{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Carrier injection based Mach-Zehnder modulator\n",
        "\n",
        "Tidy3D capabilities include the modeling of material properties\n",
        "perturbations due to the presence of free carriers. This provides a\n",
        "convenient way to perform full-wave simulations of electro-optic\n",
        "modulators. In this notebook we demonstrate simulation of a simple\n",
        "pin-junction electro-optic modulator as part of an MZI. For generating\n",
        "free carrier distributions under different voltages we use our [Charge\n",
        "solver](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.HeatChargeSimulation.html#tidy3d.HeatChargeSimulation).\n",
        "This example loosely follows the experimental modulator described in\n",
        "[Zhou Liang et al 2011 Chinese Phys. Lett. 28\n",
        "074202](https://doi.org/10.1088/0256-307X/28/7/074202).\n",
        "\n",
        "<img src=\"img/MZI_modulator.png\" width=\"500\" alt=\"Schematic of the MZI modulator\">\n",
        "\n",
        "## Problem Parameters"
      ],
      "id": "5373f8e1-188b-4462-9582-60e86b01c343"
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import photonforge as pf\n",
        "import tidy3d as td\n",
        "from matplotlib import pyplot as plt\n",
        "from tidy3d import web"
      ],
      "id": "3d788a59"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Our simulation setup will consist of an MZI with two arms, one of which\n",
        "has a common pin-junction profile. For combiner and splitter of the\n",
        "signal we use compact y-junction MMIs. The overall geometry and notation\n",
        "used is shown in the following figure.\n",
        "\n",
        "<img src=\"img/pn_mzi_cross.png\" alt=\"Modulator Cross-Section\"  width=\"500\"/>\n",
        "\n",
        "<img src=\"img/pn_mzi_circuit.png\" alt=\"Scheme of MZI Circuit\"  width=\"1000\"/>"
      ],
      "id": "9bbf9407-6948-40f5-85ab-33d78d894f18"
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {},
      "outputs": [],
      "source": [
        "# modulator cross section parameters (um)\n",
        "w_core = 0.5\n",
        "h_core = 0.34\n",
        "h_slab = 0.1\n",
        "h_side = 0.34\n",
        "w_contact = 0.5\n",
        "x_side = 2.25\n",
        "x_total = 3\n",
        "x_i = 0.55\n",
        "x_p = 1.75\n",
        "h_contact = 0.1\n",
        "# note that the height of the metal contact doesn't affect the results\n",
        "# but devsim requires creating a region representing it\n",
        "# in order to create a interface between the metal contact and modulator\n",
        "\n",
        "# modulator doping concentrations (1/cm^3)\n",
        "conc_p = 1e19\n",
        "conc_pp = 5e19\n",
        "conc_n = 1e19\n",
        "conc_nn = 5e19\n",
        "# note that concentrations in ++/-- are (conc_p + conc_pp) and (conc_n + conc_nn)\n",
        "\n",
        "# photonic circuit geometric parameters (um)\n",
        "y_length_in = 10\n",
        "y_length_out = 1\n",
        "y_length_bend = 10\n",
        "wg_spacing = 3.5\n",
        "taper_length = 10\n",
        "pin_length = 200\n",
        "\n",
        "# effective infinity\n",
        "effective_inf = 1e6"
      ],
      "id": "fec6b731"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Auxiliary variables for easier construction of simulations."
      ],
      "id": "bb2cb559-c6e3-4c44-8990-8b1e03b7824d"
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [],
      "source": [
        "mzi_length = 2 * taper_length + pin_length\n",
        "splitter_length = y_length_in + y_length_out + y_length_bend\n",
        "\n",
        "z_core = h_core / 2\n",
        "z_slab = h_slab / 2"
      ],
      "id": "7ea0cffa"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Semiconductor medium\n",
        "\n",
        "Before we can start the Charge simulation, let us create a semiconductor\n",
        "medium. Semiconductor mediums are constructed with the class\n",
        "[SemiconductorMedium](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.SemiconductorMedium.html#tidy3d.SemiconductorMedium).\n",
        "\n",
        "Since semiconductor mediums accept doping, let’s create those first.\n",
        "Doping is defined here in terms of boxes. Among the different types of\n",
        "doping boxes available we’ll be using here the\n",
        "[ConstantDoping](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ConstantDoping.html#tidy3d.ConstantDoping),\n",
        "which applies a constant doping to the doping box. One thing to note is\n",
        "that these doping boxes are additive, i.e., if two donor doping boxes\n",
        "overlap, the total concentration in the overlap region will be the sum\n",
        "of these two overlapping doping boxes. To further demonstrate this\n",
        "concept:"
      ],
      "id": "f1a1a1a3-b1b8-4d59-8aac-9be48ad808fa"
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [],
      "source": [
        "acceptors = []\n",
        "donors = []\n",
        "\n",
        "acceptors.append(\n",
        "    td.ConstantDoping.from_bounds(\n",
        "        rmin=[-effective_inf, wg_spacing / 2 - x_total, -1],\n",
        "        rmax=[effective_inf, wg_spacing / 2 - x_p, h_side + 1],\n",
        "        concentration=conc_pp,\n",
        "    )\n",
        ")\n",
        "acceptors.append(\n",
        "    td.ConstantDoping.from_bounds(\n",
        "        rmin=[-effective_inf, wg_spacing / 2 - x_total, -1],\n",
        "        rmax=[effective_inf, wg_spacing / 2 - x_i, h_side + 1],\n",
        "        concentration=conc_p,\n",
        "    )\n",
        ")\n",
        "\n",
        "donors.append(\n",
        "    td.ConstantDoping.from_bounds(\n",
        "        rmin=[-effective_inf, wg_spacing / 2 + x_p, -1],\n",
        "        rmax=[effective_inf, wg_spacing / 2 + x_total, h_side + 1],\n",
        "        concentration=conc_nn,\n",
        "    )\n",
        ")\n",
        "donors.append(\n",
        "    td.ConstantDoping.from_bounds(\n",
        "        rmin=[-effective_inf, wg_spacing / 2 + x_i, -1],\n",
        "        rmax=[effective_inf, wg_spacing / 2 + x_total, h_side + 1],\n",
        "        concentration=conc_n,\n",
        "    )\n",
        ")"
      ],
      "id": "d20a32f3"
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {},
      "outputs": [],
      "source": [
        "# let's define a material here for our Charge simulations\n",
        "si_doped = td.MultiPhysicsMedium(\n",
        "    optical=td.material_library[\"cSi\"][\"Li1993_293K\"],\n",
        "    charge=td.SemiconductorMedium(\n",
        "        permittivity=11.1,\n",
        "        N_c=td.ConstantEffectiveDOS(N=2.86e19),\n",
        "        N_v=td.ConstantEffectiveDOS(N=3.1e19),\n",
        "        E_g=td.ConstantEnergyBandGap(eg=1.11),\n",
        "        mobility_n=td.ConstantMobilityModel(mu=400),\n",
        "        mobility_p=td.ConstantMobilityModel(mu=200),\n",
        "        R=[td.ShockleyReedHallRecombination(tau_n=1e-8, tau_p=1e-8)],\n",
        "        N_a=acceptors,\n",
        "        N_d=donors,\n",
        "    ),\n",
        ")"
      ],
      "id": "ad26a3a9"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Optic mediums\n",
        "\n",
        "Since some of the structures will be reused in the optic simulations,\n",
        "let us also create the required mediums here."
      ],
      "id": "3d9f95ed-ba52-444a-bbee-ca21dc79ef41"
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [],
      "source": [
        "wvl_um = 1.55\n",
        "freq0 = td.C_0 / wvl_um\n",
        "\n",
        "si = si_doped.optical\n",
        "n_si, k_si = si.nk_model(frequency=td.C_0 / wvl_um)\n",
        "\n",
        "si_non_perturb = td.Medium.from_nk(n=n_si, k=k_si, freq=freq0)\n",
        "\n",
        "sio2 = td.Medium(permittivity=1.444**2)"
      ],
      "id": "4f3df8f2"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Charge simulation\n",
        "\n",
        "We are now ready to create the charge simulation. The first step is to\n",
        "create the waveguide structures. To do this, we define the following\n",
        "functions that encapsulate the necessary steps.\n",
        "\n",
        "We will use PhotonForge’s layout capabilities. PhotonForge also provides\n",
        "a complete set of tools for photonic design automation, including PDK\n",
        "integration, parametric components, connectivity management, and\n",
        "technology definitions. You can check the many applications of this\n",
        "powerful tool\n",
        "[here](https://docs.flexcompute.com/projects/photonforge/en/latest/examples.html).\n",
        "\n",
        "The `make_waveguide` function is a generic function that creates a\n",
        "tapered waveguide with initial width `wg_width_0` and final width\n",
        "`wg_width_1`. This is easily achieved using\n",
        "[pf.Path](https://docs.flexcompute.com/projects/photonforge/en/latest/_autosummary/photonforge.Path.html)\n",
        "and `pf.Path.segment`."
      ],
      "id": "d1690576-a258-4cb5-aaca-0e6161eb96ac"
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [],
      "source": [
        "def make_waveguide(\n",
        "    x0, y0, z0, x1, y1, wg_width_0, wg_width_1, wg_thickness, medium, sidewall_angle=0\n",
        "):\n",
        "    \"\"\"\n",
        "    Linear waveguide taper using PhotonForge.\n",
        "    \"\"\"\n",
        "\n",
        "    # create path starting at (x0, y0)\n",
        "    path = pf.Path(origin=(x0, y0), width=wg_width_0)\n",
        "\n",
        "    # linear taper to (x1, y1)\n",
        "    path.segment((x1, y1), width=wg_width_1)\n",
        "\n",
        "    # convert to polygon\n",
        "    poly = path.to_polygon()\n",
        "\n",
        "    # create PolySlab geometry\n",
        "    geometry = td.PolySlab(\n",
        "        vertices=poly.vertices,\n",
        "        axis=2,\n",
        "        slab_bounds=(z0, z0 + wg_thickness),\n",
        "        sidewall_angle=sidewall_angle,\n",
        "    )\n",
        "\n",
        "    return td.Structure(geometry=geometry, medium=medium)"
      ],
      "id": "a6e6e6e0"
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [],
      "source": [
        "def make_rib_waveguide(\n",
        "    x0,\n",
        "    y0,\n",
        "    z0,\n",
        "    x1,\n",
        "    y1,\n",
        "    core_width,\n",
        "    slab_width,\n",
        "    side_width,\n",
        "    core_thickness,\n",
        "    slab_thickness,\n",
        "    side_thickness,\n",
        "    medium,\n",
        "    sidewall_angle=0,\n",
        "):\n",
        "    \"\"\"\n",
        "    This function defines a linear waveguide taper and returns the tidy3d structure of it.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    x0: x coordinate of the waveguide starting position (um)\n",
        "    y0: y coordinate of the waveguide starting position (um)\n",
        "    z0: z coordinate of the waveguide bottom surface (um)\n",
        "    x1: x coordinate of the waveguide end position (um)\n",
        "    y1: y coordinate of the waveguide end position (um)\n",
        "    core_width: width of the waveguide core (um)\n",
        "    slab_width: width of the slab (um)\n",
        "    side_width: width of the side ribs (um)\n",
        "    core_thickness: thickness of the waveguide core (um)\n",
        "    slab_thickness: thickness of the slab (um)\n",
        "    side_thickness: thickness of the side ribs (um)\n",
        "    medium: medium of the waveguide\n",
        "    sidewall_angle: side wall angle of the waveguide (rad)\n",
        "    \"\"\"\n",
        "\n",
        "    # modulator\n",
        "    slab = make_waveguide(\n",
        "        x0=x0,\n",
        "        y0=y0,\n",
        "        z0=z0,\n",
        "        x1=x1,\n",
        "        y1=y1,\n",
        "        wg_width_0=slab_width,\n",
        "        wg_width_1=slab_width,\n",
        "        wg_thickness=slab_thickness,\n",
        "        medium=medium,\n",
        "        sidewall_angle=sidewall_angle,\n",
        "    )\n",
        "\n",
        "    core = make_waveguide(\n",
        "        x0=x0,\n",
        "        y0=y0,\n",
        "        z0=z0,\n",
        "        x1=x1,\n",
        "        y1=y1,\n",
        "        wg_width_0=core_width,\n",
        "        wg_width_1=core_width,\n",
        "        wg_thickness=core_thickness,\n",
        "        medium=medium,\n",
        "        sidewall_angle=sidewall_angle,\n",
        "    )\n",
        "\n",
        "    y_side_top = y0 + (slab_width / 2 - side_width / 2)\n",
        "    y_side_bottom = y0 - (slab_width / 2 - side_width / 2)\n",
        "\n",
        "    side_top = make_waveguide(\n",
        "        x0=x0,\n",
        "        y0=y_side_top,\n",
        "        z0=z0,\n",
        "        x1=x1,\n",
        "        y1=y_side_top,\n",
        "        wg_width_0=side_width,\n",
        "        wg_width_1=side_width,\n",
        "        wg_thickness=side_thickness,\n",
        "        medium=medium,\n",
        "        sidewall_angle=sidewall_angle,\n",
        "    )\n",
        "\n",
        "    side_bottom = make_waveguide(\n",
        "        x0=x0,\n",
        "        y0=y_side_bottom,\n",
        "        z0=z0,\n",
        "        x1=x1,\n",
        "        y1=y_side_bottom,\n",
        "        wg_width_0=side_width,\n",
        "        wg_width_1=side_width,\n",
        "        wg_thickness=side_thickness,\n",
        "        medium=medium,\n",
        "        sidewall_angle=sidewall_angle,\n",
        "    )\n",
        "\n",
        "    return [core, slab, side_top, side_bottom]"
      ],
      "id": "9e85c2e0"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "With the above functions we can now create the waveguide structures\n",
        "`pin_wg`. For ease in defining boundary conditions we define here some\n",
        "auxiliary structures made up of a conductive medium defined with\n",
        "[ChargeConductorMedium](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ChargeConductorMedium.html#tidy3d.ChargeConductorMedium)."
      ],
      "id": "b5993197-d53a-44a2-87bb-126211a66284"
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {},
      "outputs": [],
      "source": [
        "# top arm: PIN region\n",
        "pin_wg = make_rib_waveguide(\n",
        "    x0=-pin_length / 2,\n",
        "    y0=wg_spacing / 2,\n",
        "    z0=0,\n",
        "    x1=pin_length / 2,\n",
        "    y1=wg_spacing / 2,\n",
        "    core_width=w_core,\n",
        "    slab_width=2 * x_total,\n",
        "    side_width=x_total - x_side,\n",
        "    core_thickness=h_core,\n",
        "    slab_thickness=h_slab,\n",
        "    side_thickness=h_side,\n",
        "    medium=si_doped,\n",
        "    sidewall_angle=0,\n",
        ")\n",
        "\n",
        "# auxiliary materials we use to define BCs\n",
        "aux_medium = td.MultiPhysicsMedium(\n",
        "    charge=td.ChargeConductorMedium(conductivity=1), name=\"aux_medium\"\n",
        ")\n",
        "\n",
        "# create a couple structs to define the contacts\n",
        "contact_p = td.Structure(\n",
        "    geometry=td.Box(\n",
        "        center=(0, wg_spacing / 2 - x_total + w_contact / 2, h_side + h_contact / 2),\n",
        "        size=(effective_inf, w_contact, h_contact),\n",
        "    ),\n",
        "    medium=aux_medium,\n",
        "    name=\"contact_p\",\n",
        ")\n",
        "\n",
        "contact_n = td.Structure(\n",
        "    geometry=td.Box(\n",
        "        center=(0, wg_spacing / 2 + x_total - w_contact / 2, h_side + h_contact / 2),\n",
        "        size=(effective_inf, w_contact, h_contact),\n",
        "    ),\n",
        "    medium=aux_medium,\n",
        "    name=\"contact_n\",\n",
        ")"
      ],
      "id": "026c2731"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Charge scene\n",
        "\n",
        "Now let’s put these structures together and check that it all looks\n",
        "good."
