{
 "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": [],
   "source": [
    "prop_CoNi = {}\n",
    "prop_CoNi['heat_capacity'] = ['lambda T: 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'] = ['lambda T: -{:f}*(T[0]-T[1])'.format(g),\n",
    "                                    'lambda T: {:f}*(T[0]-T[1])'.format(g),\n",
    "                                    'lambda T: {0:f}*T[2]*T[1]/{1:f}*(1-T[2]* (1 + 2/(np.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": [],
   "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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R6AAAAACsjEAHAAAAYGUEOgAAAAAr8/8A4EkIu8m+BlUAAAAASUVORK5CYII=\n",
      "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_ ...\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": "c1ed3f8bd5a0430f800fc6ec897560dc",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Elapsed time for _heat_diffusion_: 1.912075 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": "c68f9f039baf4c6788f3eb832af342d3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Elapsed time for _heat_diffusion_ with 1 excitation(s): 5.409857 s\n",
      "Calculating _heat_diffusion_ ...\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": "7d18f71784864c6b9cbff08baec1edb0",
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       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Elapsed time for _heat_diffusion_: 16.854034 s\n",
      "Elapsed time for _temp_map_: 24.341133 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.contourf(distances.to('nm').magnitude, delays.to('ps').magnitude, temp_map[:, :, 0], levels=100)\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.contourf(distances.to('nm').magnitude, delays.to('ps').magnitude, temp_map[:, :, 1], levels=100)\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.contourf(distances.to('nm').magnitude, delays.to('ps').magnitude, temp_map[:, :, 2], levels=100)\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": "3.7.7"
  },
  "toc-autonumbering": true
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
