{
 "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 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/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 = \"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)"
   ]
  },
  {
   "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 = 18.687347412109375 seconds \n"
     ]
    }
   ],
   "source": [
    "QS.AcqDT = 0.0001\n",
    "QS.AcqAQ = 30.0\n",
    "QS.OdeMethod = 'DOP853'\n",
    "QS.PropagationMethod = \"ODE Solver\"\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": "de3695aeb67449a6bf84a341dc562f80",
       "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": "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
}