] FINISHED READ AFTER 4.97 SECONDS\n",
      "[DYNEX] SAMPLESET READY\n",
      "[57. 61.  6.  1.  4. 62. 50. 10. 55. 55. 20.  8. 59. 62. 63. 25. 57.  3.\n",
      " 56.  2. 55.  6.  3. 27. 59.  4. 14. 62. 61. 15. 62. 62. 62.  6. 52. 10.\n",
      " 15. 58. 12. 57. 56. 15.  0. 56. 55. 26. 13. 60. 29. 21. 15.  0. 58. 53.\n",
      " 63. 50. 62. 51. 54.  5. 60.  2. 52. 51. 15. 50. 59. 15. 18. 13. 63. 13.\n",
      " 51. 51. 20. 11.  4. 53. 55. 23. 57.  7. 20.  7. 62.  3. 54. 29.  9.  7.\n",
      "  7. 27.  4.  2.  1. 53. 57. 16. 58. 49. 61. 30. 14. 54. 62. 57. 60. 11.\n",
      "  9.  4.  9. 61.  0. 57. 63. 13.  2.  6.  3.  3.  2.  2.  3. 62.  5. 61.\n",
      "  9. 53. 63.  9. 18. 20.  7. 59. 62.  6. 63. 10. 60. 63.  7. 51.  4. 59.\n",
      " 62. 17. 62.  0.  3. 59. 16. 60. 23. 12. 62.  7. 59. 58. 57. 59.  4. 62.\n",
      "  8. 23. 19.  7. 60. 23. 58. 62. 62. 29. 63. 14.  6.  0.  2.  9. 49.  7.\n",
      " 63.  2. 19. 61. 63. 62. 53. 55. 63. 26. 62. 56. 61. 14. 29. 62. 10. 12.\n",
      " 58. 61. 60. 57. 14. 57. 23. 14. 16. 62. 29. 56. 15. 50. 48.  9.  5. 55.\n",
      " 50. 49. 59. 56. 59. 11. 62. 31. 61. 20. 62. 23. 55. 62. 16. 56. 57. 59.\n",
      " 56. 62.  2.  3. 55. 57. 10. 49.  6.  6. 54. 14. 59. 55. 60. 18. 31. 12.\n",
      " 10. 58. 57. 62. 11. 10.  4. 29. 60. 11.  6. 59. 59. 51.  5. 59. 62. 62.\n",
      " 60. 57.  7. 59. 21. 58. 18. 60. 63.  7. 62.  5.  9.  7.  2. 28. 54.  4.\n",
      " 58. 11. 11. 55. 58. 58. 28. 62. 49. 27. 61. 60. 49. 31.  3. 63.  8. 55.\n",
      " 59.  9. 12. 62. 60. 62. 56. 60. 13. 24. 12. 49. 23. 12. 12. 58.  2. 63.\n",
      "  8. 13. 49. 62. 54. 60. 55. 12. 49. 22. 12. 56.  9. 62. 51. 52. 32. 50.\n",
      " 28. 18. 59. 51. 28. 23.  6.  8. 52. 12. 60. 57. 62. 31. 15. 14. 30. 15.\n",
      " 63. 17. 61. 56.  8. 28. 55. 24. 62. 53.  3.  1. 57. 62. 58. 62. 61. 57.\n",
      "  4. 63. 59. 57. 21. 52. 54. 58.  3. 16. 49. 20. 52. 55.  5.  8. 60. 56.\n",
      "  4. 60. 59.  0. 22.  9. 56. 62.  7. 56. 57. 62.  7. 58. 13. 54. 22. 61.\n",
      "  8. 12. 13. 60. 18. 57. 15.  6. 59.  5. 63. 58.  2. 50.  9. 60. 30.  5.\n",
      " 57. 63.  6. 59. 62. 61. 13. 58. 51. 28. 54. 22. 19. 54. 46. 62. 17. 11.\n",
      " 16. 17.  0. 23.  9. 52. 57. 57. 13. 10. 10. 27. 54. 12.  1. 61. 58. 48.\n",
      " 22.  1. 22.  1. 63. 54. 57. 61. 15. 19. 49. 53. 56.  5. 63.  3. 54. 12.\n",
      " 23.  2. 31. 60. 50.  1.  7. 63. 60. 61. 55. 63. 57.  3. 58. 50. 14. 57.\n",
      " 62. 54. 30. 57.  5. 62.  6. 30. 60. 55. 62.  3. 61. 63. 53.  4. 12. 60.\n",
      " 56. 26. 61. 58. 13. 50. 56. 61.  2. 27. 13. 31. 11. 21.  0. 54. 54. 21.\n",
      " 11.  8. 56. 62.  5. 30. 62. 62. 13.  5.  3. 62. 11. 61.  5. 11. 52. 17.\n",
      " 11.  7. 56. 26. 15.  6. 25. 20. 11. 63. 61. 17. 20. 10. 56. 50. 61. 26.\n",
      "  0. 13. 14. 26. 61. 19. 17. 63.  2. 60. 60. 60. 59. 62. 60. 31. 51. 12.\n",