      ],
      "id": "a2c80392-0551-4c42-b98e-aee5e4027e25"
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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          }
        }
      ],
      "source": [
        "scene_charge = td.Scene(\n",
        "    structures=pin_wg + [contact_p, contact_n],\n",
        "    medium=sio2,\n",
        ")\n",
        "\n",
        "scene_charge.plot(x=0)\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "id": "7ec550cb"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Let’s also inspect the doping profiles and make sure it is what we were\n",
        "expecting."
      ],
      "id": "975fe0f0-364c-45ea-8c9b-0fd20f4e0164"
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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sOzo6Ftk3EZEcfvjhB+l9qrDztRcdPXpUWFlZCQCiW7du4tatW/m2X7lyRTRo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\nERGR2fg/hjDlISp9J3EAAAAASUVORK5CYII=\n"
          }
        }
      ],
      "source": [
        "scene_charge.plot_structures_property(x=0, property=\"doping\")\n",
        "plt.show()"
      ],
      "id": "06d26431"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Boundary conditions\n",
        "\n",
        "Since we’re interested in the response of the system for different\n",
        "applied voltages, we’ll need to solve the charge problem at each of\n",
        "these voltages. In Charge this can readily be done since the\n",
        "[VoltageBC](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.VoltageBC.html#tidy3d.VoltageBC)\n",
        "can accept an array of voltages as source through\n",
        "[DCVoltageSource](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.DCVoltageSource.html#tidy3d.DCVoltageSource).\n",
        "A parameter scan will be run and the returned data will have the\n",
        "provided voltage values as a separate dimension.\n",
        "\n",
        "Let’s define forward bias values up to 1.2 V with a step of 0.1 V."
      ],
      "id": "12f3d4be-34c8-41a3-ab40-f0e97bb9e4e7"
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {},
      "outputs": [],
      "source": [
        "# create BCs\n",
        "voltages = list(np.arange(13) * 0.1)\n",
        "\n",
        "bc_v1 = td.HeatChargeBoundarySpec(\n",
        "    condition=td.VoltageBC(source=td.DCVoltageSource(voltage=voltages)),\n",
        "    placement=td.StructureBoundary(structure=contact_p.name),\n",
        ")\n",
        "\n",
        "bc_v2 = td.HeatChargeBoundarySpec(\n",
        "    condition=td.VoltageBC(source=td.DCVoltageSource(voltage=0)),\n",
        "    placement=td.StructureBoundary(structure=contact_n.name),\n",
        ")\n",
        "\n",
        "boundary_conditions = [bc_v1, bc_v2]"
      ],
      "id": "ebdaa9bf"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Charge monitors\n",
        "\n",
        "Since we’re interested in obtaining the free carrier distribution we’ll\n",
        "add a\n",
        "[SteadyFreeCarrierMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.SteadyFreeCarrierMonitor.html#tidy3d.SteadyFreeCarrierMonitor)\n",
        "to our Charge simulation. Note that the below monitor has been defined\n",
        "in the $x=0$ plane."
      ],
      "id": "e49eae54-0610-43c8-b35a-d64279c0371a"
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {},
      "outputs": [],
      "source": [
        "charge_mnt = td.SteadyFreeCarrierMonitor(\n",
        "    center=(0, 0, 0),\n",
        "    size=(0, effective_inf, effective_inf),\n",
        "    name=\"charge_mnt\",\n",
        "    unstructured=True,\n",
        ")"
      ],
      "id": "0d782f34"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Charge simulation object\n",
        "\n",
        "When running Charge, we need to define the type of Charge simulation and\n",
        "some convergence settings. In the current case we set an relative\n",
        "tolerance of $10^{-5}$ and an absolute tolerance of $5\\cdot 10^{10}$.\n",
        "The absolute tolerance may seem big though one should notice we have\n",
        "variables (electrons/holes) that take on values many orders of magnitude\n",
        "larger than the tolerance ($\\approx 10^{20}$).\n",
        "\n",
        "In the current case, we are going to run an isothermal DC case which we\n",
        "can define with `IsothermalSteadyChargeDCAnalysis`. In DC mode we can\n",
        "set the parameter `convergence_dv` which tells the solver to limit the\n",
        "size of the sweep, i.e., if we need to solve for a bias of 0 and 0.5 and\n",
        "we set `convergence_dv=0.1`, it will force the solver to go between 0\n",
        "and 0.5 at intervals of 0.1.\n",
        "\n",
        "We’ll also use a `DistanceUnstructuredGrid` with fine resolution around\n",
        "interfaces, and coarser resolution in bulk."
      ],
      "id": "4e499b84-11fa-49e4-ba1c-bd0eb581f37c"
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {},
      "outputs": [],
      "source": [
        "convergence_settings = td.ChargeToleranceSpec()\n",
        "\n",
        "analysis_type = td.IsothermalSteadyChargeDCAnalysis(\n",
        "    temperature=300, tolerance_settings=convergence_settings, convergence_dv=0.1\n",
        ")\n",
        "\n",
        "res = 0.005  # resolution around interfaces in micron\n",
        "mesh = td.DistanceUnstructuredGrid(\n",
        "    dl_interface=res,\n",
        "    dl_bulk=res * 10,\n",
        "    distance_interface=res * 2,\n",
        "    distance_bulk=res * 10,\n",
        "    relative_min_dl=0.0,\n",
        ")"
      ],
      "id": "98ad8690"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "We now have all the required elements to define a Charge simulation\n",
        "object. Note that the simulation has 0 size in the $x$ direction. With\n",
        "this, we’ll make sure that the simulation is 2D even if the structures\n",
        "themselves are not."
      ],
      "id": "68ba74bc-2cba-46db-ae99-c65c6b5565ec"
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {},
      "outputs": [],
      "source": [
        "charge_sim = td.HeatChargeSimulation(\n",
        "    monitors=[charge_mnt],\n",
        "    analysis_spec=analysis_type,\n",
        "    center=(0, wg_spacing / 2, (h_side + h_contact) / 2),\n",
        "    size=(0, 2 * x_total + 0.1, h_side + h_contact + 0.1),\n",
        "    structures=scene_charge.structures,\n",
        "    medium=scene_charge.medium,\n",
        "    boundary_spec=boundary_conditions,\n",
        "    grid_spec=mesh,\n",
        ")"
      ],
      "id": "9a0ece9c"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "We can also plot here the simulation and some properties. In the\n",
        "properties plot, as well as the conductivity (which is invisible since\n",
        "the only conducting structures are the BC auxiliary ones) we can see the\n",
        "boundary conditions in blue and orange."
      ],
      "id": "a0c30d85-8e3a-45e0-b03e-01ae10c599bb"
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
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HDx7MVub48ePG3Xffna2ctamFV65caW4PCwszli5dajUzKSnJ+P33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          }
        }
      ],
      "source": [
        "# plot simulation\n",
        "fig, ax = plt.subplots(1, 2, figsize=(10, 15))\n",
        "charge_sim.plot(x=0, ax=ax[0])\n",
        "charge_sim.plot_property(x=0, property=\"electric_conductivity\", ax=ax[1])\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "id": "4840cb88"
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:12:42 UTC </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'mzi_pin_mesh'</span> with resource_id                       \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'vom-c609de59-5664-4a73-8c02-fa990805767f'</span> and task_type           \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'VOLUME_MESH'</span>.                                                     \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Tidy3D's VolumeMesher solver is currently in the beta stage. Cost  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>of VolumeMesher simulations is subject to change in the future.    \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"87e639c7021349b4bb87a2da4e3d6234\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:12:44 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>get the billed FlexCredit cost after a simulation run.             \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:12:45 UTC </span>status = queued                                                    \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"6938681d85dc4878aec700e773c164c4\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:12:57 UTC </span>starting up solver                                                 \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>running solver                                                     \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:13:01 UTC </span>status = success                                                   \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'mzi_pin_solve'</span> with resource_id                      \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'hec-78202987-c1a7-4e83-a96a-f134dfbab39f'</span> and task_type           \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'HEAT_CHARGE'</span>.                                                     \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Tidy3D's HeatCharge solver is currently in the beta stage. Cost of \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>HeatCharge simulations is subject to change in the future.         \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"c761cc7a401f495bbd42402db40f5d82\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:13:02 UTC </span>Estimated typical FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. For charge simulations,  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>the billed cost depends on the number of solver iterations required\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>for convergence.                                                   \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.229</span>. This assumes the charge solver     \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>reaches its configured iteration limits for all applied biases. Use\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed FlexCredit cost after a \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>simulation run.                                                    \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:13:06 UTC </span>status = queued                                                    \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"f3917728036d4e0aa3ffdbe0657c7010\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:13:16 UTC </span>status = preprocess                                                \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:13:25 UTC </span>starting up solver                                                 \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>running solver                                                     \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:13:27 UTC </span>status = success                                                   \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"407df33214734564a2e2d118783ddc0c\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:13:28 UTC </span>Loading results from charge_mzi_pin.hdf5                           \n",
              "</pre>"
            ]
          }
        }
      ],
      "source": [
        "charge_data = web.run(charge_sim, task_name=\"mzi_pin\", path=\"charge_mzi_pin.hdf5\")"
      ],
      "id": "649c31cf"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Carrier Distribution\n",
        "\n",
        "Let’s visualize the electron distributions for zero and 1.2 V biases."
      ],
      "id": "59541480-d84b-4f99-918e-7a976bda7231"
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
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vOlAESiZOkDhIL4hSUJAQGZ+As1l9R1DkVRIIWSuAwUg98XgJQ+SETgQzBxgURbhtBciYjPi19z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\nYII=\n"
          }
        }
      ],
      "source": [
        "_, ax = plt.subplots(2, 1, figsize=(10, 3))\n",
        "\n",
        "for ind, volt in enumerate([voltages[0], voltages[-1]]):\n",
        "    charge_data[\"charge_mnt\"].electrons.sel(x=0, voltage=volt).plot(ax=ax[ind], grid=False)\n",
        "    ax[ind].set_title(f\"Bias: {volt:1.1f} V\")\n",
        "    ax[ind].set_xlabel(\"y (um)\")\n",
        "    ax[ind].set_ylabel(\"z (um)\")\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "id": "df741a9d"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Optic Simulations\n",
        "\n",
        "Having obtained free carrier solutions in the modulator cross section we\n",
        "can now turn to setting up optic simulation that will use these results.\n",
        "\n",
        "We will use empiric relationships presented in [M. Nedeljkovic, R. Soref\n",
        "and G. Z. Mashanovich, “Free-Carrier Electrorefraction and\n",
        "Electroabsorption Modulation Predictions for Silicon Over the 1–14- μm\n",
        "Infrared Wavelength Range,” IEEE Photonics Journal, vol. 3, no. 6,\n",
        "pp. 1171-1180, Dec. 2011](https://doi.org/10.1109/JPHOT.2011.2171930),\n",
        "that state that changes in $n$ and $k$ of Si can be described by\n",
        "formulas\n",
        "$$ - \\Delta n = \\frac{dn}{dN_e}(\\lambda) (\\Delta N_e)^{\\alpha(\\lambda)} + \\frac{dn}{dN_h}(\\lambda) (\\Delta N_h)^{\\beta(\\lambda)}$$\n",
        "$$ \\Delta \\left( \\frac{4 \\pi k}{\\lambda} \\right) = \\frac{dk}{dN_e}(\\lambda) (\\Delta N_e)^{\\gamma(\\lambda)} + \\frac{dk}{dN_h}(\\lambda) (\\Delta N_h)^{\\delta(\\lambda)}$$\n",
        "where $\\Delta N_e$ and $\\Delta N_h$ are electron and hole densities, and\n",
        "parameters have the following values for wavelength of 1.55 $\\mu$m:\n",
        "\n",
        "| $\\lambda$ | $\\frac{dn}{dN_e}$ | $\\alpha$ | $\\frac{dn}{dN_h}$ | $\\beta$ | $\\frac{dk}{dN_e}$ | $\\gamma$ | $\\frac{dk}{dN_h}$ | $\\delta$ |\n",
        "|-------|-----------|------|------------|------|-----------|------|-----------|------|\n",
        "| $1.55$ | $5.40 \\times 10^{-22}$ | $1.011$ | $1.53 \\times 10^{-18}$ | $0.838$ | $8.88 \\times 10^{-21}$ | $1.167$ | $5.84 \\times 10^{-20}$ | $1.109$ |"
      ],
      "id": "a6858422-d3e4-4f51-a32e-bc47f0d22e96"
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {},
      "outputs": [],
      "source": [
        "ne_coeff = -5.4e-22\n",
        "ne_pow = 1.011\n",
        "\n",
        "nh_coeff = -1.53e-18\n",
        "nh_pow = 0.838\n",
        "\n",
        "k_factor = wvl_um * 1e-4 / 4 / np.pi  # factor for conversion from absorption coefficient into k\n",
        "\n",
        "ke_coeff = k_factor * 8.88e-21\n",
        "ke_pow = 1.167\n",
        "\n",
        "kh_coeff = k_factor * 5.84e-20\n",
        "kh_pow = 1.109"
      ],
      "id": "a9a0967d"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Given the nonlinear character of these dependencies we will incorporate\n",
        "them as sampled function on a rectangular grid formed by electron and\n",
        "hole density values. Specifically, we will sample the given $n$ and $k$\n",
        "dependencies in the electron and hole density ranges up to $10^{20}$\n",
        "1/$\\text{cm}^3$."
      ],
      "id": "3d7e4316-0926-4541-bdf2-2abbc03046ca"
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {},
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Max electron density exponent: 20\n",
            "Max hole density exponent: 20"
          ]
        }
      ],
      "source": [
        "max_electron_exp = np.ceil(\n",
        "    np.log10(charge_data[\"charge_mnt\"].electrons.sel(x=0, y=2, z=0, method=\"nearest\").values.max())\n",
        ")\n",
        "max_holes_exp = np.ceil(\n",
        "    np.log10(charge_data[\"charge_mnt\"].holes.sel(x=0, y=2, z=0, method=\"nearest\").values.max())\n",
        ")\n",
        "\n",
        "print(f\"Max electron density exponent: {max_electron_exp:.0f}\")\n",
        "print(f\"Max hole density exponent: {max_holes_exp:.0f}\")"
      ],
      "id": "335d3a60"
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {},
      "outputs": [],
      "source": [
        "Ne_range = np.concatenate(([0], np.logspace(15, max_electron_exp, 20)))\n",
        "Nh_range = np.concatenate(([0], np.logspace(15, max_holes_exp, 21)))\n",
        "\n",
        "Ne_mesh, Nh_mesh = np.meshgrid(Ne_range, Nh_range, indexing=\"ij\")\n",
        "\n",
        "dn_mesh = ne_coeff * Ne_mesh**ne_pow + nh_coeff * Nh_mesh**nh_pow\n",
        "dk_mesh = ke_coeff * Ne_mesh**ke_pow + kh_coeff * Nh_mesh**kh_pow"
      ],
      "id": "4bac8948"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Now we convert sampled values of $n$ and $k$ into permittivity\n",
        "$\\varepsilon$ and conductivity $\\sigma$ values, and assemble a\n",
        "non-dispersive medium with perturbations (`PerturbationMedium`)."
      ],
      "id": "545b65be-e49e-4ee2-bbc5-4d256ce4440c"
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {},
      "outputs": [],
      "source": [
        "dn_data = td.ChargeDataArray(dn_mesh, coords=dict(n=Ne_range, p=Nh_range))\n",
        "dk_data = td.ChargeDataArray(dk_mesh, coords=dict(n=Ne_range, p=Nh_range))\n",
        "\n",
        "n_si_charge = td.CustomChargePerturbation(perturbation_values=dn_data)\n",
        "k_si_charge = td.CustomChargePerturbation(perturbation_values=dk_data)\n",
        "\n",
        "n_si_perturbation = td.ParameterPerturbation(\n",
        "    charge=n_si_charge,\n",
        ")\n",
        "\n",
        "k_si_perturbation = td.ParameterPerturbation(\n",
        "    charge=k_si_charge,\n",
        ")\n",
        "\n",
        "si_perturb = td.PerturbationMedium.from_unperturbed(\n",
        "    medium=si_non_perturb,\n",
        "    perturbation_spec=td.IndexPerturbation(\n",
        "        delta_n=n_si_perturbation,\n",
        "        delta_k=k_si_perturbation,\n",
        "        freq=freq0,\n",
        "    ),\n",
        ")"
      ],
      "id": "31cfd465"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Circuits Structures\n",
        "\n",
        "For generating the entire circuit we use helper functions for creating a\n",
        "single waveguide and a waveguide y-junction (see tutorials [Defining\n",
        "common integrated photonic\n",
        "components](https://www.flexcompute.com/tidy3d/examples/notebooks/PICComponents/)\n",
        "and [Waveguide Y\n",
        "junction](https://www.flexcompute.com/tidy3d/examples/notebooks/YJunction/))."
