{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PyOR also called Python On Resonance\n",
    "## Author: Vineeth Francis Thalakottoor\n",
    "## Email: vineeth.thalakottoor@ens.psl.eu or vineethfrancis.physics@gmail.com\n",
    "## Example: NOE (Hilbert space and Lindblad)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the source path\n",
    "SourcePath = '/media/HD2/Vineeth/PostDoc_Simulations/Github/PyOR_V1/PyOR_Combined/Source_Doc'\n",
    "\n",
    "# Add source path\n",
    "import sys\n",
    "sys.path.append(SourcePath)\n",
    "import time\n",
    "%matplotlib ipympl\n",
    "\n",
    "# Import PyOR package\n",
    "from PyOR_QuantumSystem import QuantumSystem as QunS\n",
    "from PyOR_Hamiltonian import Hamiltonian\n",
    "from PyOR_DensityMatrix import DensityMatrix\n",
    "from PyOR_QuantumObject import QunObj\n",
    "from PyOR_HardPulse import HardPulse\n",
    "from PyOR_Basis import Basis\n",
    "from PyOR_Evolution import Evolutions\n",
    "from PyOR_Plotting import Plotting\n",
    "import PyOR_SignalProcessing as Spro"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the spin system\n",
    "Spin_list = {\"A\" : \"H1\", \"B\" : \"H1\"}\n",
    "QS = QunS(Spin_list,PrintDefault=False)\n",
    "\n",
    "# initialize the system\n",
    "QS.Initialize()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rotating frame frequencies: {'A': -2514706800.0, 'B': -2514706800.0}\n",
      "Offset frequencies: {'A': 10.0, 'B': 50.0}\n",
      "Initial spin temperatures: {'A': 300.0, 'B': 300.0}\n",
      "Final spin temperatures: {'A': 300.0, 'B': 300.0}\n",
      "Radiation damping gain: {'A': 0, 'B': 0}\n",
      "Radiation damping phase: {'A': 0, 'B': 0}\n",
      "\n",
      "Rprocess = Auto-correlated Dipolar Homonuclear\n",
      "RelaxParDipole_tau = 1e-11\n",
      "DipolePairs = [('A', 'B')]\n",
      "RelaxParDipole_bIS = [30000.0]\n"
     ]
    }
   ],
   "source": [
    "# Master Equation\n",
    "QS.PropagationSpace = \"Hilbert\"\n",
    "QS.MasterEquation = \"Lindblad\"\n",
    "\n",
    "# B0 Field in Tesla, Static Magnetic field (B0) along Z\n",
    "QS.B0 = 9.4\n",
    "\n",
    "# Offset Frequency in rotating frame (Hz)\n",
    "QS.OFFSET[\"A\"] = 10.0\n",
    "QS.OFFSET[\"B\"] = 50.0\n",
    "\n",
    "# Define J coupling between Spins \n",
    "QS.JcoupleValue(\"A\",\"B\",5.0)\n",
    "\n",
    "# Define paris of spins coupled by dipolar interaction\n",
    "QS.Dipole_Pairs = [(\"A\",\"B\")]\n",
    "\n",
    "# Define initial and final Spin Temperature\n",
    "QS.I_spintemp[\"A\"] = 300.0\n",
    "QS.I_spintemp[\"B\"] = 300.0\n",
    "QS.F_spintemp[\"A\"] = 300.0\n",
    "QS.F_spintemp[\"B\"] = 300.0\n",
    "\n",
    "# Relaxation Process\n",
    "QS.Rprocess = \"Auto-correlated Dipolar Homonuclear\"\n",
    "QS.RelaxParDipole_tau = 10.0e-12\n",
    "QS.RelaxParDipole_bIS = [30.0e3]\n",
    "\n",
    "QS.Update()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generate Hamiltonians"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Larmor Frequency in MHz:  [-400.22802765 -400.22806765]\n"
     ]
    }
   ],
   "source": [
    "# generate Larmor Frequencies\n",
    "QS.print_Larmor = True\n",
    "Ham = Hamiltonian(QS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle \\left[\\begin{matrix}-30.0000000759161 & 0 & 0 & 0\\\\0 & 20.0000008601147 & 0 & 0\\\\0 & 0 & -20.0000008601147 & 0\\\\0 & 0 & 0 & 30.0000000759161\\end{matrix}\\right]$"
      ],
      "text/plain": [
       "Matrix([\n",
       "[-30.0000000759161,                0,                 0,                0],\n",
       "[                0, 20.0000008601147,                 0,                0],\n",
       "[                0,                0, -20.0000008601147,                0],\n",
       "[                0,                0,                 0, 30.0000000759161]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Hz = Ham.Zeeman_RotFrame()\n",
    "Hz.Inverse2PI().matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle \\left[\\begin{matrix}1.24999997786618 & 0 & 0 & 0\\\\0 & -1.24999997786618 & 2.49999995573235 & 0\\\\0 & 2.49999995573235 & -1.24999997786618 & 0\\\\0 & 0 & 0 & 1.24999997786618\\end{matrix}\\right]$"
      ],