      " 29. 62. 17. 21. 49. 19. 59. 60. 53. 61. 16.  5.  4. 52. 24. 19. 15. 25.\n",
      " 29. 12. 16. 13. 27. 54. 59. 56.  6. 25. 58. 59. 63. 62. 61. 59. 57. 16.\n",
      " 59. 27. 23.  1. 11. 10. 60. 14.  8. 63. 59. 62. 60. 57. 62. 12. 19. 61.\n",
      " 63.  5. 50. 60.  0.  8.  6. 14. 59. 61.  7. 62. 27. 27. 52. 61. 58. 58.\n",
      " 11. 51. 62.  2.  4. 48. 17. 51. 51. 14. 59.  0. 50. 29.  7. 19.  2.  8.\n",
      " 63. 12. 57. 62. 63. 63. 51.  3. 10. 31.  4. 62.  9.  7. 14. 19. 23. 54.\n",
      " 29. 29. 12. 63.  8. 48. 22. 56. 52.  2. 62. 60. 63. 59.  6. 62. 10.  8.\n",
      " 57. 61.  0. 48. 18. 53. 14. 23. 60. 55. 51.  3. 20. 62. 15. 15. 29. 58.\n",
      " 54. 19. 52. 23. 53. 10.  7.  7.  7. 16.  6.  6. 15.  6. 62. 56.  0.  3.\n",
      " 62.  1.  3. 11. 12. 49. 26.  2. 52.  7. 56. 25. 57. 56. 49. 63. 52. 63.\n",
      " 55. 63. 59.  9. 54. 62. 19. 52. 57.  1. 13. 12. 53.  5. 18. 52.  0. 61.\n",
      " 61. 54.  5. 58.  7. 63. 61. 21.]\n",
      "------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "Classical solution: \n",
      "[136.09 144.36  41.35  21.02  42.75 149.98 157.18  78.73 157.74 152.22\n",
      "  51.14  52.34 158.21 180.51 163.84  74.83 135.48  67.09 132.89  64.48\n",
      " 125.02  35.61  17.43  34.1  118.99  41.84  48.37 151.63 158.16  81.01\n",
      " 165.86 182.45 163.92  73.24 129.06  42.98  42.86 128.47  71.03 155.63\n",
      " 151.51  50.39  50.06 149.87 149.4   47.74  41.57 118.52  32.51  11.53\n",
      "  13.6   42.87 157.89 188.67 196.81 198.55 197.4  191.04 166.78  76.07\n",
      " 137.51  73.96 158.33 159.37  79.16 157.27 149.92  42.42  19.76  36.63\n",
      " 126.77  70.43 154.96 149.41  42.69  21.34  42.69 149.41 154.95  70.4\n",
      " 126.63  36.14  17.93  35.59 124.41  62.05 123.81  33.18   8.9    2.44\n",
      "   0.84   0.94   2.92  10.74  40.03 149.39 157.53  80.74 165.43 180.98\n",
      " 158.47  52.92  53.21 159.92 186.45 185.9  157.15  42.71  13.69  12.07\n",
      "  34.57 126.2   70.23 154.72 148.64  39.83  10.68   2.91   0.94   0.85\n",
      "   2.45   8.95  33.37 124.52  64.7  134.28  72.41 155.35 149.    40.64\n",
      "  13.55  13.55  40.65 149.04 155.52  73.05 136.67  73.64 157.88 157.89\n",
      "  73.68 136.83  73.64 157.74 157.3   71.46 128.54  42.7   42.27 126.36\n",
      "  63.18 126.37  42.31  42.86 129.13  73.67 165.54 188.5  188.47 165.39\n",
      "  73.08 126.92  34.61  11.54  11.53  34.58 126.79  72.6  163.6  181.8\n",
      " 163.59  72.56 126.67  34.1    9.73   4.82   9.55  33.39 124.03  62.71\n",
      " 126.8   44.48  51.14 160.07 189.15 196.54 197.   191.45 168.8   83.75\n",
      " 166.19 180.99 157.79  50.18  42.92 121.48  43.02  50.6  159.36 186.85\n",
      " 188.04 165.3   73.17 127.38  36.36  18.04  35.8  125.17  64.89 134.38\n",
      "  72.62 156.11 151.83  51.19  52.94 160.55 189.27 196.53 196.85 190.87\n",