      ],
      "id": "75ec31e9-a39c-40eb-a0c6-0905c63f86c4"
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {},
      "outputs": [],
      "source": [
        "def make_y_junction(\n",
        "    x0,\n",
        "    y0,\n",
        "    z0,\n",
        "    wg_thickness,\n",
        "    wg_spacing,\n",
        "    wg_length_in,\n",
        "    wg_length_out,\n",
        "    bend_length,\n",
        "    direction,\n",
        "    medium,\n",
        "    sidewall_angle=0,\n",
        "):\n",
        "\n",
        "    w1, w2, w3, w4, w5 = 0.5, 0.5, 0.6, 0.7, 0.9\n",
        "    w6, w7, w8, w9, w10 = 1.26, 1.4, 1.4, 1.4, 1.4\n",
        "    w11, w12, w13 = 1.31, 1.2, 1.2\n",
        "\n",
        "    l_junction = 2\n",
        "    if wg_length_in < l_junction:\n",
        "        raise ValueError(f\"'wg_length_in' cannot be less than {l_junction}.\")\n",
        "\n",
        "    slab_bounds = (z0, z0 + wg_thickness)\n",
        "    h_bend = (wg_spacing - w13 + w1) / 2\n",
        "\n",
        "    x1 = x0 - direction * wg_length_out\n",
        "    x2 = x1 - direction * bend_length\n",
        "    x3 = x2 - direction * l_junction\n",
        "    x4 = x2 - direction * wg_length_in\n",
        "\n",
        "    y_out = y0 + wg_spacing / 2\n",
        "    yb = y0 + w13 / 2 - w1 / 2\n",
        "\n",
        "    bend_dir = (direction, 0)\n",
        "\n",
        "    # input straight\n",
        "    wg_in = pf.Path(origin=(x4, y0), width=w1).segment(endpoint=(x3, y0))\n",
        "\n",
        "    # junction taper\n",
        "    x_j = np.linspace(x3, x2, 13)\n",
        "    w_j = np.array([w1, w2, w3, w4, w5, w6, w7, w8, w9, w10, w11, w12, w13])\n",
        "    x_poly = np.concatenate((x_j, x_j[::-1]))\n",
        "    y_poly = y0 + np.concatenate((w_j / 2, -w_j[::-1] / 2))\n",
        "    junction = pf.Polygon(list(zip(x_poly, y_poly)))\n",
        "\n",
        "    # bends\n",
        "    bend_up = pf.Path(origin=(x2, yb), width=w1).s_bend(\n",
        "        (direction * bend_length, h_bend), direction=bend_dir, relative=True\n",
        "    )\n",
        "    bend_down = pf.Path(origin=(x2, y0 - (yb - y0)), width=w1).s_bend(\n",
        "        (direction * bend_length, -h_bend), direction=bend_dir, relative=True\n",
        "    )\n",
        "\n",
        "    # output straights\n",
        "    straight_up = pf.Path(origin=(x1, y_out), width=w1).segment(endpoint=(x0, y_out))\n",
        "    straight_down = pf.Path(origin=(x1, y0 - (y_out - y0)), width=w1).segment(\n",
        "        endpoint=(x0, y0 - (y_out - y0))\n",
        "    )\n",
        "\n",
        "    polygons = pf.boolean(\n",
        "        [wg_in, junction, bend_up, bend_down, straight_up, straight_down],\n",
        "        [],\n",
        "        \"+\",\n",
        "    )\n",
        "    assert len(polygons) == 1, f\"Expected 1 polygon, got {len(polygons)}\"\n",
        "    polygon = polygons[0]\n",
        "    assert len(polygon.holes) == 0\n",
        "\n",
        "    geometry = td.PolySlab(\n",
        "        vertices=polygon.vertices,\n",
        "        axis=2,\n",
        "        slab_bounds=slab_bounds,\n",
        "        sidewall_angle=sidewall_angle,\n",
        "    )\n",
        "    return td.Structure(geometry=geometry, medium=medium)"
      ],
      "id": "32b049bd"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Additionally, we create convenience functions to create a rib waveguide\n",
        "and a strip-to-rib taper."
      ],
      "id": "d025bd2a-fe8c-4f32-8f6a-71cc4f5f6a7d"
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {},
      "outputs": [],
      "source": [
        "def make_strip_rib_taper(\n",
        "    x0,\n",
        "    y0,\n",
        "    z0,\n",
        "    x1,\n",
        "    y1,\n",
        "    core_width,\n",
        "    slab_width,\n",
        "    core_thickness,\n",
        "    slab_thickness,\n",
        "    medium,\n",
        "    sidewall_angle=0,\n",
        "):\n",
        "    \"\"\"\n",
        "    This function defines a linear waveguide taper and returns the tidy3d structure of it.\n",
        "\n",
        "    Parameters\n",
        "    ----------\n",
        "    x0: x coordinate of the waveguide starting position (um)\n",
        "    y0: y coordinate of the waveguide starting position (um)\n",
        "    z0: z coordinate of the waveguide bottom surface (um)\n",
        "    x1: x coordinate of the waveguide end position (um)\n",
        "    y1: y coordinate of the waveguide end position (um)\n",
        "    core_width: width of the waveguide core (um)\n",
        "    slab_width: width of the slab (um)\n",
        "    core_thickness: thickness of the waveguide core (um)\n",
        "    slab_thickness: thickness of the slab (um)\n",
        "    medium: medium of the waveguide\n",
        "    sidewall_angle: side wall angle of the waveguide (rad)\n",
        "    \"\"\"\n",
        "\n",
        "    # core\n",
        "    core = make_waveguide(\n",
        "        x0=x0,\n",
        "        y0=y0,\n",
        "        z0=z0,\n",
        "        x1=x1,\n",
        "        y1=y1,\n",
        "        wg_width_0=core_width,\n",
        "        wg_width_1=core_width,\n",
        "        wg_thickness=core_thickness,\n",
        "        medium=medium,\n",
        "        sidewall_angle=sidewall_angle,\n",
        "    )\n",
        "\n",
        "    # slab\n",
        "    slab = make_waveguide(\n",
        "        x0=x0,\n",
        "        y0=y0,\n",
        "        z0=z0,\n",
        "        x1=x1,\n",
        "        y1=y1,\n",
        "        wg_width_0=core_width,\n",
        "        wg_width_1=slab_width,\n",
        "        wg_thickness=slab_thickness,\n",
        "        medium=medium,\n",
        "        sidewall_angle=sidewall_angle,\n",
        "    )\n",
        "\n",
        "    return [core, slab]"
      ],
      "id": "768ee554"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Now we need to create necessary components. Note that we use the medium\n",
        "with perturbation models only for the modulator section (`pin_wg`) as\n",
        "the rest of the structures are assumed to be undoped. Note that we’re\n",
        "recreating the waveguide in the PIN region so that we can use the\n",
        "perturbed silicon."
      ],
      "id": "1e9d52a7-4620-4ec5-8b35-5debad7ae4f1"
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {},
      "outputs": [],
      "source": [
        "# input coupler\n",
        "coupler_in = make_y_junction(\n",
        "    x0=-mzi_length / 2,\n",
        "    y0=0,\n",
        "    z0=0,\n",
        "    wg_thickness=h_core,\n",
        "    wg_spacing=wg_spacing,\n",
        "    wg_length_in=y_length_in,\n",
        "    wg_length_out=y_length_out,\n",
        "    bend_length=y_length_bend,\n",
        "    direction=1,\n",
        "    medium=si_non_perturb,\n",
        "    sidewall_angle=0,\n",
        ")\n",
        "\n",
        "# output coupler\n",
        "coupler_out = make_y_junction(\n",
        "    x0=mzi_length / 2,\n",
        "    y0=0,\n",
        "    z0=0,\n",
        "    wg_thickness=h_core,\n",
        "    wg_spacing=wg_spacing,\n",
        "    wg_length_in=y_length_in,\n",
        "    wg_length_out=y_length_out,\n",
        "    bend_length=y_length_bend,\n",
        "    direction=-1,\n",
        "    medium=si_non_perturb,\n",
        "    sidewall_angle=0,\n",
        ")\n",
        "\n",
        "# bottom arm\n",
        "bot_arm = make_waveguide(\n",
        "    x0=-mzi_length / 2,\n",
        "    y0=-wg_spacing / 2,\n",
        "    z0=0,\n",
        "    x1=mzi_length / 2,\n",
        "    y1=-wg_spacing / 2,\n",
        "    wg_width_0=w_core,\n",
        "    wg_width_1=w_core,\n",
        "    wg_thickness=h_core,\n",
        "    medium=si_non_perturb,\n",
        "    sidewall_angle=0,\n",
        ")\n",
        "\n",
        "# top arm: taper in\n",
        "taper_in = make_strip_rib_taper(\n",
        "    x0=-mzi_length / 2,\n",
        "    y0=wg_spacing / 2,\n",
        "    z0=0,\n",
        "    x1=-pin_length / 2,\n",
        "    y1=wg_spacing / 2,\n",
        "    core_width=w_core,\n",
        "    slab_width=2 * x_side,\n",
        "    core_thickness=h_core,\n",
        "    slab_thickness=h_slab,\n",
        "    medium=si_non_perturb,\n",
        "    sidewall_angle=0,\n",
        ")\n",
        "\n",
        "# top arm: PIN region\n",
        "pin_wg = make_rib_waveguide(\n",
        "    x0=-pin_length / 2,\n",
        "    y0=wg_spacing / 2,\n",
        "    z0=0,\n",
        "    x1=pin_length / 2,\n",
        "    y1=wg_spacing / 2,\n",
        "    core_width=w_core,\n",
        "    slab_width=2 * x_total,\n",
        "    side_width=x_total - x_side,\n",
        "    core_thickness=h_core,\n",
        "    slab_thickness=h_slab,\n",
        "    side_thickness=h_side,\n",
        "    medium=si_perturb,\n",
        "    sidewall_angle=0,\n",
        ")\n",
        "\n",
        "\n",
        "# top arm: taper out\n",
        "taper_out = make_strip_rib_taper(\n",
        "    x0=mzi_length / 2,\n",
        "    y0=wg_spacing / 2,\n",
        "    z0=0,\n",
        "    x1=pin_length / 2,\n",
        "    y1=wg_spacing / 2,\n",
        "    core_width=w_core,\n",
        "    slab_width=2 * x_side,\n",
        "    core_thickness=h_core,\n",
        "    slab_thickness=h_slab,\n",
        "    medium=si_non_perturb,\n",
        "    sidewall_angle=0,\n",
        ")"
      ],
      "id": "c37bff7b"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Before proceeding further into creating an optic simulation, we can\n",
        "combine created structures into a `Scene` object for visualization\n",
        "purposes."
      ],
      "id": "bc4b9f0d-f433-41b7-bb43-e37142328560"
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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          }
        }
      ],
      "source": [
        "scene = td.Scene(\n",
        "    structures=[coupler_in, coupler_out, bot_arm] + taper_in + pin_wg + taper_out,\n",
        "    medium=sio2,\n",
        ")\n",
        "\n",
        "_, ax = plt.subplots(3, 1, figsize=(15, 7))\n",
        "scene.plot(z=z_core, ax=ax[0])\n",
        "scene.plot(z=z_slab, ax=ax[1])\n",
        "scene.plot(x=0, ax=ax[2])\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "id": "24154a4e"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Optic Sources and Monitors\n",
        "\n",
        "Having inspected the geometry we now continue to define other components\n",
        "of an optic simulation. First, we define several auxiliary variables\n",
        "corresponding to: - SiO2 buffer around the circuit, - reduction of\n",
        "simulation in x direction, - location and size of source injection and\n",
        "monitor ports, - width of the injected pulse, and - frequencies at which\n",
        "to measure output signals."
      ],
      "id": "a48147c1-18c5-4880-baf0-a7b6a3693131"
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {},
      "outputs": [],
      "source": [
        "buffer = 1\n",
        "dx = 6\n",
        "\n",
        "port_x = mzi_length / 2 + splitter_length - dx - 1\n",
        "port_y = 0\n",
        "port_z = z_core\n",
        "\n",
        "port_size = (0, 3, 2)\n",
        "\n",
        "fwidth = freq0 / 5\n",
        "freqs = np.linspace(freq0 - fwidth / 10, freq0 + fwidth / 10, 201)\n",
        "wvls = td.C_0 / freqs"
      ],
      "id": "d6007750"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "The propagation of EM pulse in the circuit is triggered by a\n",
        "`ModeSource`."
      ],
      "id": "6de41c3d-12d6-41a3-912c-72ddac3b1528"
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {},
      "outputs": [],
      "source": [
        "src = td.ModeSource(\n",
        "    center=(-port_x - 0.5, port_y, port_z),\n",
        "    size=port_size,\n",
        "    direction=\"+\",\n",
        "    mode_index=0,\n",
        "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
        ")"
      ],
      "id": "34874dfd"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "We will measure mode decompositions in the input port and two output\n",
        "ports. Additionally, we will sample field distribution on the horizontal\n",
        "plane passing through the circuit’s center."
      ],
      "id": "c9224793-1476-403c-b759-fa2cd7decec6"
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {},
      "outputs": [],
      "source": [
        "mnt_in = td.ModeMonitor(\n",
        "    center=(-port_x, port_y, port_z),\n",
        "    size=port_size,\n",
        "    freqs=freqs,\n",
        "    mode_spec=td.ModeSpec(num_modes=3),\n",
        "    name=\"in\",\n",
        ")\n",
        "mnt_out = td.ModeMonitor(\n",
        "    center=(port_x, port_y, port_z),\n",
        "    size=port_size,\n",
        "    freqs=freqs,\n",
        "    mode_spec=td.ModeSpec(num_modes=3),\n",
        "    name=\"out\",\n",
        ")\n",
        "mnt_field = td.FieldMonitor(\n",
        "    center=(0, 0, z_core), size=(effective_inf, effective_inf, 0), freqs=[freq0], name=\"field\"\n",
        ")"
      ],
      "id": "b766e518"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Simulation Assembly"
      ],
      "id": "2547bd44-8ce2-4f5e-91b8-9dd45efc7413"
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {},
      "outputs": [],
      "source": [
        "sim_size = (scene.size[0] - 2 * dx, scene.size[1] + 2 * buffer, scene.size[2] + 2 * buffer)\n",
        "\n",
        "sim = td.Simulation.from_scene(\n",
        "    scene,\n",
        "    center=scene.center,\n",
        "    size=sim_size,\n",
        "    sources=[src],\n",
        "    monitors=[mnt_in, mnt_out, mnt_field],\n",
        "    run_time=6e-11,\n",
        ")"
      ],
      "id": "7dabd147"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Let us perform another visual inspection to ensure the right placement\n",
        "of monitors and sources."
      ],
      "id": "7efce11a-2c66-405d-86b2-00a3f17c29a1"
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
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OrhOtMsCu9eA+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KTHyXPJ4/DnskB/vvsBAAAAyLa8z7/y3g8AQOtz52UAAMiYiQbXPT09mb4Dh/589wMA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\nRb9+/aX0WL9+/fqb/dzVol+//lJ6rF+/f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          }
        }
      ],
      "source": [
        "_, ax = plt.subplots(2, 1, figsize=(15, 7))\n",
        "sim.plot(x=sim.center[0], ax=ax[0])\n",
        "sim.plot(z=sim.center[2], ax=ax[1])\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "id": "ee2dddbc"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "This can also be done using a three dimensional plotting functionality."
