{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Microscopic 3-Temperature-Model\n",
    "\n",
    "Here we adapt the NTM from the last example to allow for calculations of the magnetization within the microscopic 3-temperature-model as proposed by:\n",
    "\n",
    "Koopmans, B., Malinowski, G., Dalla Longa, F. et al.  \n",
    "*Explaining the paradoxical diversity of ultrafast laser-induced demagnetization.*  \n",
    "[Nature Mater 9, 259–265 (2010).](https://doi.org/10.1038/nmat2593)\n",
    "\n",
    "We need to solve the following coupled differential equations:\n",
    "\n",
    "\\begin{align}\n",
    "c_e(T_e) \\rho \\frac{\\partial T_e}{\\partial t} & = & \\frac{\\partial}{\\partial z}\n",
    "\\left( k_e(T_e) \\frac{\\partial T_e}{\\partial z} \\right)\n",
    "- G_{ep}(T_e-T_p) + S(z, t) \\\\\n",
    "c_p(T_p) \\rho \\frac{\\partial T_p}{\\partial t} & = & \\frac{\\partial}{\\partial z}\n",
    "\\left( k_p(T_p) \\frac{\\partial T_p}{\\partial z} \\right)\n",
    "+ G_{ep}(T_e-T_p) \\\\\n",
    "\\frac{\\partial m}{\\partial t} & = & R m \\frac{T_p}{T_C}\n",
    "\\left( 1 - m \\coth\\left( \\frac{m T_C}{T_e} \\right) \\right)\n",
    "\\end{align}\n",
    "\n",
    "We treat the temperature of the 3rd subsystem as magnetization $m$.\n",
    "For that we have to set its `heat_capacity` to $1/\\rho$ and `thermal_conductivity` to zero.\n",
    "We put the complete right term of the last equation in the `sub_system_coupling` term for the 3rd subsystem.\n",
    "Here, we need to rewrite the kotangens hyperbolicus in Python as\n",
    "$$\\coth(x) = 1 + \\frac{2}{e^{2x} - 1}$$\n",
    "\n",
    "The values of the used parameters are not experimentally verified."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup\n",
    "\n",
    "Do all necessary imports and settings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import udkm1Dsim as ud\n",
    "u = ud.u  # import the pint unit registry from udkm1Dsim\n",
    "import scipy.constants as constants\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "u.setup_matplotlib()  # use matplotlib with pint units"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Structure\n",
    "\n",
    " to the [structure-example](structure.ipynb) for more details."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "Co = ud.Atom('Co')\n",
    "Ni = ud.Atom('Ni')\n",
    "CoNi = ud.AtomMixed('CoNi')\n",
    "CoNi.add_atom(Co, 0.5)\n",
    "CoNi.add_atom(Ni, 0.5)\n",
    "Si = ud.Atom('Si')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of subsystems changed from 1 to 3.\n"
     ]
    }
   ],
   "source": [
    "prop_CoNi = {}\n",
    "prop_CoNi['heat_capacity'] = ['0.1*T',\n",
    "                              532*u.J/u.kg/u.K,\n",
    "                              1/7000\n",
    "                             ]\n",
    "prop_CoNi['therm_cond'] = [20*u.W/(u.m*u.K),\n",
    "                           80*u.W/(u.m*u.K),\n",
    "                           0]\n",
    "\n",
    "R = 25.3/1e-12\n",
    "Tc = 1388\n",
    "g = 4.0e18\n",
    "\n",
    "prop_CoNi['sub_system_coupling'] = ['-{:f}*(T_0-T_1)'.format(g),\n",
    "                                    '{:f}*(T_0-T_1)'.format(g),\n",
    "                                    '{0:f}*T_2*T_1/{1:f}*(1-T_2* (1 + 2/(exp(2*T_2*{1:f}/T_0) - 1) ))'.format(R, Tc)\n",
    "                                    ]\n",
    "prop_CoNi['lin_therm_exp'] = [0, 11.8e-6, 0]\n",
    "prop_CoNi['sound_vel'] = 4.910*u.nm/u.ps\n",
    "prop_CoNi['opt_ref_index'] = 2.9174+3.3545j\n",
    "\n",
    "layer_CoNi = ud.AmorphousLayer('CoNi', 'CoNi amorphous', thickness=1*u.nm,\n",
    "                               density=7000*u.kg/u.m**3, atom=CoNi, **prop_CoNi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of subsystems changed from 1 to 3.\n"
     ]
    }
   ],
   "source": [
    "prop_Si = {}\n",
    "prop_Si['heat_capacity'] = [100*u.J/u.kg/u.K, 603*u.J/u.kg/u.K, 1]\n",
    "prop_Si['therm_cond'] = [0, 100*u.W/(u.m*u.K), 0]\n",
    "\n",
    "prop_Si['sub_system_coupling'] = [0, 0, 0]\n",
    "\n",
    "prop_Si['lin_therm_exp'] = [0, 2.6e-6, 0]\n",
    "prop_Si['sound_vel'] = 8.433*u.nm/u.ps\n",
    "prop_Si['opt_ref_index'] = 3.6941+0.0065435j\n",
    "\n",
    "layer_Si = ud.AmorphousLayer('Si', \"Si amorphous\", thickness=1*u.nm,\n",
    "                             density=2336*u.kg/u.m**3, atom=Si, **prop_Si)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "S = ud.Structure('CoNi')\n",
    "\n",
    "S.add_sub_structure(layer_CoNi, 20)\n",