      " 166.61  75.59 135.73  67.34 133.63  67.19 135.14  73.38 158.37 160.11\n",
      "  82.08 168.22 190.78 194.9  188.83 160.43  52.9   51.15 151.71 155.69\n",
      "  71.04 128.48  42.86  42.97 129.    73.05 163.18 179.68 155.52  42.41\n",
      "  14.13  14.1   42.26 154.93 177.45 154.88  42.07  13.39  11.48  32.54\n",
      " 118.68  42.16  49.98 157.74 180.98 166.17  83.71 168.68 191.01 195.37\n",
      " 190.47 166.52  75.59 135.84  67.77 135.24  73.21 157.58 157.1   70.83\n",
      " 126.2   33.97   9.7    4.81   9.55  33.39 124.02  62.69 126.75  44.32\n",
      "  50.54 157.85 180.86 165.6   81.53 160.51 160.51  81.53 165.6  180.87\n",
      " 157.9   50.71  44.93 129.03  71.19 155.73 151.72  51.15  52.88 160.38\n",
      " 188.64 194.18 188.08 158.13  44.44  19.65  34.14 116.92  33.54  17.25\n",
      "  35.46 124.58  62.85 126.83  44.49  51.11 159.94 188.66 194.71 190.18\n",
      " 165.99  73.8  129.22  43.07  43.07 129.22  73.8  166.   190.18 194.74\n",
      " 188.78 160.38  52.73  50.56 149.49 147.4   40.1   13.01  11.92  34.68\n",
      " 126.78  72.45 163.01 179.59 155.34  41.79  11.8    5.41   9.85  33.98\n",
      " 126.09  70.36 155.35 151.06  48.88  44.44 128.9   71.15 155.72 151.72\n",
      "  51.16  52.93 160.55 189.28 196.57 197.01 191.46 168.84  83.92 166.82\n",
      " 183.36 166.63  83.17 166.04 180.99 157.93  50.72  44.94 129.03  71.18\n",
      " 155.68 151.56  50.56  50.66 152.09 157.7   78.72 157.18 150.01  42.86\n",
      "  21.44  42.9  150.17 157.77  80.91 165.87 182.56 164.38  74.98 135.52\n",
      "  67.1  132.9   64.49 125.05  35.72  17.83  35.6  124.58  62.7  126.23\n",
      "  42.23  42.69 128.53  71.45 157.26 157.58  73.05 134.64  65.51 127.4\n",
      "  44.09  48.97 151.8  158.21  81.06 166.02 183.04 166.13  81.5  159.85\n",
      " 157.9   71.77 129.17  44.92  50.51 157.13 178.   154.88  41.51  11.18\n",
      "   3.19   1.6    3.19  11.17  41.47 154.72 177.4  154.86  42.06  13.39\n",
      "  11.48  32.54 118.66  42.11  49.76 156.94 178.   155.08  42.3   14.14\n",
      "  14.25  42.86 157.19 185.91 186.46 159.91  53.2   52.89 158.36 180.54\n",
      " 163.8   74.68 134.9   64.91 124.76  34.13  11.78  12.97  40.09 147.4\n",
      " 149.49  50.56  52.77 160.51 189.27 196.56 196.98 191.35 168.41  82.28\n",
      " 160.72 160.6   81.67 166.07 182.61 164.37  74.88 135.14  65.67 127.55\n",
      "  44.54  50.61 157.9  180.97 165.99  83.01 166.03 181.1  158.37  52.38\n",
      "  51.16 152.28 157.94  79.47 159.96 160.35  81.44 165.42 180.22 155.47\n",
      "  41.67  11.22   3.19   1.56   3.04  10.58  39.3  146.62 147.17  42.06\n",
      "  21.08  42.25 147.92 149.43  49.81  49.8  149.4  147.8   41.82  19.46\n",
      "  36.04 124.68  62.68 126.05  41.51  39.99 118.45  33.8   16.75  33.21\n",