      ],
      "id": "834d1efd-2c54-4536-9235-8edc3a66d337"
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "\n",
              "    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"600\" data-simulation=\"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\" ></div>\n",
              "    <script>\n",
              "        \n",
              "        /**\n",
              "        * Simulation Viewer Injector\n",
              "        *\n",
              "        * Monitors the document for elements being added in the form:\n",
              "        *\n",
              "        *    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"800\" data-simulation=\"{...}\" />\n",
              "        *\n",
              "        * This script will then inject an iframe to the viewer application, and pass it the simulation data\n",
              "        * via the postMessage API on request. The script may be safely included multiple times, with only the\n",
              "        * configuration of the first started script (e.g. viewer URL) applying.\n",
              "        *\n",
              "        */\n",
              "        (function() {\n",
              "            const TARGET_CLASS = \"simulation-viewer\";\n",
              "            const ACTIVE_CLASS = \"simulation-viewer-active\";\n",
              "            const VIEWER_URL = \"https://tidy3d.simulation.cloud/simulation-viewer\";\n",
              "\n",
              "            class SimulationViewerInjector {\n",
              "                constructor() {\n",
              "                    for (var node of document.getElementsByClassName(TARGET_CLASS)) {\n",
              "                        this.injectViewer(node);\n",
              "                    }\n",
              "\n",
              "                    // Monitor for newly added nodes to the DOM\n",
              "                    this.observer = new MutationObserver(this.onMutations.bind(this));\n",
              "                    this.observer.observe(document.body, {childList: true, subtree: true});\n",
              "                }\n",
              "\n",
              "                onMutations(mutations) {\n",
              "                    for (var mutation of mutations) {\n",
              "                        if (mutation.type === 'childList') {\n",
              "                            /**\n",
              "                            * Have found that adding the element does not reliably trigger the mutation observer.\n",
              "                            * It may be the case that setting content with innerHTML does not trigger.\n",
              "                            *\n",
              "                            * It seems to be sufficient to re-scan the document for un-activated viewers\n",
              "                            * whenever an event occurs, as Jupyter triggers multiple events on cell evaluation.\n",
              "                            */\n",
              "                            var viewers = document.getElementsByClassName(TARGET_CLASS);\n",
              "                            for (var node of viewers) {\n",
              "                                this.injectViewer(node);\n",
              "                            }\n",
              "                        }\n",
              "                    }\n",
              "                }\n",
              "\n",
              "                injectViewer(node) {\n",
              "                    // (re-)check that this is a valid simulation container and has not already been injected\n",
              "                    if (node.classList.contains(TARGET_CLASS) && !node.classList.contains(ACTIVE_CLASS)) {\n",
              "                        // Mark node as injected, to prevent re-runs\n",
              "                        node.classList.add(ACTIVE_CLASS);\n",
              "\n",
              "                        var uuid;\n",
              "                        if (window.crypto && window.crypto.randomUUID) {\n",
              "                            uuid = window.crypto.randomUUID();\n",
              "                        } else {\n",
              "                            uuid = \"\" + Math.random();\n",
              "                        }\n",
              "\n",
              "                        var frame = document.createElement(\"iframe\");\n",
              "                        frame.width = node.dataset.width || 800;\n",
              "                        frame.height = node.dataset.height || 800;\n",
              "                        frame.style.cssText = `width:${frame.width}px;height:${frame.height}px;max-width:none;border:0;display:block`\n",
              "                        frame.src = VIEWER_URL + \"?uuid=\" + uuid;\n",
              "\n",
              "                        var postMessageToViewer;\n",
              "                        postMessageToViewer = event => {\n",
              "                            if(event.data.type === 'viewer' && event.data.uuid===uuid){\n",
              "                                frame.contentWindow.postMessage({ type: 'jupyter', uuid, value: node.dataset.simulation, fileType: 'hdf5'}, '*');\n",
              "\n",
              "                                // Run once only\n",
              "                                window.removeEventListener('message', postMessageToViewer);\n",
              "                            }\n",
              "                        };\n",
              "                        window.addEventListener(\n",
              "                            'message',\n",
              "                            postMessageToViewer,\n",
              "                            false\n",
              "                        );\n",
              "\n",
              "                        node.appendChild(frame);\n",
              "                    }\n",
              "                }\n",
              "            }\n",
              "\n",
              "            if (!window.simulationViewerInjector) {\n",
              "                window.simulationViewerInjector = new SimulationViewerInjector();\n",
              "            }\n",
              "        })();\n",
              "    \n",
              "    </script>\n",
              "    "
            ]
          }
        }
      ],
      "source": [
        "sim.plot_3d(width=800, height=600)"
      ],
      "id": "0bafd46b"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Applying Carrier Distributions\n",
        "\n",
        "At this point we have created an optic simulation that contains\n",
        "materials with charge perturbation models, however no electron and hole\n",
        "distributions have been provided to it. That is, when we submit such a\n",
        "simulation for solving, all mediums with perturbation models will be\n",
        "considered as regular materials with no perturbations applied. In our\n",
        "case, this corresponds to the case of undoped materials.\n",
        "\n",
        "To obtain simulations in which perturbation models are sampled against\n",
        "provided carrier densities one can use a convenience method\n",
        "`perturbed_mediums_copy()`."
      ],
      "id": "91556c6a-9204-4592-80eb-f624d76d6bad"
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {},
      "outputs": [],
      "source": [
        "def apply_charge(charge_data):\n",
        "    perturbed_sims = []\n",
        "    for n, v in enumerate(charge_data[\"charge_mnt\"].electrons.values.voltage.data):\n",
        "        e_data = charge_data[\"charge_mnt\"].electrons.sel(voltage=v)\n",
        "        h_data = charge_data[\"charge_mnt\"].holes.sel(voltage=v)\n",
        "        perturbed_sims.append(\n",
        "            sim.perturbed_mediums_copy(\n",
        "                electron_density=e_data,\n",
        "                hole_density=h_data,\n",
        "            )\n",
        "        )\n",
        "    return perturbed_sims\n",
        "\n",
        "\n",
        "perturbed_sims = apply_charge(charge_data)"
      ],
      "id": "2918f50b"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "The difference in the permittivity values in the modulator cross-section\n",
        "compared to the undoped case can be visualized as follows."
      ],
      "id": "1982a790-e28b-47a1-89c1-850f7d4818b5"
    },
    {
      "cell_type": "code",
      "execution_count": 34,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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          }
        }
      ],
      "source": [
        "_, ax = plt.subplots(2, 1, figsize=(10, 5))\n",
        "\n",
        "sampling_region = td.Box(center=(0, wg_spacing / 2, port_z), size=(0, 6, 2))\n",
        "eps_undoped = sim.epsilon(box=sampling_region).isel(x=0, drop=True)\n",
        "\n",
        "for ax_ind, ind in enumerate([5, 10]):\n",
        "    eps_doped = perturbed_sims[ind].epsilon(box=sampling_region).isel(x=0, drop=True)\n",
        "    eps_doped = eps_doped.interp(y=eps_undoped.y, z=eps_undoped.z)\n",
        "    eps_diff = np.abs(np.real(eps_doped - eps_undoped))\n",
        "    eps_diff.plot(x=\"y\", ax=ax[ax_ind])\n",
        "\n",
        "    ax[ax_ind].set_aspect(\"equal\")\n",
        "    ax[ax_ind].set_title(f\"Bias: {voltages[ind]:1.1f} V\")\n",
        "    ax[ax_ind].set_xlabel(\"y (um)\")\n",
        "    ax[ax_ind].set_ylabel(\"z (um)\")\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "id": "5e8351d3"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Waveguide Mode Analysis\n",
        "\n",
        "Before proceeding to full-wave simulations one can investigate the\n",
        "influence of applied voltage on the propagation index of waveguide modes\n",
        "in the modulator."
      ],
      "id": "c8a0ab64-a9ae-43b3-a2bf-4784a72df9e5"
    },
    {
      "cell_type": "code",
      "execution_count": 35,
      "metadata": {},
      "outputs": [],
      "source": [
        "from tidy3d.plugins.mode import ModeSolver"
      ],
      "id": "e2ac7ea0"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Let us define a plane for which waveguide modes will be calculated."
      ],
      "id": "eeec617a-0352-47f7-85e1-7b17004600c1"
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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          }
        }
      ],
      "source": [
        "mode_plane = td.Box(center=(0, wg_spacing / 2, port_z), size=port_size)\n",
        "\n",
        "# visualize\n",
        "ax = sim.plot(x=mode_plane.center[0])\n",
        "mode_plane.plot(x=mode_plane.center[0], ax=ax, alpha=0.5)\n",
        "plt.show()"
      ],
      "id": "9e037994"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create a mode solver specification for each carrier distribution. We\n",
        "will consider only the first mode at 11 different frequencies. Also,\n",
        "given that the anticipated changes are small, double precision is turned\n",
        "on for mode solving."
      ],
      "id": "f464a6c9-06b1-4d79-a93d-bbcd353d4a42"
    },
    {
      "cell_type": "code",
      "execution_count": 37,
      "metadata": {},
      "outputs": [],
      "source": [
        "mode_solvers = {}\n",
        "for n, psim in enumerate(perturbed_sims):\n",
        "    ms = ModeSolver(\n",
        "        simulation=psim,\n",
        "        plane=mode_plane,\n",
        "        freqs=np.linspace(freqs[0], freqs[-1], 11),\n",
        "        mode_spec=td.ModeSpec(num_modes=1, precision=\"double\"),\n",
        "    )\n",
        "    mode_solvers[f\"v={voltages[n]}\"] = ms"
      ],
      "id": "1a240d81"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Perform calculation on our servers. Note that since the associated\n",
        "simulation objects contain custom medium data, they are automatically\n",
        "reduced to the mode solver plane for optimizing uploading/downloading\n",
        "data. Setting `reduce_simulation=True` will silence the associated\n",
        "warning."
      ],
      "id": "0763f07c-e16e-46c2-9d5a-4c8bda4d38ec"
    },
    {
      "cell_type": "code",
      "execution_count": 38,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
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              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:14:08 UTC </span>Started working on Batch containing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13</span> tasks.                      \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:14:20 UTC </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.064</span> for the whole batch.                \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</span> to get the billed FlexCredit cost after    \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>completion.                                                        \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"f4701bbd422843e888ecff1dc44f83bd\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:14:39 UTC </span>Batch complete.                                                    \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        }
      ],
      "source": [
        "batch = web.Batch(simulations=mode_solvers, reduce_simulation=True)\n",
        "ms_data = batch.run()"
      ],
      "id": "974d22be"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Let us extract the effective propagation index for the central frequency\n",
        "and visualize its dependence on applied voltage. As expected, increasing\n",
        "the applied voltage results in a more pronounced change in the\n",
        "propagation index and, at the same time, in larger losses in the\n",
        "waveguide."
      ],
      "id": "44a7b297-6954-4a86-abb2-6d485104d29c"
    },
    {
      "cell_type": "code",
      "execution_count": 39,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
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          }
        }
      ],
      "source": [
        "n_eff_freq0 = [md.n_complex.sel(f=freq0, mode_index=0).values for _, md in ms_data.items()]\n",
        "\n",
        "_, ax = plt.subplots(1, 2, figsize=(15, 4))\n",
        "ax[0].plot(voltages, np.real(n_eff_freq0), \".-\")\n",
        "\n",
        "ax[0].set_xlabel(\"Bias (V)\")\n",
        "ax[0].set_ylabel(\"Re[$n_{eff}$]\")\n",
        "\n",
        "ax[1].plot(voltages, np.imag(n_eff_freq0), \".-\")\n",
        "\n",
        "ax[1].set_xlabel(\"Bias (V)\")\n",
        "ax[1].set_ylabel(\"Im[$n_{eff}$]\")\n",
        "\n",
        "plt.show()"
      ],
      "id": "12c7c174"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Using the obtained propagation index values we can compute the\n",
        "associated phase change and loss over the PIN section of the modulator\n",
        "at the central wavelength of 1.55 um. From this information we can\n",
        "estimate the bias $V_\\pi$ required for a phase shift of $\\pi$ to be\n",
        "around 0.95 V. In [Zhou Liang et al 2011 Chinese Phys. Lett. 28\n",
        "074202](https://doi.org/10.1088/0256-307X/28/7/074202) the value of 1.15\n",
        "V was obtained for a similar experimental setup."
      ],
      "id": "0345a61b-62a5-4815-8dad-632c318d1d57"
    },
    {
      "cell_type": "code",
      "execution_count": 40,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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80THh6O5ORk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\nI4/qz5okVAAAAABJRU5ErkJggg==\n"
          }
        }
      ],
      "source": [
        "phase_shift = 2 * np.pi / wvl_um * (np.real(n_eff_freq0) - np.real(n_eff_freq0[0])) * pin_length\n",
        "intensity = np.exp(-4 * np.pi * np.imag(n_eff_freq0) * pin_length / wvl_um)\n",
        "\n",
        "_, ax = plt.subplots(1, 2, figsize=(15, 4))\n",
        "ax[0].plot(voltages, phase_shift / np.pi, \".-\")\n",
        "ax[0].axhline(y=-1, color=\"k\", linestyle=\"--\")\n",
        "\n",
        "ax[0].set_xlabel(\"Bias (V)\")\n",
        "ax[0].set_ylabel(r\"Phase shift ($\\pi$)\")\n",
        "\n",
        "ax[1].plot(voltages, 10 * np.log10(intensity), \".-\")\n",
        "\n",
        "ax[1].set_xlabel(\"Bias (V)\")\n",
        "ax[1].set_ylabel(\"Output power (dB)\")\n",
        "\n",
        "plt.show()"
      ],
      "id": "1c945c12"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Full-wave simulation of the circuit\n",
        "\n",
        "**Note: the cost of running this section is over 15 FlexCredits.**\n",
        "\n",
        "While performing full-wave simulations is not the most cost effective\n",
        "approach for such a simple geometry, we still perform it here for zero\n",
        "and 1 V bias values for demonstration purposes. Alternatively, one could\n",
        "achieve the full-wave simulation accuracy by dividing the problem setup\n",
        "into smaller components and obtaining the S-matrix for each of them\n",
        "using Tidy3D’s\n",
        "[ComponentModeler](https://www.flexcompute.com/tidy3d/examples/notebooks/SMatrix/)\n",
        "plugin. Here, we simply perform the simulation over the entire circuit.\n",
        "\n",
        "For a clearer demonstration let us obtain free carrier distribution for\n",
        "the approximately found $V_\\pi$ of 0.95 V."
