{
  "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# Polarization conversion\n\nSimulation of conversion efficiency of a geometric metasurface.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\nimport numpy as np\n\nimport nannos as nn"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "The unit cell is a rectangular Si structure on a SiO2 substrate\nas in :cite:p:`Yoon2021`.\nCircularly-polarized light of wavelength 635 nm is normally incident from the\nsubstrate to the structure\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "wl = 635  # wavelength\nP = 350  # period\nW = 100  # pillar width along x\nL = 190  # pillar length along y\neps_Si = (3.87 + 0.02j) ** 2\neps_SiO2 = 1.4573**2\nnh = 100"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Define a function to initialize simulation\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "def simu(H, psi):\n    lattice = nn.Lattice([[P, 0], [0, P]], discretization=2**9)\n    sup = lattice.Layer(\"Superstrate\", epsilon=eps_SiO2)\n    sub = lattice.Layer(\"Substrate\", epsilon=1)\n    epsilon = lattice.ones()\n    metaatom = lattice.rectangle((0.5 * P, 0.5 * P), (W, L))\n    epsilon[metaatom] = eps_Si\n    ms = lattice.Layer(\"Metasurface\", thickness=H, epsilon=epsilon)\n    pw = nn.PlaneWave(wavelength=wl, angles=(0, 0, psi))\n    return nn.Simulation([sup, ms, sub], pw, nh=nh)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Since the layer eigenmodes do not change with thickness we compute them\nonly once for the first iteration.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "nb_thick = 100\nthicknesses = np.linspace(200, 500, nb_thick)\nconv_effs = np.zeros(nb_thick)\n\nfor ih, H in enumerate(thicknesses):\n    # x-polarization\n    if ih == 0:\n        simx = simu(H, 0)\n    else:\n        simx.layers[1].thickness = H\n        simx.reset(\"S\")\n    rxi, txi = simx.diffraction_efficiencies(orders=True, complex=True)\n    txx = simx.get_order(txi[0], (0, 0))\n\n    # y-polarization\n    if ih == 0:\n        simy = simu(H, 90)\n    else:\n        simy.layers[1].thickness = H\n        # print(self.is_solved)\n        simy.reset(\"S\")\n    ryi, tyi = simy.diffraction_efficiencies(orders=True, complex=True)\n    tyy = simy.get_order(tyi[1], (0, 0))\n\n    conv_effs[ih] = np.abs((tyy - txx) / 2) ** 2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Plot the efficiency\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "plt.clf()\nplt.plot(thicknesses, conv_effs)\nplt.xlabel(\"H (nm)\")\nplt.ylabel(\"conversion efficiency\")\nplt.tight_layout()\nplt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Plot the unit cell\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "p = simx.plot_structure()\np.show_axes()\np.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": "3.12.5"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}