{
 "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 (Liovillie space and Redfield)"
   ]
  },
  {
   "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/PyOR/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\n",
    "from PyOR_Commutators import Commutators\n",
    "from PyOR_QuantumLibrary import QuantumLibrary\n",
    "from PyOR_Relaxation import RelaxationProcess"
   ]
  },
  {
   "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": [
      "Larmor Frequency in MHz:  [-400.22802765 -400.22806765]\n"
     ]
    }
   ],
   "source": [
    "# Master Equation\n",
    "QS.PropagationSpace = \"Liouville\"\n",
    "QS.MasterEquation = \"Redfield\"\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)\n",
    "COMM = Commutators()\n",
    "Hz = Ham.Zeeman_RotFrame()\n",
    "\n",
    "# J coupling Hamiltonian\n",
    "Hj = Ham.Jcoupling()\n",
    "\n",
    "# Generating the commutation superoperator\n",
    "QS.RowColOrder = 'C'\n",
    "QLib = QuantumLibrary(QS)\n",
    "\n",
    "Hz_L = QLib.CommutationSuperoperator(Hz+Hj)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### product operator basis (Shift Z or PMZ basis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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": 6,
   "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_L = DM.EquilibriumDensityMatrix(QS.Ispintemp,HT_approx)\n",
    "    \n",
    "    # Equlibrium Density Matrix\n",
    "    rhoeq = DM.EquilibriumDensityMatrix(QS.Fspintemp,HT_approx)\n",
    "else:\n",
    "    rho_in_L = QS.Az + QS.Bz\n",
    "    rhoeq = QS.Az + QS.Bz  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle \\left[\\begin{matrix}0.250016003847122\\\\0\\\\0\\\\0\\\\0\\\\0.25\\\\0\\\\0\\\\0\\\\0\\\\0.25\\\\0\\\\0\\\\0\\\\0\\\\0.249983996152878\\end{matrix}\\right]$"
      ],
      "text/plain": [
       "Matrix([\n",
       "[0.250016003847122],\n",
       "[                0],\n",
       "[                0],\n",
       "[                0],\n",
       "[                0],\n",
       "[             0.25],\n",
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       "[             0.25],\n",
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       "[                0],\n",
       "[                0],\n",
       "[                0],\n",
       "[0.249983996152878]])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rho_in_L.matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle \\left[\\begin{matrix}0.250016003847122\\\\0\\\\0\\\\0\\\\0\\\\0.25\\\\0\\\\0\\\\0\\\\0\\\\0.25\\\\0\\\\0\\\\0\\\\0\\\\0.249983996152878\\end{matrix}\\right]$"
      ],
      "text/plain": [
       "Matrix([\n",
       "[0.250016003847122],\n",
       "[                0],\n",
       "[                0],\n",
       "[                0],\n",
       "[                0],\n",
       "[             0.25],\n",
       "[                0],\n",
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       "[                0],\n",
       "[             0.25],\n",
       "[                0],\n",
       "[                0],\n",
       "[                0],\n",
       "[                0],\n",
       "[0.249983996152878]])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rho_in_L.matrix"
   ]
  },
  {
   "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_L)"
   ]
  },
  {
   "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_L,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",
      "Larmor Frequency in MHz:  [-400.22802765 -400.22806765]\n",
      "Total time = 1.0280861854553223 seconds \n"
     ]
    }
   ],
   "source": [
    "QS.AcqDT = 0.0001\n",
    "QS.AcqAQ = 30.0\n",
    "QS.OdeMethod = 'DOP853'\n",
    "QS.PropagationMethod = \"Relaxation\"\n",
    "\n",
    "# Relaxation Superoperator\n",
    "RPro = RelaxationProcess(QS)\n",
    "R_L = RPro.Relaxation()\n",
    "\n",
    "EVol = Evolutions(QS,Ham)\n",
    "\n",
    "start_time = time.time()\n",
    "t, rho_t = EVol.Evolution(rho,rhoeq,Hz_L,R_L)\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"
     ]
    },
    {
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       "model_id": "1c7cac059ba94a9ebe57f008d4442012",
       "version_major": 2,
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      "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([t,t],[signal_Z1,signal_Z2],\"time (s)\",\"Mz\",[\"green\",\"blue\"])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "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"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}