      ],
      "id": "16f60697-97c9-42be-95f9-60bf7cc0f27f"
    },
    {
      "cell_type": "code",
      "execution_count": 41,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:15:34 UTC </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'mzi_pin_Vpi_mesh'</span> with resource_id                   \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'vom-e8967922-abbd-4227-8bed-f0c90070c1b9'</span> and task_type           \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'VOLUME_MESH'</span>.                                                     \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Tidy3D's VolumeMesher solver is currently in the beta stage. Cost  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>of VolumeMesher simulations is subject to change in the future.    \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
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              "</script>"
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        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
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        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:15:35 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>get the billed FlexCredit cost after a simulation run.             \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:15:36 UTC </span>status = queued                                                    \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
              "</pre>"
            ]
          }
        },
        {
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          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
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              "</script>"
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        },
        {
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          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
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          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:16:02 UTC </span>starting up solver                                                 \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>running solver                                                     \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:16:03 UTC </span>status = success                                                   \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'mzi_pin_Vpi_solve'</span> with resource_id                  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'hec-56b7f346-5451-49c6-a514-0032813409d8'</span> and task_type           \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'HEAT_CHARGE'</span>.                                                     \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Tidy3D's HeatCharge solver is currently in the beta stage. Cost of \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>HeatCharge simulations is subject to change in the future.         \n",
              "</pre>"
            ]
          }
        },
        {
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          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
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              "</script>"
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          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:16:04 UTC </span>Estimated typical FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. For charge simulations,  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>the billed cost depends on the number of solver iterations required\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>for convergence.                                                   \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.148</span>. This assumes the charge solver     \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>reaches its configured iteration limits for all applied biases. Use\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed FlexCredit cost after a \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>simulation run.                                                    \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:16:06 UTC </span>status = queued                                                    \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"98d19baecefc41c3acb3bb399217835b\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
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        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:16:15 UTC </span>status = preprocess                                                \n",
              "</pre>"
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          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:16:27 UTC </span>starting up solver                                                 \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>running solver                                                     \n",
              "</pre>"
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          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:16:28 UTC </span>status = success                                                   \n",
              "</pre>"
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          }
        },
        {
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          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
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          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"02898404804e42288c4206f248c0e7f2\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
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          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:16:29 UTC </span>Loading results from charge_mzi_pin_Vpi.hdf5                       \n",
              "</pre>"
            ]
          }
        }
      ],
      "source": [
        "bc_v1 = td.HeatChargeBoundarySpec(\n",
        "    condition=td.VoltageBC(source=td.DCVoltageSource(voltage=[0, 0.95])),\n",
        "    placement=td.StructureBoundary(structure=contact_p.name),\n",
        ")\n",
        "\n",
        "boundary_conditions = [bc_v1, bc_v2]\n",
        "\n",
        "charge_sim_95 = charge_sim.updated_copy(boundary_spec=boundary_conditions)\n",
        "\n",
        "charge_data_95 = web.run(charge_sim_95, task_name=\"mzi_pin_Vpi\", path=\"charge_mzi_pin_Vpi.hdf5\")"
      ],
      "id": "460441e8"
    },
    {
      "cell_type": "code",
      "execution_count": 42,
      "metadata": {},
      "outputs": [],
      "source": [
        "perturbed_sim_0_95V = apply_charge(charge_data_95)"
      ],
      "id": "b66bc083"
    },
    {
      "cell_type": "code",
      "execution_count": 43,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
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          }
        }
      ],
      "source": [
        "_, ax = plt.subplots(2, 1, figsize=(10, 5))\n",
        "\n",
        "sampling_region = td.Box(center=(0, wg_spacing / 2, port_z), size=(0, 6, 2))\n",
        "eps_undoped = sim.epsilon(box=sampling_region).isel(x=0, drop=True)\n",
        "\n",
        "for ind in range(2):\n",
        "    eps_doped = perturbed_sim_0_95V[ind].epsilon(box=sampling_region).isel(x=0, drop=True)\n",
        "    eps_doped = eps_doped.interp(y=eps_undoped.y, z=eps_undoped.z)\n",
        "    eps_diff = np.abs(np.real(eps_doped - eps_undoped))\n",
        "    eps_diff.plot(x=\"y\", ax=ax[ind])\n",
        "\n",
        "    ax[ind].set_aspect(\"equal\")\n",
        "    ax[ind].set_title(f\"Bias: {[0, 0.95][ind]:1.2f} V\")\n",
        "    ax[ind].set_xlabel(\"y (um)\")\n",
        "    ax[ind].set_ylabel(\"z (um)\")\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "id": "be3182ed"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "For convenience, we use `Batch` functionality to submit two simulation\n",
        "for solving in parallel."
      ],
      "id": "a74bcbe6-010a-40b1-a939-55d00bccb4c9"
    },
    {
      "cell_type": "code",
      "execution_count": 44,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"5d6868bc215b4178820732b57982f175\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:16:45 UTC </span>Started working on Batch containing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span> tasks.                       \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:16:48 UTC </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">27.215</span> for the whole batch.               \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</span> to get the billed FlexCredit cost after    \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>completion.                                                        \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"c346d48a46cc427181c9f289c907fc67\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">08:27:31 UTC </span>Batch complete.                                                    \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>"
            ]
          }
        }
      ],
      "source": [
        "batch = web.Batch(\n",
        "    simulations={\"Bias: 0 V\": perturbed_sims[0], \"Bias: 0.95 V\": perturbed_sim_0_95V[-1]}\n",
