{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fischer 2020 Model\n",
    "\n",
    "CCSN neutrino model from Tobias Fischer\n",
    "\n",
    "The citation is: *Neutrino signal from proto-neutron star evolution: Effects of opacities from charged-current-neutrino interactions and inverse neutron decay*, Fischer, Tobias ; Guo, Gang ; Dzhioev, Alan A. ; Martínez-Pinedo, Gabriel ; Wu, Meng-Ru ; Lohs, Andreas ; Qian, Yong-Zhong, Physical Review C, Volume 101, Issue 2, article id.025804 (https://ui.adsabs.harvard.edu/link_gateway/2020PhRvC.101b5804F/doi:10.1103/PhysRevC.101.025804), [arXiv:1804.10890](https://arxiv.org/abs/1804.10890)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "from astropy import units as u \n",
    "from snewpy.neutrino import Flavor\n",
    "from snewpy.models.ccsn import Fischer_2020\n",
    "from snewpy.flavor_transformation import NoTransformation, AdiabaticMSW, ThreeFlavorDecoherence\n",
    "\n",
    "mpl.rc('font', size=16)\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialize Models\n",
    "\n",
    "For the `Fischer_2020` model, there’s just a single progenitor available; so let’s initialize it. If this is the first time you’re using this progenitor, snewpy will automatically download the required data files for you."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "F2020 = Fischer_2020()\n",
    "\n",
    "F2020"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the luminosity of different neutrino flavors for this model. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1, figsize=(8, 6), tight_layout=False)\n",
    "\n",
    "for flavor in Flavor:\n",
    "    if flavor.is_electron == True:\n",
    "        color='C0'\n",
    "    else:\n",
    "        color='C1'\n",
    "    ls='-' if flavor.is_neutrino else ':'\n",
    "    lw = 2\n",
    "    \n",
    "    ax.plot(F2020.time, F2020.luminosity[flavor]/1e51,  # Report luminosity in units foe/s\n",
    "            label=flavor.to_tex(), color=color, ls=ls, lw=lw)\n",
    "    \n",
    "ax.set(xlim=(-0.1, 1), xlabel=r'$t-t_{\\rm bounce}$ [s]')\n",
    "ax.grid()\n",
    "ax.legend(loc='upper right', ncol=2, fontsize=18)\n",
    "ax.set(ylabel=r'luminosity [foe s$^{-1}$]');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initial and Oscillated Spectra\n",
    "\n",
    "Plot the neutrino spectra at the source and after the requested flavor transformation has been applied.\n",
    "\n",
    "### Adiabatic MSW Flavor Transformation: Normal mass ordering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Adiabatic MSW effect. NMO is used by default.\n",
    "xform_nmo = AdiabaticMSW()\n",
    "\n",
    "# Energy array and time to compute spectra.\n",
    "# Note that any convenient units can be used and the calculation will remain internally consistent.\n",
    "E = np.linspace(0,100,201) * u.MeV\n",
    "t = 50*u.ms\n",
    "\n",
    "ispec = F2020.get_initial_spectra(t, E)\n",
    "ospec_nmo = F2020.get_transformed_spectra(t, E, xform_nmo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, axes = plt.subplots(1,2, figsize=(12,5), sharex=True, sharey=True, tight_layout=True)\n",
    "\n",
    "for i, spec in enumerate([ispec, ospec_nmo]):\n",
    "    ax = axes[i]\n",
    "    for flavor in Flavor:\n",
    "        if flavor.is_electron == True:\n",
    "            color='C0'\n",
    "        else:\n",
    "            color='C1'\n",
    "        ax.plot(E, spec[flavor],\n",
    "                label=flavor.to_tex(),\n",
    "                color=color,\n",
    "                ls='-' if flavor.is_neutrino else ':', lw=2,\n",
    "                alpha=0.7)\n",
    "\n",
    "    ax.set(xlabel=r'$E$ [{}]'.format(E.unit),\n",
    "           title='Initial Spectra: $t = ${:.1f}'.format(t) if i==0 else 'Oscillated Spectra: $t = ${:.1f}'.format(t))\n",
    "    ax.grid()\n",
    "    ax.legend(loc='upper right', ncol=2, fontsize=16)\n",
    "\n",
    "ax = axes[0]\n",
    "ax.set(ylabel=r'flux [erg$^{-1}$ s$^{-1}$]')\n",
    "\n",
    "fig.tight_layout();"
   ]
  }
 ],
 "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": "3.12.3"
  },
  "vscode": {
   "interpreter": {
    "hash": "e2528887d751495e023d57d695389d9a04f4c4d2e5866aaf6dc03a1ed45c573e"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}