{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Zha et al. 2021 Models\n",
    "\n",
    "Data from Zha et al. 2021, hadron-quark phase transition simulations of a variety of progenitors from Sukhbold et al. 2018 and the STOS EOS with B=145MeV.\n",
    "  \n",
    "Reference: Zha et al. ApJ 911 74 2021\n",
    "- [doi:10.3847/1538-4357/abec4c](https://doi.org/10.3847/1538-4357/abec4c)\n",
    "- [arXiv:2103.02268](https://arxiv.org/abs/2103.02268)"
   ]
  },
  {
   "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",
    "\n",
    "from snewpy.neutrino import Flavor, MassHierarchy\n",
    "from snewpy.models.ccsn import Zha_2021\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",
    "To start, let’s see what progenitors are available for the `Zha_2021` model. We can use the `param` property to view all physics parameters and their possible values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Zha_2021.param"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We’ll initialise two of these progenitors. If this is the first time you’re using a progenitor, snewpy will automatically download the required data files for you."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "m19 = Zha_2021(progenitor_mass=19*u.solMass)\n",
    "m19_89 = Zha_2021(progenitor_mass=19.89*u.solMass)\n",
    "\n",
    "m19"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, let’s plot the luminosity of different neutrino flavors for this model. (Note that the `Zha_2021` simulations didn’t distinguish between $\\nu_x$ and $\\bar{\\nu}_x$, so both have the same luminosity.) We’ll also add zoomed-in plots to see the phase transition better."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, axes = plt.subplots(2, 2, figsize=(12, 10), tight_layout=True)\n",
    "\n",
    "for i, model in enumerate([m19, m19_89]):\n",
    "    for j in range(2):\n",
    "        ax = axes[j, i]\n",
    "        for flavor in Flavor:\n",
    "            ax.plot(model.time, model.luminosity[flavor]/1e51,  # Report luminosity in units foe/s\n",
    "                    label=flavor.to_tex(),\n",
    "                    color='C0' if flavor.is_electron else 'C1',\n",
    "                    ls='-' if flavor.is_neutrino else ':',\n",
    "                    lw=2)\n",
    "        ax.set(xlim=(-0.05, 0.9) if j==0 else (0.605, 0.665),\n",
    "               ylim=(0, 600) if j==0 else (0, 125),\n",
    "               xlabel=r'$t-t_{\\rm bounce}$ [s]',\n",
    "               ylabel=r'luminosity [foe s$^{-1}$]',\n",
    "               title=r'{}: {} $M_\\odot$'.format(model.metadata['EOS'], model.metadata['Progenitor mass'].value))\n",
    "        ax.grid()\n",
    "        ax.legend(loc='upper right', ncol=2, fontsize=18)"
   ]
  },
  {
   "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 = 400*u.ms\n",
    "\n",
    "ispec = model.get_initial_spectra(t, E)\n",
    "ospec_nmo = model.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",
    "        ax.plot(E, spec[flavor],\n",
    "                label=flavor.to_tex(),\n",
    "                color='C0' if flavor.is_electron else 'C1',\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();"
   ]
  }
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