      "text/plain": [
       "Matrix([\n",
       "[1.24999997786618,                 0,                 0,                0],\n",
       "[               0, -1.24999997786618,  2.49999995573235,                0],\n",
       "[               0,  2.49999995573235, -1.24999997786618,                0],\n",
       "[               0,                 0,                 0, 1.24999997786618]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# J coupling Hamiltonian\n",
    "Hj = Ham.Jcoupling()\n",
    "Hj.Inverse2PI().matrix"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### product operator basis (Shift Z or PMZ basis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "BS = Basis(QS)\n",
    "\n",
    "sort = 'negative to positive'\n",
    "Index = False\n",
    "Normal = True\n",
    "Basis_PMZ, coh_PMZ, dic_PMZ = BS.ProductOperators_SpinHalf_PMZ(sort,Index,Normal)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Initialize Density Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Trace of density matrix =  1.0\n",
      "Trace of density matrix =  1.0\n"
     ]
    }
   ],
   "source": [
    "DM = DensityMatrix(QS,Ham)\n",
    "\n",
    "Thermal_DensMatrix = True\n",
    "\n",
    "if Thermal_DensMatrix:    \n",
    "    # High Temperature\n",
    "    HT_approx = False\n",
    "    \n",
    "    # Initial Density Matrix\n",
    "    rho_in = DM.EquilibriumDensityMatrix(QS.Ispintemp,HT_approx)\n",
    "    \n",
    "    # Equlibrium Density Matrix\n",
    "    rhoeq = DM.EquilibriumDensityMatrix(QS.Fspintemp,HT_approx)\n",
    "else:\n",
    "    rho_in = QS.Az + QS.Bz\n",
    "    rhoeq = QS.Az + QS.Bz "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Density Matrix = 2e-05 Iz1 Id2  + 2e-05 Id1 Iz2  + 0.5 Id1 Id2 \n"
     ]
    }
   ],
   "source": [
    "DM.DensityMatrix_Components(Basis_PMZ,dic_PMZ,rho_in)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pulse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "HardP = HardPulse(QS)\n",
    "\n",
    "flip_angle1 = 0.0   # Flip angle Spin 1\n",
    "flip_angle2 = 180.0 # Flip angle Spin 2\n",
    "\n",
    "rho = HardP.Rotate_Pulse(rho_in,flip_angle1,QS.Ay)\n",
    "rho = HardP.Rotate_Pulse(rho,flip_angle2,QS.By) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Density Matrix = 2e-05 Iz1 Id2  + -2e-05 Id1 Iz2  + 0.5 Id1 Id2 \n"
     ]
    }
   ],
   "source": [
    "DM.DensityMatrix_Components(Basis_PMZ,dic_PMZ,rho)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evolution "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Larmor Frequency in MHz:  [-400.22802765 -400.22806765]\n",
      "Total time = 17.052765607833862 seconds \n"
     ]
    }
   ],
   "source": [
    "QS.AcqDT = 0.0001\n",
    "QS.AcqAQ = 30.0\n",
    "QS.OdeMethod = 'DOP853'\n",
    "QS.PropagationMethod = \"ODE Solver Lindblad\"\n",
    "\n",
    "EVol = Evolutions(QS,Ham)\n",
    "\n",
    "start_time = time.time()\n",
    "t, rho_t = EVol.Evolution(rho,rhoeq,Hz+Hj)\n",
    "end_time = time.time()\n",
    "timetaken = end_time - start_time\n",
    "print(\"Total time = %s seconds \" % (timetaken))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Expectation Value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "det_Z1 = QS.Az\n",
    "det_Z2 = QS.Bz\n",
    "\n",
    "t, signal_Z1 = EVol.Expectation(rho_t,det_Z1)\n",
    "t, signal_Z2 = EVol.Expectation(rho_t,det_Z2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.12/site-packages/matplotlib/cbook.py:1762: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  return math.isfinite(val)\n",
      "/opt/anaconda3/lib/python3.12/site-packages/matplotlib/cbook.py:1398: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  return np.asarray(x, float)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1f4e17ca914f41abad2af54a05aa891c",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=1000.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot = Plotting(QS)\n",
    "plot.PlotFigureSize = (10,5)\n",
    "plot.PlotFontSize = 20\n",
    "plot.PlottingMulti(1,[t,t],[signal_Z1,signal_Z2],\"time (s)\",\"Mz\",[\"green\",\"blue\"])"
   ]
  }
 ],
 "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": "3.12.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}