{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "# This file is part of nannos\n# License: GPLv3\n%matplotlib notebook"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Two photonic crystal slabs\n\nMechanically tunable photonic crystal structure consisting of coupled photonic crystal slabs.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import matplotlib as mpl\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nimport nannos as nn"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "We will code the structures studied in :cite:p:`Suh2003`.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "nh = 51\nL1 = [1.0, 0]\nL2 = [0, 1.0]\ntheta = 0.0 * np.pi / 180\nphi = 0.0 * np.pi / 180\npsi = 0.0 * np.pi / 180\n\nNx = 2**8\nNy = 2**8\n\nlattice = nn.Lattice((L1, L2), (Nx, Ny))\n\nepsgrid = lattice.ones() * 12.0\nhole = lattice.circle((0.5, 0.5), 0.4)\nepsgrid[hole] = 1.0"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Define the problem\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "sup = lattice.Layer(\"Superstrate\", epsilon=1.0)\nphc_slab = lattice.Layer(\"PC slab\", thickness=0.55)\nsub = lattice.Layer(\"Substrate\", epsilon=1.0)\nphc_slab.epsilon = epsgrid\nstack = [sup, phc_slab, sub]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Fig 2 (a) from :cite:p:`Suh2003`.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "def compute_transmission(fn):\n    pw = nn.PlaneWave(wavelength=1 / fn, angles=(0, 0, 0))\n    sim = nn.Simulation(stack, pw, nh)\n    R, T = sim.diffraction_efficiencies()\n    print(f\"f = {fn} (normalized)\")\n    print(\"T = \", T)\n    return T\n\n\n#\nfreqs_norma = np.linspace(0.49, 0.6, 30)\nfreqs_adapted, transmission = nn.adaptive_sampler(\n    compute_transmission,\n    freqs_norma,\n)\n\n\nplt.figure()\nplt.plot(freqs_adapted, transmission, c=\"#be4c83\")\nplt.xlim(freqs_norma[0], freqs_norma[-1])\nplt.ylim(0, 1)\nplt.xlabel(r\"frequency ($2\\pi c / a$)\")\nplt.ylabel(\"Transmission\")\nplt.tight_layout()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Figs 2 (b-c) from :cite:p:`Suh2003`.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "phc_slab_top = lattice.Layer(\"PC slab top\", thickness=0.55)\nphc_slab_top.epsilon = epsgrid\nphc_slab_bot = phc_slab_top.copy(\"PC slab bottom\")\n\nplt.figure()\n\nseps = [1.35, 1.1, 0.95, 0.85, 0.75, 0.65, 0.55]\ncolors = plt.cm.turbo(np.linspace(0, 1, len(seps)))\n\nfor i, sep in enumerate(seps):\n    spacer = lattice.Layer(\"Spacer\", epsilon=1, thickness=sep)\n    stack = [sup, phc_slab_top, spacer, phc_slab_bot, sub]\n\n    def compute_transmission(fn):\n        pw = nn.PlaneWave(wavelength=1 / fn, angles=(0, 0, 0))\n        sim = nn.Simulation(stack, pw, nh)\n        R, T = sim.diffraction_efficiencies()\n        print(f\"f = {fn} (normalized)\")\n        print(\"T = \", T)\n        return T\n\n    freqs_norma = np.linspace(0.49, 0.6, 30)\n    freqs_adapted, transmission = nn.adaptive_sampler(\n        compute_transmission,\n        freqs_norma,\n    )\n\n    plt.plot(freqs_adapted, transmission, c=colors[i], label=rf\"$d = {sep}a$\")\n    plt.xlim(freqs_norma[0], freqs_norma[-1])\n    plt.ylim(0, 1)\n    plt.xlabel(r\"frequency ($2\\pi c / a$)\")\n    plt.ylabel(\"Transmission\")\n    plt.tight_layout()\n    plt.pause(0.1)\n\n\nplt.legend(loc=(1.05, 0.3))\nplt.tight_layout()\nplt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import nannos.utils.jupyter\n%nannos_version_table"
      ]
    }
  ],
  "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": "3.10.13"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}