        ")\n",
        "batch_data = batch.run()"
      ],
      "id": "79c9e995"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Let us first visualize the field distribution across the whole circuit.\n",
        "Comparing the two simulations, one can qualitatively observe two\n",
        "effects:\n",
        "\n",
        "1.  power in the output waveguide is drastically changed as bias value\n",
        "    of 0.95 V is close to $V_\\pi$,\n",
        "2.  the signal strength visibly decreases along the PIN section of the\n",
        "    modulator in the case of 0.95 V bias value due to losses associated\n",
        "    with the increased concentration of free carriers.\n",
        "\n",
        "Note that unequal aspect ratio is used for plotting."
      ],
      "id": "bf197be5-a056-4041-af2d-5ac2d357e12b"
    },
    {
      "cell_type": "code",
      "execution_count": 45,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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GRhOuSDOmqGI4bhv5Mr4X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ENs5mR3Mdr900RNf7ziJoaspX5vs4jz3B0D8f5XNP9fBb704GThzAWk05FxERERERERERWRWs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82yhDgBrb77dmPef/wP8v+DjncOlH7/8T8MfHj58R/U3qNHjx49evTo0aNHjx49evTo0eNf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\nExIzuT2+2xwcPyI24+5NOevyZlFxDWgiPbizv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NbDQ512+X++uatdkXgz82+zrLxm0/5piRx3Qb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IhdWEBtbGCrVfSVq9iFedT6JubsGdTWJvbsWdSly9hWC7226soQ5X0NsGGIimP3t2MSufec\npRKYDFufc3GuVNFXrmDn51GXr2BPn0JtbGIeOItaX8eeOIG+eAnbaqKuXsOuLKM6PczJk66fN+Zc\nXx70IQxd/BbmXflbLdTWliv/6pr7eWPDlX9jA3v6DOrKFVf+q1ddHu0O5sTyZP9Ox/WvThsCH1KD\nyjL3N8rGFmx1MFd7dJ7N+NIrp8ksfH3dspFEPGe+jLEZ6+svs7l10S0TaPPzJsUFPSFuHyP9StxG\ncqedELeJtZbLl67e7WIIIYQQQgghhBBCCHFfs9Zy4cLFu10MIYQ4NLnTTojbaHNzi35vyHL9xtsK\nIYQQQgghhBBCCCFuv9XVDUajEciz7MQRs1gM5m4XYxe5q/Tepay10nr7GA6HPPXUU1y6dIkrV65g\nreXkyZO8733v4+GHH77t+W1tbfE7v/M7XLx4kVKpxOOPP87HPvYxfP/gLy634xiHLfPCwkL+kweo\nI8nnuFFT9SxOgAqF0mXqtRW+/23vYS44iSGlSgufgIZp8L6lKn/qkavMv9WgKgHZ6ohLz9Y5361T\nUoY3nl6n+a4S6tFTbumg5y5z7Y99XtxqopXlDUubLL3XQz3ulgNKv36eS0/XON+tU/UyHjuxRet9\nxf4p5tsXuPpUyEvbTXxleGxpy+3/htNu/6++wsVv1TjfqVPzM95waoPme6vwyCmIYrJvX+TKN0Je\nabv9n1jZZP7dgcvfGMyzl3jly2Uu9mtUvYwnTq8z956a2380InvmMpe+XubVboNAGd6wssn8+0PU\no6chTjDPXmb1KY/nNlvU/YxHVzZc/c8tQZKRffcKq98uc367ga8tD863WXr7/7+9O4+TparvPv49\ntXX3rHfjgiDIpqAsooliVB5AxZckCsGVaEyMuCfR5InRBwEfDC7hcUninhf65Ik8IXlcolmERDFK\nohFBBRUkKvt6udtsPb3Vcp4/TlUvMz1zZ+bOvT1z7+f9kpcz91Sd8zunTlXX9K/rdCrvmC2S7ym7\nc7smbze6d+cGWRk9ZqSqrSfWFRy3UfKM0vsmNHFHoIcnR5XJ6PDxGW06tqXgWLeUUfbojKbvyLRt\n95gaia8tlbq2HDmr0hOGZcqR7FRdtf9qavv2UU03I20eqmnr0TWFxw7LDJWU7ayq/otYj2xz+4+U\nYh12xIyiY0ryNgwpm6ypdW9Tjz44qplWqLKf6jGHTav8OF/+liHZ2Zbqv2hoxzZXPhrF2rxlVkPH\nejJjJamZqnlfQ1PbypqoVVQOEm0YrWvkcZn8jW5ZlWRbQ7PbAu2aGpJnpJFKQ2OHtRQe7sqz3bGq\nD3uanq4ozjyNVpoa29JU+JhApuzL1hM1H0o1s7usmXpJ5TDW2FhDQ4+VvLEgb6Ol2e2hdk9XFHqZ\nxsbqGn5M6mKwVunuWLPbAk3PlJXJaHSoqeFNLYWH+jK+UTabqrHNaHYmUqMVaqjc1NBorNKhRqZk\nZGuZGjuMZqcjNVuBSlGi0Y1NRZskM+zLNjIlE5lmdkVqNkPJWI2NNVTekinYFMjGmdKZTLPbQs3W\nQiWZr43jNQ1tTeVvCl2ME4lmtwWamqnIShopNzV6WEvh1kCmFCjd3VRjm9GuXcOKU09DUaxNj6kp\nPCyQNxYpm2qqfq/Vzl3DihNPI+VYGw+rKToilBkOlU231Hww0e7tQ6q2ShoKYm3aUlPlaE/eSCSb\npGrd33THcraiUpBqw2hdYydaeWORFGdq3d/Q5COuPPAybdlY1chRVv5hFSmzSh+ua+r+ULumh5RZ\noy2jsxp7bEvhUUOSZ5TtqmvmLqOJqWE1E19bRmc1fmRLwZFumbh0d0PVu412TQ4rznxtqDS08Yi6\nwsMjmaFQ2a666g9IO3cOq5X4Gopa2nJ4ZwzSR+uqP2y0c/eI0sxopNzShsfUFR0WyAxFSicbaj5k\nNbFzSPU40HAp1oYtdZUe68kbCmWbiZoPJJreVdZ0raRKmGjjlprKj/Nlyr7USnvKS0GqDRtqGjrC\nytsYSYlVsr2lmW2RpmfdEkIbRusaPixWsDWSMimbilV9yNNUPkYbx2oaOiRx5dYqm05UfchTdaas\nOPM1UmlodEtL4SGeTOQrm03VfNRqeqKiVuIrClKNb64r2uTOh2wqUWvSamrnkNLUyPetxjbWFW2y\n8kYDN1cnM1V3Rmq0AnlGGhpuamhLKm/MLW6QTWeq7/I1Wy3J86xKpUTDW2N5FSMTGSUTmeIZT9OT\nZRkjhUGikc0tBWNGpmyU1TK1drvzJUl8hWGiykii8hYrRUZKrRrbjBqzgRrNUJVKrNJQovIhVgqN\nlEmtHVaNaqBaLVIYpqoMtVTekskbcjGmU5nqu115ZqWR4ZYqmxMFm33ZplXWcOdbsxmoFfsaHWmq\nPBorPNSTMZJtWNW3GdVm3TldLsUaHmuptFUyFXdOx7syTe7ojOP4lpqiDUbeeKCsmiiZspraXlYc\nu6XxxjfUVdrszvmslSmdzFTdHqled0vfjYw0NXRIIn/ckzyj+NFUjSl3zkdBqlIp1ujhsUzFk1f2\nFG9P1Jz0NDk5JM/LVI4SjWxtKdjgytOpRM1dnmYmy4oTT6MjTVXGY4WH+W7pqIZV7RGjei1SvRVq\npNxUZTRW6QjjxiCVGg9L9Wqg2UZJlSjW8GhL5a1WZsiTja1aj1pN7aoozdzqlONbagrHJX9DqGw6\nUTKTj0HiSdZow6a6ovFMwZZAWS1TWnVj0GwGyjKjkdGGKhtTBZvccYx3ZGpMuWtzGGQqlWKNHJrP\ntYqvZGeieMbT5ERZvif5fqqxQ5oKRozMsKdsOlU8I83sdjEMVWKVRxJFWyQZIyVWjR29cy0qJaoc\navNbQqPWDqtWzVd1NlIpShRGqYa2pvJCI1kpnrKqT4dqtQIZYzU82lIwnCnY4Mk2M2UNqbYrVJIY\nxXGgkdGGwkqmcLMnG2eyqVTf4Stu+mrFgYaGWiqPJ/KHJRMYpVWruOqpVnXzxDNWwxtb8iuSN+Ip\nnc6UNaXqRP6amXkaGW/Kr1gFY56yhothdnekOPYV+KlKlUSlzZnrg6R40qo566teKykIEoVhpsrm\nRF4omZKnZDJTUvdUnS7J8zL5voshGDWSkdKaVXPKU7MRKEkCVSotheVUpXzFW2utmjs9xU1f9Xqo\ncjlWEKaqHJK5pdM9o+ZOKW56qtdKCoNE5eFE0Xgmr2JkW1ZJVapPh0oST9YaN87lTMHGfJxjqbYz\nVJoYtfJxDkpW0RbJtqyyllTfHajV8mWtUamU9IxzMmOVzHqanYlkjJVnrEa2tORF+ThPZUqbbi55\nXqYs8zS2uaFgRDKRUVa3imeM6jOh4iRQFCVunDdlMr4b5+YuKW74qtUilUqJ/CDV8KGpuwcvee25\nVqtFisJEUTlReVMmL3L7JzNWjRlfzYabC+VKrGgoVbjByGZWNpZqO32lia9mM9DwSFN+aFU+xMom\nVjbtlLda7jhFQ6nCMevudVpWrWlPjWqgzBp5xmpoPJZftvJHjNJZ10Z1VyTjuVUShze4MQpG3Vy1\niTQ7EclmboXCynCiYDiTX5GUSUlVatV8NRuBfN/K9zOVNyYynuRX3DzIEqPZaklRlMjzrMobE3mB\n5EX5cWp4qs+6+7swzBQNpQpGrYyRsliKZ9xca7X8fJwzlbdmsrEkT2ru8pQmnprNQKVSoiDKFI5m\n7fdCkxmjVs1XErvrUHk4UVDO5I9IWdOtStaY9pWlnpLE09BoLC/IFI7n5ZnUmHTlaWoUlVKFlVRB\n/oHIrCUls56a9UA2kzzfqjwau3EcMoqnrGxmNDsVyvetrDWqjLXkBZI/LKV1V0ezGirLjIyxisqp\nguFMXuD6mMwYJU2jRj1UGGYyXqahLamyRPIrbgxsKtVmI0VRKuNlKm9IZTzJC91xShqeWk0XY1hK\nFZYzBaO2WJVNtZ2hjJepUY80MuaWgS5tyZTWJS+Q6rt8WSs1G6FK5VhBZBWOuHG2iZTMGrXqgdLE\nze/KaCwvsAo3GMWTVsaTZnZFCgKrOPY0sqElGatog1FSdX+71ifduZAkRuVKfpyG3VzLmlJcc33w\ng1RZ6mn4kFg2dvO1sdPI862md5dVrrSUtHyNbGnJplI4btSakGSsapOR/MDKWqk8ksgLrbxyPg8m\nfBljVZstaXikqTQ1GtqaKqtL/pBU2+7LD6yq0yUNDTeVZUaVTalscRwm3HFo1AMFgVVp2A1uuMEq\nmZaML9UmQvlBpkY91OjGprLEqLQlUzIteZF7ffH8TM1GoKGRWJIUjWfKWm7/5pSnuBXI9zM3l8Zj\n2UwKRqR42rT7GESpkpav4Y0tWSuF41Iy7Y51fTqU51mlqafycCzjW/nFauOznrJEajYChVEqY6Ty\nhlQ2lbyy1Jp051G96spljcrjiWQlr+Lmqs2kxmwoY6zCKHXzYNRdt+VJzSl3H9Vq+qoMJ7KZVNqY\nz7WSOw6eZ9WoBypXElkrlcbd66sJOnPNGKssMyqPuHEORt1ri+dLtUk3znHT11A+RuG4VTrrxrEx\nFUjGKk18lSqJgkq+TGwktaY7fSyVE6WJr8qmWFnTKByzau725IWZqhMllSux4lag4Y0tZYkrb00a\nGd9d/9PEV1RKOsex2emjH1jNzkQaHm0paXkaOiRRMmsUjFrVd/gKokzVqZKGhltKYl9Dm2OlTXc+\nZrFRq57fIye+ysOxrDWKNmRKZoy8klVtV6ionGp2JtLopoZaNV/Dh6ZqTngKR9z9Wmko0ex0pKHh\nlrzAyo/c/VLWNMpSo1bdVxCm7T4mDU/RxkyNnZ6ikUxT28saHmupOlXShsfUVd8davSxiaoPeyqP\nppqdiBRGiZLYV3k0lqyLLWtJNjVKWp5sZuQH7qteopFMWWzkl61mHo00vLGlyR1D2nBITbMTkcYe\n21J9h6+hrammH4o0NN7S1M6KxjY11KgGGj4kVjzjKRrPFM8YxQ3fzYOWr6ENcTv+5i5P4ZD7W35o\nNNbsdKSxQ5tqTAQaPjzR7CO+ymOppneUNDQaq1ENNLI57/94pta0Jz/M1KwGMp5VlnqyVkoST1Oz\nZU22StreDHV31dctU5OqeTU90vqJjPE0OfOAfvrT/1Ka5F+xYddeQmX/sZLcfdPu3bu1sVjuF3vt\n+uuv1znnnKPIG9WpY7856HDmuWv2a5qI79L73/9+XXzxxata986dOzU5Odn+/dZbb9XLXvYySdL/\n/J//U7/5m53xqFQqOuKII1a1/QMdHzXo42//9m/1yU9+UjfddJNarVbfbc466yx99KMf1SmnnLLX\n7TWbTV122WX6i7/4i3ntbd26VR/96Ef1ile8Yp/XgdXRarX06LZdGjvysD1vDAAAAAAAAGDV3H//\ng+I5FWDfufzyy/WJT3yib9l73vMevec972n//qxnPUvf/va391doBwSSdn3867/+a3sijYyM6Mwz\nz9Txxx8vY4xuuukm/ed//qe+9a1v6elPf7quvfZanX322StuK8syveIVr9A//MM/SJJOO+00nXnm\nmZqdndU//uM/avv27brwwgs1OTmpN77xjfusDqyu7dt36YjNTZWH/EGHAgAAAAAAABwUdu+e1MzM\nzKDDwEHGrsHlMbUPl8c85JBDdNxxxy1p28c+9rH7LI4DFctj9vGa17xG3/3ud/XOd75Tr3zlK1Uu\nl3vKr7vuOr3kJS9RvV7XYYcdpp///OcaHR1dUVsf+9jH9Na3vlWSdMkll+i9731vu2x6elq/9mu/\npm9/+9sKgkC33367nvCEJ+yTOlbqYF0eU+oskdm9PrAxgTxvSGEwojAM9cQTn6AgDJWkNQVeWYdV\nTtFp0dE6athoLMxUSz3dPys9Wm8pMJ4eNxro8SOJDi23lFpPD9cj/Wza00O1lnxj9NjhUCeMpnpM\npanMGt09W9adM0bbak2VfV+PHQl0wkiiQ/L9H6hFunPG7R8YT0cMBzphNNWh5ZY8Y/WLakV35ftH\nvq9jRgIdP5Joa7mlxHq6f7akX1SNHsn3P2ok0PEjnfYfrpf0owmjHY2Wyr6vo0cCHT+a6JBSS3Hm\n6YFaST+fMdpW7+z/+NFUjyk3leT9+8WMp/urTVV8X0eNBDp2JNHmKFGSGT3YiHRv1ejReqLASIdW\nAh09kumQUiJPVo82Qz1Q8/RILZW1VpvLgY4atjqklMrIamcr0IM1o52NVLLSlrKvw4akQ6JEnpGm\nYk8P1T3tbFg100wbSr4OLUuHllOFxqqeenqk4cpn40xjJV+HV6QtpVQlz2o69rSj6Wlb3aqVWlUC\no8cMGW2OMo0EmWYTTztbnrbVpVqcKfKNDq0YbYmsRsNUjdTTo01POxpSPclUCTxtLkmHlDKVfask\nM9rZ8rS7Kc3EVpEnjUVGh5Sshnw37yZjT5OxNNV0vw8HRptK0njobhZmU08TLWkmlpLMaiQwGouk\njaFV4FnFmdHultF0LNUSq8g3Gg2kzSWrkufqnIo9TcXSdMsq8IxGQmljJA35ro1q4mKYjaXMWg2H\nRmOhNBZYGUlNazTZlGqp1EytKr7RcCiNh1aBkVqZ0VQszSZSnEmhJ42F0kggRZ5VYqVq4mJspm5V\nttFAGg2lYd8qldRIjSZaUj2V0sxqLDIaD6WRwMVYSz3tbknV2C01VgmMNkXSaGAVelbV1NNUS5po\nuXEq+0Zbyq4PFT9TPfW0vWE00bJKMqkSuPINYaaSZ9VIPe2OjXY1pXri9t8QSYeU3P6JNdrd8rSr\nKU3HmUJjNF4yOqJsVfYzpdZoV1d5YIw2ltyxHgvdEiZTsa/tTXesU1ltiDxtKUmb8+V0qomnRxtG\nk02r2M4vn0nyPjStEms1EnjaWpY2Rpkbg8TTrqbR7qbrYykw2lqWxgOrSpBpMvY12ZR2Nd1Vr+wb\nHVJ2cy30rGqpp8mW0e6m2ufDhkjaFFlF+VybiI0mW9Js7ObappK0OXLHILXSrpY7DkX5WChtLEnD\nfqbMurk4GUszLTc3xyKjjZE0mh/neuppVz7f08xqvGS0IXTlVlIjL6/m58NwYLShJI0EVoGxamSe\nZmJpqiUlVgqMtCFyc7Hsu2t2LZEmW1ImyZMrHwqkimfVtEaN1JW33Mp1qgRuvlby86GWGM0mbr5L\nUsl351PgSYGxqiVGtUSq5uVBfj4M+VLgWTVSo3rqzrdWviLmcCgNB8rH0Z1vjcydLyVfqvjSeOiW\nBpSk6djVUUvc+Vbx3flUyq8rtcRoJpEaievnUN6H0cCdj63MnW/NVEqtKx8KpLHQ9THJ3HGupW4c\nyp6LcTSUItM5p3c33f6+cce54rvrSiPz1Eil3U13TTBGGgukkfycTyTVE6PJWGqkkrWu/rFAGgqs\nPEnTiVE1ccc6MJ1xLvlWgaSZ/DhMx67+yHPlFd8qNFI9M5qJ82undeM7HEgbQvenWGKNJprumtPM\n5/twIG2I3BhYSbubbpzriVXJd+XjkRuDVNJUy41T3zFIPTUyNwZJfpsxnh/nYd8qtu66t7slJZmr\nYyS/bg4HNr82uzGYjV39kS9tyudaZKyqiYtvKnZzNTDShpI7XpFnVUvdfJ7Ox6Dsu3k4EkqerDLr\nrt1uDNxcj/JzRsZtMx0bNTI31yIjhflcDNxKrW4uJ1LLrdaj0dC1U/GtEmsUZ679NOsch8gv5qLJ\nrwuu/61UKgfFa4fkGRdXI+2cb57J53rex0ZqFFtpJl+kIstjiDwXQyszSqyLoZW6sSt7bgyC/JZ3\nNm+jnuTnsefmomdcG9XE9WMmn4ue52Icym+bW3l8zTQf58DFNxp0YppuSbF141XxXT3jUadPM7E7\n14oYKvl5H/lufrQy10YxjiP5OI4Ero/d45hkxfXE9bOYXzNdx8nt23+cPXeTrA1RcQ1017XEumur\nl/dpQ+T2DzzXRjEXkszVX/JcHMU4zyRSM59LZd+1uyHM4/E6c62Rj0Gxf+RWNFMt7czVLJ9LJd9d\nuzKrnjFopJ22xyMXk7vnctsVc63sdWLJrIu/nuYXAOPGKPRcO638+E7H+faZNBq5c7Psd66n1cTV\nJeX1533IrOt/I5Xi1M0jL78fMnLbzOTHuJq4Nk1XeeC5fVupe30oXl+KPkiujVoiJXLbRb77hO9Y\nPgaeyV8/55QP5fNdcm00ss6YlT23XTmfi5lcfNa6WCtBZ84m+bKgxRikmetH2BVjcXyamdvGN/k5\nkfdlNn9NqMZu2WErdyz9/DrfyjrzLbX5eWpcHH5XH+L8NTTw3fiNh2770HPnm7VuTkV5XCOBm9ue\ncbHFqXuNzvJ9oryPxbGdyudBPXH7mvzaFGcujqnYxd7KX8eDvJ/FXCvmQprXN5wfg2HfjYHJrxtB\nPvfGwk6cxfGfifMxzdz4hvl5J7lxKuZK6Ll2NoTuOjTsu/h84+53KoGLe0Pkthv2O/cw1cRtZ1Xc\nx+TX//ya4smdNyOBW7RtPHRtR17eRl7HcF4+FrjzKPLcfjafD34+vsrnYz117U7ncTbzMUitG+d6\n6lYMn8qvy/X8nLf5a2lild+zubEOvPxeI8iXrvVdmcmvv6HnxmDUrcrfjsHk8Xumc231TOe61kg7\nxzP0OsfIym1TvHbVE3d8bF6e5WOQ/4nrrjtyc9nPr3/F28bFdbl4nc7yMWhmbgxmEjfOjdTNA5uP\nYZrfBxdzzeTHrfhMctl3ZUUffePGYKRrjJr5fK4mbrs0v28td/Whu48l3439WH4ulP38Ps5z/1/y\n3RwsxqDsu757pnPelr3OPIhtp4/FeA7n/74h7LymTsX5NTR2/Yu7YijOueK8KY5j8TpSTzvzNcr7\nuiFyfR8PXZsV371+lPI2RgJ3nHzj6o+zrnmQj/lY6M7BkdDVPRxIOxvuNWmqJR1SdvN7c0na3XJx\nT+dtxPlxsnLzqri2tvJ2ivlXnLuRJ0003WvSrqarc6YlbSm7tsdDaWfTzZuJputfLXVjWEvcWBfz\nJDD5dSJw18GR0PW55LvrxWjo4t9SdmO1KXLxjwTunnc4cHNhLHL9L86lwHNtee6bAJRlrs2ZVqqZ\nJNZuzWiH7tVM8yEZeZqYeli/+MXdStOGJMnaREbmIP9uL5bH3Fe6l8c8ZeyVgw5nnrtnv66J+O59\nsjwm9i1v0AGsRW95y1t022236bWvfe28hJ0knXvuue3E2LZt2/SlL31pRe20Wi1dccUVkqTTTz+9\n/XNhbGxM11xzjaIoUpIk+pM/+ZN9Ugf2jTiOdc89D7g7dwAAAAAAAAD7RBwnuvvue1kWE8C6R9Ku\nj6c//ekKw3DRbV7ykpe0f/7hD3+4onauv/567dixQ5L0u7/7uzJm/lNqRx55pM4//3xJ0le+8hU1\nGo1VrwP7zuxsTQ888PCgwwAAAAAAAAAOSNZK99xzv+I4HnQoOEhlJltz/5G+Xr/4TrsVKpVK7Z/r\n9fqK6vj617/e/vmcc85ZcLtzzjlHX/jCFzQ7O6v//M//1HOe85xVrQMr0/fRepvKZnXFSSrJl2cC\nPfTIo6o3RvW4xx2jR/QjzWa79f3msIzxZW2qWjapRjIhI0932MN04/RhGs6GlSnVjLdbk/Yh1eKd\nMvJ0e7ZFN1WP0Gg2okxWk959msq2qZ7sUpCUdFt2yJz9d2rSPtLefyjffzgbliej3V37+0mkn2aH\naePUYRqylc7+2UOqJbtl5Omn2VaNzzym3f6MN6Fd2T1qJJN5+4e290+VaNrbrsnsYTWSCXkm0E+n\nt+h7M4fP699svF1BUtJPskO1YXqryllFmTLNeI9oJntU9WRSnvFVTjdqfPZQle2QjIxmzYxm7S7V\nkl2SpFIyqpH6VlWyERkZ1U1VVbtLzXRK1mYqJeMaqm3UcDYuSWqaumbtLjWzGaVZS2E8oqHaBg1p\ng3zrKzaxqtqlZjatJK0rjEc0XN+sih3Ny5uqaVK1bFJZ1pLvlTTU2KSKRhXakmLTVF0zqmW7lWZN\neV6kcnNcQxpXpJISpappt+rZlNKsKd8rqVQf05DGFShSpkR1zaiZTSu2dXkmVFQfUsXboMC6DxY0\nVFVs62raWUlSYEoqz44q0pAkKTZNtbKqWrYmK6vAlBSZikoaka9AqRI1VVUrm1Vim/JMpMirqGzG\n5Fm3/klLNTXtrGJbl5FRZIYUeSMKbalvG6GpuG1UkSSlJlHLzirJGkoUKzAlBaasshmRsaanPFUi\nX4ECb0iRqci3gVKTKLENtWxdmXVLOkReRYFKClWWNVapErWyqmLbVKZEpfqwi2ORcSgbN06ePLWM\nq7+ZTcvKylOgSm1ckSryFSlVS3XNqJFNSTZTYEoq1cZU0rA8BUrVUlNVNbKqUtuQZ0KV6mOqaFS+\nIkmZO5a2qjiblTGBSo1hDU1vXLS84m1QZN350DI11bMpxdmsrDJFzVGVZ8dUssPy5ClWQ3VNqZHN\nyNqkb3nNTqhpZ2VtotBUVK6Nq6wReQry/Tt99EzUHoNQZTVMVS07q0Y203cMEtNUw1bdGNo0n0vD\n+RgEypSpoeneuVbvU27rSrK6jPFV8kYUmWFFtuzGoGsuSlKp0XucE9NSM5tpH+eFyot5EpiSSrMj\nilSRkafEtPL2a+25GHnDCkxZgY0Um6Zi21CS1ZTJypNR4A0pNGUFNlRqEqU2VtNW23M1NCWFpqLA\nuPMlsU3Ftq7YNuXJuGNthuWZQL4N1FJdqVpqZa6PnvFVMiPyTShPvlIlvTEYX4EpKzTlfBxTdz7Z\nllLbkm8iBSZSZIblyc/L60ptS4lt5OdbWYFK7Rhj21BiG4pts92HwJQVqaLUJMps0p5HqZK8/ZIi\nMyxJ82OYc05bY/O5VG2/fJZrI/JNSaEtKTEtN47ZtIo/MyKvotAMKbChrLFKbFNNO6vUxvPG2Vij\nlur5daMmI1++CVX2xuQrkGd9tVRToqaaWVVGfnucQ1OWl1/fY9tQK5uVVarIDMk3oUoakTVWmVL3\n2mFbShQrNBX5JlLZjLT71LBVJbahxDYVKFTglRWZ4fYYNGy1fRyXNgbDChQq0pAS01JmEzXsjDKb\ntmMs5kL3cWzZmnwF8+ZaLHdNbmWznbk2OyLPBApsqFgNZUrUymaVyco3oXwTKTKV9n1QbGvt4xyY\nsnwTtOeBJLVsXdYmbr4bX74ChaYizwSyskptU7Ftylq3PlbgleUrUmjKSuXmmjufM2U2VeRV5MnN\neSsra1PFtq5MmVIbt+eqZwIZGaU2VqqWkiz/wJrxFJmKPAUKTElJfi1o5dcU2UyBN5THWVZim7Ky\natqqZDPJeApMpEAlGeNeI1PbVGrjdh+NPJWMu88zMkpsQ5lSF4Nxn5eMTEW+KcnIKLOJEjWV2JYy\nmyo0JRkTKDKV9r1mbGtKrbu+uOMQKDTuumZk2uOc2lZPjIuN89xxbNrZnnGWvHYM7eOQ7++uKwuM\nc97HknH3YoEpKbYNWaVurhlPspkib3jOGMRurGy6aB9j28yvh54ibyR/vQkWnGvdxyG1sRujvA++\nCefNJTfviuPgKTLDyvJ+F3PN2kS+iWRM0D7frE3bx7EQ5Ndl34RKbezGwHb+boxMpX196lcemEi+\nInccbapMSbsPxgR5He6euBgDKVOSNeaVG+MrtU03F4sxyK8LgTofVk3UVGqTrj56Cs2QbP6alqgp\na7P264sxngKVuvaP268NRR88+fJNSdamsrL5OeHGMfCG5MnIN6X2OLfLlbXHz8vftrBulFyMymTk\nuWOV/93l+ujaMG4h3/Y4eyZQZhNZpe58yPf3TSBfUfurDxLFPePoyVOYnwueCRTbmtuuqzzI50En\nhsXHuWln5clz107P7RuaIWX5Em7FfU5nnOceJzcPiu/OCUzZ3ZOYshLrrnctW3djkI+za6PcHudW\n3g+rrH2cinHOlLT7UPy9UDaj+b1TWS07K0++GllVoSkpVaKSGZFVKj8/5738vDX558R9E7mxyMe5\n6GNsm4q8iqzNFHkjSm1TvimplVVljKdWVm+Xh6aiTEneRn4cbCs/jlG7j6ltyshXy9a6xnlIUqbQ\nDCm1TXkK+h6HQKX2tTexnb9NMmWKzFDfPhZjFJmKMlmFptwud/d7Xvt+yZORUf76oaR9vvj52Ltr\nUururdWU5LXv1/rFUMRZzGXJU6BQmRIZ+e354NqPesbRU+D+vjOekqyhwCvL2mxODG6uefKUKVNo\nSspkFShUorhvH904dmJoH4c8Bl/R/D5m7utEUpsoMkNKleTjWJMnX61sVoFXVmJbKpmRrnI3zu51\nyNVfHMeF+pjaRCUz7P4uVZiXB31jKI5t8frX6aObS3F+bJq2qsBESrKGIm9YsW2q7I0ptjUFKqlh\nZ9z5mbchee25UFwvE9twdeR9TGxDkTeiVlZVYMqqZ1OKvGG1sllVauNq2qoq3gY1smlFZqgdQ5pf\nv4vrT1G/tYkyZfJN0D7ORR+b2bQib1j1bEqV2njexiY1smmVvTHVs0lFpqJGVlXkDSuxDZXNqBI1\nFajUnie+CZTYVn4upApUUmzrCkxZzWxagTfUjr9layp7Y5348/LENnr2T9SUJ79nnmU2VWZbSrOW\ne13JmmrFdf38Z7eqWq3mr+uS8teu4vUDANYTnrRboZtuuqn98zHHHLOiOm6//XZJ7osbDzvssAW3\nO/XUU+fts5p1YN/btWuX7rzzLqXpWvxSUgAAAAAAAGB9aTVb+tl/3alqtbrnjQFgneBJuxX68Ic/\n3P75vPPOW1Ed9957ryS3fOViusvvueeeVa9jTyYmJhYsm5ycXFZdB7OZmRn9/Od36eTjt6o0Orzn\nHQAAAAAAAADMMzExpXvvu0fNVnPQoQDKtPYe1OAp0/WLpN0KfPKTn9S///u/S5Je8YpX6OSTT15R\nPdPT05Kk0dHRRbfrLp+ZmVn1OvZk06ZNy9r+YGeVymZNt1yQ8WRt7C6SNtH09IO66cdf05ZNh+sx\nhz9G5UqgJKkrzZemitOaauEuBZ5b9iKOa2rGU0rTqmSMWklVjXBCO3y3NFWzNa1WMqMsralpfDWT\nGc0GOxT4bgmXuDWrVjLTs3893K3Ar8jI9Owv4ytOZ1ULdsj3Sn33j9OaasEu7cjrT+K6GvGE0tQt\n59dKq/P2byZT7fpbSVW1YFc7viSuqxlPKUln5HmhWmlVs/6j8v2yZDO18vaL/RvxlGrBTvleKGM8\nxWldcVJTmtUkZap7Fc0GO3uWoXPj65ZfacSTqvqPKsyXP0ltrDipKbN1t7ySV1HN294en8ymitOa\n0qwhaxN5Xqiat12+V5JnfKU2VpI22uXGBKr5rv++CZXZVElWV5o1lGWxK/d2aNov50sdZUqyupK0\n3q5/1pQ07ZfbS/qkWdMt+5AvhWQUyvdd+5KUZk1lWaIsXyLOGF++F8nz3BI6NkuVZrEy25KUyphI\nngnl+1GnjbSlzMbz2jDGyMib14ZnIncMPL+rjVZXeSjPCzoxWKs0bcoqlrVWxvj5NqGMMe0Y55Ub\nX8bzZa1VlsV5/e4myCiU5/nyvNB9ybTN8uUxEllrNWtC+V60YIzd42TkKbOp0rTZNU6BZr2yPM8t\nyZQpUZI0esr9OeVuHJvtuVBVqCAoy1Mw71hKvmZNqOmgMq88y5qufRPJ991cKuZrmjaU5cvceLCq\nWogAAEWsSURBVKYs34vke26+z41xT+XGRG6JNC/Ml3NqKU1bSrNG3zFw7Td79i/GsCh3x6kzBp4p\n9cy1LIt75vPc8u656JYYjhad78Vx9rxQVtmc+e7KPS/Ir0lZPhcb7Xky73yZN1eNPFPqzMUszZdj\n6fxROLfcHctW11wN5HlBe6kyaxNlWSKbL1XTvzyVVfFdDF77fCiWlXMxFOeD55ZX88J2uTufUlmb\n5kvDdZVLyrLYLbVm4/w8D3vKF43RZvmxTNrj6JnQnbf5OPaLof853WyPc7V7HK11y0VljXZ5EWNv\nef9xNsa4+vO54vYP5HuRZLyu8rQ9V4q5UOw/97pU9NH3o65rTp9x9jvLxLm5VJTP78OiY9CeS53v\nIZ573VtsDLqPYzEGktfTx+4x6CmXJ+P5+Tyx7RiXcpzbc02SjDdnrrmlIz0vaC+X1juXO33snmuu\nj+4qZuRe/z0vnDMXs7w8yOdbfu1Xlp9PneWRXD/c0rTWJnkf4542ihjay2G1x9mdb57n9/TBLfuX\n5OVdfWyPQZaf0147hv4xuj5IpjOOktIslvuTO9lj+eIxFuO0p3FcrFzzjmOnD719nD/Ozbw8a187\nZbyu616qede1Bfvo5qtVJmMCpWlziWNQXNfyPvYchyR/rUjlmbA9zkW/VzzX8te43rm25/LuPhTl\nnePYOQ7Fz26M1D4Oc8vdGGTtGN3YmJ42siztO9e6x8C10Sn38nstV17sX8Tot8d5fh+ynuMwf5xd\njMb4Pd/b3m+c3f/77aWp545zUb7YOBc6MRZ9lDwvyK+Dfs84F+VFjHsa504fusfRxbda49w9Bu64\nJj3jPL88mzfO3cep2Mb3ogXHwCrrGec0i2WMN6cNF2PRxvwxsHPGuSXJ9IxzUe5ew9J8/7Qdv7WZ\nfC9ccAyKcc7y1+U0a80r9/LXaNdG0jMGe+qjZ8JFYug3Bp3jWFyrFutjMdfc//eWF/Oguw/uWBbb\nZHm5ndNGsoRxtu06ij52tzG3j3uKw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          }
        }
      ],
      "source": [
        "_, ax = plt.subplots(2, 1, figsize=(10, 10))\n",
        "\n",
        "for ind, (key, data) in enumerate(batch_data.items()):\n",
        "    batch_data[key].plot_field(\"field\", \"S\", ax=ax[ind])\n",
        "    ax[ind].set_title(key)\n",
        "    ax[ind].set_aspect(\"auto\")\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "id": "ed379794"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "A more quantitative visualization of data can be obtained from the\n",
        "output `ModeMonitor` results."
      ],
      "id": "d554c389-e203-4ea9-b957-356a779306ea"
    },
    {
      "cell_type": "code",