    "S.add_sub_structure(layer_Si, 50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "S.visualize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialize Heat and the Excitation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "h = ud.Heat(S, True)\r\n",
    "\r\n",
    "h.save_data = False\r\n",
    "h.disp_messages = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "h.excitation = {'fluence': [30]*u.mJ/u.cm**2,\n",
    "                'delay_pump':  [0]*u.ps,\n",
    "                'pulse_width':  [0.05]*u.ps,\n",
    "                'multilayer_absorption': True,\n",
    "                'wavelength': 800*u.nm,\n",
    "                'theta': 45*u.deg}\n",
    "# temporal and spatial grid\n",
    "delays = np.r_[-1:5:0.005]*u.ps\n",
    "_, _, distances = S.get_distances_of_layers()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculate Heat Diffusion\r\n",
    "\r\n",
    "The `init_temp` sets the magnetization in the 3rd subsystem to `1` for CoNi and `0` for Si."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Surface incidence fluence scaled by factor 0.7071 due to incidence angle theta=45.00 deg\n",
      "Calculating _heat_diffusion_ without excitation...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "58f57e6b7a974ba6b2b1ca034b55b1cd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elapsed time for _heat_diffusion_: 1.004121 s\n",
      "Calculating _heat_diffusion_ for excitation 1:1 ...\n",
      "Absorption profile is calculated by multilayer formalism.\n",
      "Total reflectivity of 42.4 % and transmission of 28.4 %.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0f5de7e4cc0744b68a746f8e3ebb31e0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elapsed time for _heat_diffusion_ with 1 excitation(s): 2.797672 s\n",
      "Calculating _heat_diffusion_ without excitation...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "16b11d10795d4a61a19ec96c52bc9e95",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elapsed time for _heat_diffusion_: 8.989778 s\n",
      "Elapsed time for _temp_map_: 12.859290 s\n"
     ]
    }
   ],
   "source": [
    "# enable heat diffusion\n",
    "h.heat_diffusion = True\n",
    "# set the boundary conditions\n",
    "h.boundary_conditions = {'top_type': 'isolator', 'bottom_type': 'isolator'}\n",
    "# The resulting temperature profile is calculated in one line:\n",
    "\n",
    "init_temp = np.ones([S.get_number_of_layers(), 3])\n",
    "init_temp[:, 0] = 300\n",
    "init_temp[:, 1] = 300\n",
    "init_temp[20:, 2] = 0\n",
    "\n",
    "temp_map, delta_temp = h.get_temp_map(delays, init_temp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x864 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[6, 12])\n",
    "plt.subplot(3, 1, 1)\n",
    "plt.pcolormesh(distances.to('nm').magnitude, delays.to('ps').magnitude, temp_map[:, :, 0], shading='auto')\n",
    "plt.colorbar()\n",
    "plt.xlabel('Distance [nm]')\n",
    "plt.ylabel('Delay [ps]')\n",
    "plt.title('Temperature Map Electrons')\n",
    "\n",
    "plt.subplot(3, 1, 2)\n",
    "plt.pcolormesh(distances.to('nm').magnitude, delays.to('ps').magnitude, temp_map[:, :, 1], shading='auto')\n",
    "plt.colorbar()\n",
    "plt.xlabel('Distance [nm]')\n",
    "plt.ylabel('Delay [ps]')\n",
    "plt.title('Temperature Map Phonons')\n",
    "\n",
    "plt.subplot(3, 1, 3)\n",
    "plt.pcolormesh(distances.to('nm').magnitude, delays.to('ps').magnitude, temp_map[:, :, 2], shading='auto')\n",
    "plt.colorbar()\n",
    "plt.xlabel('Distance [nm]')\n",
    "plt.ylabel('Delay [ps]')\n",
    "plt.title('Magnetization')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[6, 8])\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.plot(delays.to('ps'), np.mean(temp_map[:, S.get_all_positions_per_unique_layer()['CoNi'], 0], 1), label='electrons')\n",
    "plt.plot(delays.to('ps'), np.mean(temp_map[:, S.get_all_positions_per_unique_layer()['CoNi'], 1], 1), label='phonons')\n",
    "plt.ylabel('Temperature [K]')\n",
    "plt.xlabel('Delay [ps]')\n",
    "plt.legend()\n",
    "plt.title('M3TM Koopmans et. al')\n",
    "\n",
    "plt.subplot(2, 1, 2)\n",
    "\n",
    "plt.plot(delays.to('ps'), np.mean(temp_map[:, S.get_all_positions_per_unique_layer()['CoNi'], 2], 1), label='M')\n",
    "plt.ylabel('Magnetization')\n",
    "plt.xlabel('Delay [ps]')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.8.9"
  },
  "toc-autonumbering": true
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