      " 116.09  31.16   8.54   2.99   3.42  10.69  39.33 146.64 147.21  42.21\n",
      "  21.62  44.27 155.46 177.56 154.8   41.63  11.72   5.25   9.26  31.81\n",
      " 117.97  40.06  42.27 129.01  73.79 166.14 190.76 196.92 196.92 190.77\n",
      " 166.14  73.8  129.06  42.44  40.7  120.35  40.69  42.42 129.01  73.6\n",
      " 165.39 187.95 186.41 157.68  44.31  19.57  33.96 116.28  31.16   8.35\n",
      "   2.25   0.66   0.37   0.84   2.99  11.13  41.51 154.92 178.16 157.73\n",
      "  52.78  53.37 160.7  189.43 197.   198.59 197.36 190.84 166.01  73.21\n",
      " 126.84  34.14   9.71   4.72   9.16  31.93 118.55  42.27  50.54 159.9\n",
      " 189.07 196.37 196.4  189.24 160.55  52.96  51.31 152.26 157.74  78.69\n",
      " 157.04 149.45  40.76  13.58  13.55  40.61 148.9  154.97  71.   129.01\n",
      "  45.04  51.15 159.55 187.05 188.64 167.53  81.46 158.33 151.86  49.1\n",
      "  44.53 129.03  71.58 157.29 157.57  73.   134.44  64.75 124.57  33.54\n",
      "   9.59   4.83   9.74  34.14 126.83  73.16 165.81 190.09 194.54 188.06\n",
      " 157.72  42.81  13.53  11.32  31.76 115.73  31.16   8.9    4.46   8.93\n",
      "  31.27 116.15  33.35  17.23  35.59 125.13  64.91 134.53  73.21 158.32\n",
      " 160.07  81.96 167.77 189.11 188.68 165.62  73.81 129.61  44.65  48.97\n",
      " 151.23 155.96  72.62 134.53  65.51 127.5   44.48  50.43 157.26 178.59\n",
      " 157.11  49.84  42.26 119.22  34.6   19.19  42.15 149.4  155.46  72.44\n",
      " 134.28  64.7  124.52  33.37   8.94   2.41   0.7    0.38   0.8    2.84\n",
      "  10.56  39.39 147.01 148.63  47.53  41.5  118.45  32.3   10.76  10.74\n",
      "  32.19 118.03  39.93  41.68 126.8   65.51 135.24  75.47 166.63 191.06\n",
      " 197.59 199.31 199.67 199.35 197.72 191.54 168.45  82.25 160.55 159.97\n",
      "  79.32 157.3  149.89  42.27  19.18  34.46 118.68  40.24  42.27 128.86\n",
      "  73.17 163.8  182.04 164.35  75.37 137.12  73.1  155.3  148.08  37.02]\n",
      "------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "fidelity 0.969376\n"
     ]
    }
   ],
   "source": [
    "SupercarCFD_M = 'advanced/matrix_exported.txt'\n",
    "SupercarCFD_V = 'advanced/vector_exported.txt'\n",
    "matrix = np.loadtxt(SupercarCFD_M)\n",
    "vector = np.loadtxt(SupercarCFD_V)\n",
    "\n",
    "print(\"Quantum Solution:\")\n",
    "qcfd = QCFD()\n",
    "sol = qcfd.compute(matrix, vector, compute='dynex', num_reads=1000, annealing_time=500)\n",
    "print(\"-\"*150)\n",
    "NPLinear = NumPyLinearSolver()\n",
    "classicRes = NPLinear.solve(matrix, vector)\n",
    "CSol = classicRes.state\n",
    "CSol_SV = np.maximum(np.round(CSol, 2), 0)\n",
    "print(\"Classical solution: \")\n",
    "print(CSol_SV)\n",
    "print(\"-\"*150)\n",
    "Fidelity(sol,CSol_SV)"
   ]
  }
 ],
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