      "execution_count": 46,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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AAABF65nZ72vx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\nYPyciXtdGxsdQ2p6Dj+8clGvSi1eHfAwh1ev+29jSpIkSZIkKT+smAxf3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I4OE+N3LhcaeHKZUKpYw0mP0R/PA0rJ2X+7qK9eGYa+GIsyE6LlTpJEmSJEnS/tq1Eb55BCb/\nFwL7uXldqapQ6XCofBhUOgwqH575kVgxf7NKKhDyupNaIIvL+ncsLkvKCxu2b+a2EY/z+fTx2eYq\nlirH+9c8Q+NDGoQhmSRJkiRJ2h//GfMO93/8XJaxyIhIhl54J2e26xamVCr0gkH47Wv4/unM3Zhy\nU6oatL8y8xGxCRVCFk+SJEmSJOUiPQUmvwLfPArJW3JeU7bWX+Xkw/8qKP9VVC5RNpRJJRUwFpe1\nTxaXJeWlL6ZP4JYRj7Fx++Ys42USSjH8qqc4sm7TMCWTJEmSJEk5CQaDPDbyvzz55atZxmOionnx\nkvs5uWWnMCVTkbNiMnz/FCwYlfuaqBg4rBu0PBcanpD5Z0mSJEmSFDrBIMz7HL6+CzYtzXlNzTbQ\n/cHMz5L0DxaXtU8WlyXltY07tnDz8EcZOWNClvGEuBK8dcVjHHN4UpiSSZIkSZKk/wkGg0yY+zP/\nGfMOE3+bkWUuPiaO1y5/mM5NjgpTOhVpa+fDj0Nh1vt7f8RsYkVofmZmiblac4iICF1GSZIkSZKK\noz+mw+jbYPnPOc+XrQ0n3gtNT/Pf6ZJyVaCLyzfccAOLFy8G4IknnqBevXrZxg/U38+j/WNxWVJ+\nCAQC3P3hUF6Z8F6W8bjoWF657AG6Nj82TMkkSZIkSSreUtPT+HTaWF4YO4z5q5Zkm0+MS+DtgY/T\nvmGrMKRTsbJlJUz8D0x9A9J27X1tlcaZBeYWZ0GpqiGJJ0mSJElSsbFlJYy9N/Mm45zElYaON0K7\nARATH9pskgqdAl1cTkpKYvr06QBMnTqVpKSkbOMH6u/n0f6xuCwpv+T2qNnoyCie638Pp7Y+IUzJ\nJEmSJEkqfrbv3sk7P37Ky+NH8OeW9TmuKZNQinevfopWdZqGOJ2KtV0bM8vLM4fBhn1sahIRCQ26\nZJaYDz/ZN0slSZIkSfo3MtLh20fhh6chPTn7fGQUtL4IOt+a+WQkSdoPed1Jjc6LUP/Ttm1bypYt\nC0Dp0qVzHD9Qfz+PJCm8IiIiuKnnpZSKT+Dej57dM54eyOCK1+5ie/JOzj/21PAFlCRJkiSpGFiz\nZT2vTHiPt77/hO3JO3Ndd/RhR/Lg2TdwWPU6IUwnAQkVoMP1cNxg+GMqzHwXfv0IkrdkXxsMwG9j\nMz/iy0CrvtDpJijhhhySJEmSJB2Q1J3w/kWwYHTO84edCCcOgcqHhTaXJP1Dnu64rILBHZclhcLb\nP3zKTcMf4Z8/Ru7ufTVXnHBemFJJkiRJklR0LVy9lBfGDeOjyV+RlpGe45rIiEh6tOrElV37ckTt\nRiFOKO1FWjIsHA0zh8OicRDIyH1tYkU48f7MXZgjIkKXUZIkSZKkwmrHOnj7LFg1I/tc1aZw0gNQ\nv1Poc0kqEvK6k2pxuQiyuCwpVD6ZOoarX7+X9H+80TT45Iu5scclRPjGkiRJkiRJB2R3ajLrt21i\nw/bNbNi+ac/XU3+fzbjZP+V6XImYOM5p35PLj+9D7Uo1QphYOgjb18KvH2SWmNfMyX1d7aOg55NQ\ntUnoskmSJEmSVNisXwRv9YbNy7KOl6wMx98Frc6DyKiwRJNUNFhc1j5ZXJYUSmN+/YFLX76dlPTU\nLOOXdT6He8+8xvKyJEmSJEl/EwwG+XHhNH5e9Asbtm3aU05e/1dReUfyrgM6X/mSZbm405n069Cb\nCiXL5k9oKT/9+WtmgXnW+7BzQ/b5yChodzl0vhXiS4c+nyRJkiRJBdnySfDO2bB7c9bxas3h/A+g\ndLXw5JJUpFhc1j5ZXJYUaj8umMYFL9zIrpTdWcb7tO/J431vIco79yRJkiRJ4tcVC7j7g6H8vGjm\nvz7XoZUO4fLj+3DWUSeTEBufB+mkMEtLhh+ehu+fgPSU7POlqkK3B6FZb/BGeUmSJEmSYM6n8OGl\n2f8d3aALnPMWxJUKSyxJRY/FZe2TxWVJ4TD99zmc+9x1bN21Pct4z1ZdeOqC2ygZnximZJIkSZIk\nhdfarRt46LMXee/nL/m3L8e2PLQxV57Ql+4tO3ijsIqmTUvhy5tg4dc5z9ftAD2fgEoNQ5tLkiRJ\nkqSCIhiEif+Br27P/PrvWp0PpzwNUTFhiSapaCrQxeUbbriBxYsX59XpAHjiiSeoV69enp6zqLO4\nLClc5v2xiLOGDmLD9qyPICmbUJqLO53JxZ3OonzJMmFKJ0mSJElSaO1OTebl8SMY+tWb2Z5SlJvo\nyCgqlipPpdLlqFi6fObXpcpRsVR52tRvzpF1mhLhbrMq6oJBWDAKvrwZtqzIPh8VA0dfDR1vhFhv\nlpckSZIkFSOBDBh9K/z8Yva5LrdDx5t8UpGkPFegi8tJSUlMnz49r04HwNSpU0lKSsrTcxZ1Fpcl\nhdOStSs46+mrWbV5bba5hLgSnH/sqVzepQ/VylUOQzpJkiRJkvJfMBjks2njuP+T/7Bq05oc13Rq\n3I4uzdpTqVR5KpUuT8VS5ahUujxlE0pbTJb+J3UXfPc4/DgUMtKyz5epCSc/DI16+KasJEmSJKno\nS9sNH1wC877IOh4ZDac+C63OC08uSUVegS4uDxw4kIULF+bV6QB4/vnnadjQR74dCIvLksLtj01r\nOHvoIJaszWFHHCA2OoazjzqZgV37cmilQ0KcTpIkSZKk/DNj6Vzu/uBppv4+O8f5BlUP5Z4zBtGl\nafsQJ5MKsfWLYOQNsOSbnOebnAqnDoUSvhYuSZIkSSqidm6Ad86GlVOzjseVgj5vQ/3O4cklqVgo\n0MVlFQwWlyUVBNt37+TFccN59ZsP2LJrW45rIiMiOSXpeK4+8XwaH9IgxAklSZIkSco7qzev48FP\nn+fDyV/lOF8usTQ39ryM8489lZio6BCnk4qAYBDmfAKjboXtf2afL10DzngZ6h4b+mySJEmSJOWn\njUvgrd6w8fes46WrwwUfQtWm4cklqdiwuKx9srgsqSDZkbyTt77/lBfHDWfdto25rjuh2dFc060f\nSXWbhTCdJEmSJEn/TnJaCs99/Tb/+fptdqelZJuPjozi4k5ncl33iyibWDoMCaUiJmU7THgYfn4e\nAhlZ5yIi4JhrocvtEB0blniSJEmSJOWpZT/D8HNh1z/6FlWaZJaWy9QITy5JxYrFZe2TxWVJBVFy\nWgrv/zyK58a8zYoNq3Ndd0TtxrSp15wjDm3EEbUbcWilQ4iMjAxhUkmSJEmS9s/WXds599nrmL50\nTo7zXZsfw929B1GvSq0QJ5OKgbXz4KPLYfUv2eeqt4Qz/wuVfMKXJEmSJKmQWjkFvn0cFubwdK+6\nHeHctyG+TMhjSSqeLC5rnywuSyrI0jPS+WzaOJ75+i0Wrv59n+tLlyhJi9qHc0TtxhxxaCNa1G5E\njXJViIiICEFaSZIkSZJytmnHVs55ZhC/rliYba5RjXrce8Y1HNeoTRiSScVIeiqMHwI/DoV/vtUR\nkwDdH4akCzN3YpYkSZIkqaALBmHpj/DtY/D7tzmvOaIPnPqsTxqSFFIWl7VPFpclFQaBQICxs39k\n6FdvMmPp3AM6tmKpchxxaGNa1Dqcjo3b0rpe83xKKUmSJElSduu3beSsoYOYv2pJlvEKpcpxS68B\nnHt0T6Iio8KUTiqGlnwHHw2AbTk85atxTzj1GUioEPpckiRJkiTtj2AQFo3N3GF5xaTc13W8Cbrc\n7g26kkKu0BeX58yZw4cffsjMmTPZsGEDu3btYm8Rhg8fTuPGjfMly+bNmxk3bhx//PEHcXFxNGjQ\ngE6dOhEdHZ0n59+9ezfTp09n1apV/PnnnwSDQapWrUq7du2oU6dOnlwjJxaXJRUmwWCQn36bwdDR\nr/PDgmkHdY4Tmh3N/Wddx6GVDsnjdJIkSZIkZbVmy3rOfPoqFq1ZnmW8bf0WvHXl45RJKBWmZFIx\nt2sjfHYtzP0s+1ypanDGS1CvY6hTSZIkSZKUu0AAFnyZucPy6l9yX1ezNXS+DRp0CVk0Sfq7Qltc\n3rlzJwMGDGDYsGEHdNzUqVNJSkrK0ywpKSnceeedDB06lNTU1CxzlStX5plnnuHss88+6PO/++67\nPP/880yZMiXb+f+nY8eOPPPMMzRr1uygr5Mbi8uSCqvVm9cxc9lcflk2n1nL5zNrxQK27tq+X8fG\nRscwsGtfrj7pQhJi4/M5qSRJkiSpOPpj0xrOeOoqlq3/I8v4MYcl8eaVj5EYVyJMySQBmTtUzXgH\nvrwJUndmnz9mEBx/J0THhT6bJEmSJEn/k5EOcz6G756AdfNzX1fnOOh4I9Q9zl2WJYVVoS0u9+7d\nm48//hiABg0a0Lp1a8aMGcOGDRvo1asXABMnTmTDhg0ceeSRHHHEEQDceeed1K5dO89yBAIBTj/9\ndD77LHPXhSOOOIIOHTqwc+dOPv/8c9atWwfAiy++yIABAw7qGv369ePNN98EoGTJknTo0IH69esT\nERHBlClTmDhxIgDx8fGMGjWKTp065cF39v8sLksqKgKBAMvW/8EvyzOLzL8sn8+vKxayOzU512Nq\nlK/KPb0H0aNVJyL8xV2SJEmSlEeWr19F76cG8semNVnGOzVpx2sDHqaEN9FKBceGxfDBxbBqZva5\nas2h94tQtWnoc0mSJEmSio+MNEjdASk7IW3X/3+9YRH89Axs/D33Yxt2zSws12oburyStBeFsrj8\n448/cuyxxwLw+OOPM3jwYCIiIkhKSmL69Ol7dlVOTU3l0Ucf5f777+exxx5j0KBBeZ7l2Wef3XPe\n22+/nSFDhuyZ27ZtGyeffDI//vgj0dHRzJ07l4YNGx7wNfr168fPP//MzTffzLnnnkt8fNY3LUaP\nHk3v3r3ZvXs3VatW5bfffqNUqbx7hKTFZUlFWXpGOovWLOOX5QsYMfELJi+eleO6Yw9P4oGzr6dh\ntTohTihJkiRJKmqWrF3BGU8N5M8t67OMd21+DK9c+iBxMbFhSiYpVxlpMOEh+P6JzJ2Y/6luB2h7\nKRzeHaKiQ59PkiRJklR4ZaTD4nEw51PY8kdmKTltV2YxOXVH5lOAMlIP/LyNe0HHG6D6EXmdWJL+\nlUJZXB48eDBPPfUUnTt3Zvz48XvG/1lc/p9bbrmFRx99lM8//5wePXrkWY7U1FQOOeQQ1q9fT9u2\nbfn555+z7ca5cuVK6tevT2pqKueddx7vvPPOAV9nypQptGzZkpiYmFzXPPnkk1x//fUAvP766/Tr\n1++Ar5Mbi8uSiotgMMjHU77m3o+eZd22jdnmoyOjuKTz2Vx/8sWUKpEYhoSSJEmSpMJuwerfOfPp\nq1i/bVOW8R6tOvP8RfcSG537a4CSCoClP8KHl8HWP3KeL10dWveHpAuhVNXQZpMkSZIkFS7rFsCM\nYfDLCNixNm/OGREJzXpDhxugSqO8Oack5bG87qRG5kWofZk3bx4Affv2zXE+EAhk+fMtt9xCVFQU\n9957b57mGDduHOvXZ+6KMnDgwGylZYCaNWtyyimnAPDpp5+SnJx8wNdp06bNXkvLAL17997z9YwZ\nMw74GpIkiIiIoHfbk/jp3ve54oTziI6MyjKfHsjgxXHDOfrus/hw8mhCcK+OJEmSJKkImbPyN05/\n8spspeXebU7kxYvvs7QsFQZ1joGrfoKmp+c8v201jH8AHmsM7/WDpT/lvEOzJEmSJKl42r0ZJv8X\nXuwEz7SBH4fmTWk5MhqOvACunQ5nvWppWVKxEpLi8rZt2wCoW7dulvHY2MxHKO7atSvLeNmyZalX\nrx7Tpk1jy5YteZZj7Nixe74+4YQTcl33v7mdO3cyceLEPLv+38XFxe35evfu3flyDUkqLkqVSOTu\n3lcz4c53OPbwpGzz67Zt5KrX7+XUJy5nzsrfwpBQkiRJklTYzFw2jzOeuopNO7ZkGe/TvifP9LuL\n6Kjo8ASTdOBKlIOzX4c+70CttjmvCaTD7I/h1W7w3FGZb0qnbA9tTkmSJElSwRDIgEXj4L3+8EhD\n+GIw/DH9wM4REQnxZaBUNahYH6ofAYceDQ1PgOMGw+BZcNpzUKFevnwLklSQheTV9f9tEZ2SkpJl\nvHTp0gCsWrUq2zH/24V51apVlC1bNk9yzJ07F4BKlSpRtWruj3xr3rx5lmM6d+6cJ9f/uylTpuz5\nuk6dOnl+fkkqjhpWq8P71zzLlzO/4e4PhrJqc9a7HCcvnkXXB/txx2kDueKEc3PceV+SJEmSpCmL\nZ3Hec4PZnrwzy/iFx53OQ+fcQGRkSPaDkJSXIiKgSa/Mjz9/hcmvwqz3IG1X9rVr52W+KT3mbjji\nHGjdH6o0yTyHJEmSJKno2rAIZgyHX97NfELP3sSVyny6T+OTIaECxCb+9VEy83N0nP+OlKRchKS4\nXKNGDQBWr876F3rDhg35+uuvmTJlCuedd96e8U2bNrF8+XLg/3dlzgvLli0DoGbNmntd9/f5pUuX\n5tn1/+6JJ57Y83WvXr0O+PjNmzfnOpeXu1RLUmETERFBj1ad6dy0Pc9+9Sb/GfMOqelpe+YDwQD3\nffwsc//4jcf73kqJ2PgwppUkSZIkFTTfz59CvxdvZldK1qekDehyDveccY03wUpFQbXmcOpQOPHe\nzDejJ/83883pf0rZDpNfyfwoXR3qdYL6naF+J0isGPrckiRJkqT8sWExfHYtLP1+32vrdoBW50Hj\nnpkFZUnSAQtJcblVq1YAzJ8/P8t4x44defbZZ3nzzTe5/PLLadSoEenp6QwePJjU1FRKly5N3bp1\n8yzHtm3bAChVqtRe1/19fvv2vH8U3PPPP8/332f+oDv77LNp2rTpAZ/jf7tYS5JylhAbz829BnBW\nu+7c9cHTjJ39U5b5j6Z8zaI1y3jt8kc4pHzuu/BLkiRJkoq+YDDIxN9m8OzXb/HtvMnZ5geddCG3\nnnK5pWWpqClRFo66AtpdDr9/l1lgXvBl5iOB/2nbapg5LPMDMsvP9TtnlplrHwUx3hwvSZIkSYXS\nyqnw9pmwa1Pua8odCi3PzfwoVytk0SSpqIoIBoPB/L7IypUrqVWrFg0bNmThwoV7xlNSUjj88MNZ\ntmwZ0dHRNG/enBUrVrBhwwYArrvuOp588sk8y1GmTBm2bdvGCSecwJgxY3Jdl5qaSlxcHADnnXce\n77zzTp5l+Omnn+jcuTOpqalUr16dWbNmUbHige/MsL9vkmzatIly5cod8PklqagZ/ct3XPPm/Wzb\nvSPLeIVS5Xj1sodo1+CI8ASTJEmSJIVNIBBg7Owfeeart5i+dE6Oa27qeRnXde9vaVkqLraugqmv\nw7Q3YMe6/TsmOh4Obf//ReaqTX0csCRJkiQVBgu/ghH9IG1X9rnYRGhyaubuyrXbQ2RkqNNJUoGx\nefPmPZvt5kUnNSQ7LtesWZM777yTTZs2sXXrVsqUKQNAXFwcI0aMoFu3bmzevJkZM2bsOebYY4/l\n/vvvz9McJUqUYNu2baSmpu51XUpKSpZj8sr8+fM55ZRTSE1NJSEhgY8++uigSsuQ+V9+brZs2ZKn\nO1VLUlHQ7YgOHFatDhe+cBOL1izbM75x+2bOeGogQ84ezIXHne4b0ZIkSZJUDKRlpPPp1LE8N+Zt\nFq7+Pdd1d5w2kKtOPD+EySSFXZkacPwd0PEmmP8FzBgGy36CtN25H5OeDIsnZH4AlKwMrS+CY6+F\n2ISQxJYkSZIkHaDp78BnV2d/6k6tdpB0ITQ5BeJKhiebJBVxIdlxeV/Wrl3LW2+9xbx584iLi6ND\nhw6cddZZREVF5el1GjRowOLFiznyyCOZNm1arutWr15NjRo1gLzb9XnZsmUcc8wxrFq1itjYWL74\n4gu6du36r8+bk7xut0tSUbJ9906uev0evv71h2xzfY85hQfOvp64mNgwJJMkSZIk5bfdqcm8O3Ek\nL4wdxsqNf+a6rm39Flx/8sUc16hNCNNJKrDSkmHFZFjyDSz+Bv78BfbnrZWytaD7w9DoZHdgliRJ\nkqSCIhiE756Acfdln+t4I3S5w3/DSdI/5HUntUAUl0PlhBNOYNy4cVSuXJm1a9fmum7y5Mm0a9cO\ngKFDhzJo0KB/dd3Vq1dz7LHH8vvvvxMdHc3777/Paaed9q/OuTcWlyVp7wKBAI9/+SpPfvlqtrnW\ndZvx3wEPUaXMwe2IL0mSJEkqeLbt3sEb333Ey+NHsGH75lzXdWnankEnXUDb+keELpykwmfnRvj9\n28wS8+IJsPWPva9vcDyc/ChUrB+SeJIkSZKkXAQy4MubYPIrWccjIqDH49D20vDkkqQCLq87qdF5\nEaqwaNKkCePGjWPdunWsW7eOypUr57huzpw5e75u3Ljxv7rm+vXrOf744/n999+JjIzkrbfeytfS\nsiRp3yIjI7mp56U0OaQ+V79xH7tS/v9Rn1N/n82JD/bntcsfplWdJmFMKUmSJEn6u2AwyJQls/ho\n8tes3bohxzUROeyGEwgG+Pm3mWxP3pnjMZERkfQ6sgtXn3QBTQ5pkKeZJRVRiRWgWe/Mj2AQNiyG\nJRMyS8y//wCpO7KuXzQOnm0HxwyCDtdDbGJ4ckuSJElScZaWDB9eCnM/yzoeHQdnvgpNeoUnlyQV\nQ8Vqx+WRI0fSs2dPAIYNG8a5556b47o+ffowYsQIEhISWL9+PQkJCQd1vc2bN9OpUydmzZpFREQE\nr776Kv379z/o/AdyXXdclqT9M3/VEvq9cBPLN6zKMh4XHcuj593M2UedHKZkkiRJkiSA9Ix0Rv3y\nHS+MHcbMZfPy7Lyx0TGcfdTJXHnCedSpXDPPziupmEveChMegkkvZe7k9U9lDoHuD0HjXj56WJIk\nSZJCZfcWGNYHlv2UdTy+LPQdAYe2D0cqSSo08rqTGtLiciAQ4JtvvuHbb79l8eLFbNu2jYyMHF64\n+5tnn32WBg3yZqeTlJQUatSowcaNGzn66KP58ccfs61ZvXo1devWJSUlhXPOOYd33333oK61fft2\njj/+eKZMmQLA888/zxVXXPGv8u8vi8uSdGA279zK5f+9k+/mT8k2d3GnM7m51wBKlygZhmSSJEmS\nVHztTN7FuxO/4OUJ77Fiw+o8O29iXAIXHncaA47vQ5UyFfPsvJKUxdp58MX12d8U/596nTIfQ1zJ\nnd4lSZIkKV9tWw1vnp7577S/K10dLvwYqjQOTy5JKkQKbXH5119/pW/fvsyePfuAjps6dSpJSUl5\nluPJJ5/k+uuvB+D+++/njjvu2DO3c+dOevbsyTfffENUVBSzZ8+mUaNG2c7x4osvsmHDBuLj47nh\nhhuyze/evZtu3brx3XffAfDUU09x7bXX5tn3sC8WlyXpwKVnpDPkk+d5cdzwbHOl4hO5sMPpXNr5\nbN/UliRJkqR8tnbrBl795gPe/P5jtu7anmfnLV+yLJd2Pov+Hc6gbGLpPDuvJOUqGIRfP4Svboft\na7LPR8VA+6ug440Q503zkiRJkpTn1i2EN0+DrX9kHa90GFz4CZQ9JDy5JKmQKZTF5TVr1tCkSRM2\nbdoEQMmSJTn88MMpV64ckZGRez02L3dcBsjIyKBnz56MHj0agHbt2tGxY0d27tzJxx9/zKpVqwAY\nOnQogwYNyvEchx9+OAsXLqRMmTJs2bIl23y/fv148803ATjssMPo27fvXjPVqVOH88477198V1lZ\nXJakg/fR5K+4/p2HSE5LyTYXGx3DmW27cWXXvtSrUisM6SRJkiSp6Jq/agkvjX+XjyZ/RVpGeq7r\njm92NGe0OYn4mLg9Y0GyvsT5z5c8S5VI5Mi6zUiIjc/b0JK0P1K2wzePwMTnIZDD32+lq0O3B6Hp\naRAREfp8kiRJklQUrZgMb58Ju7dkHa/VDvqOgITyYYklSYVRoSwu33rrrTz88MOUKFGCZ599lvPP\nP5/Y2Nj8vmyudu/ezU033cQLL7xARkZGlrly5crx1FNPceGFF+Z6/L6Kyx07dtyz2/L+6NKlC+PG\njdvv9fticVmS/p1Zyxdw0Ys3s2rz2hznIyIi6H5EBwZ27UurOk1DnE6SJEmSio5gMMiPC6fx/Nhh\nfDN3Uq7rYqNjOKPtSQzoci6HVa8TwoSSlIfWLYCRN8Lvubx/0OIs6PW0uy9LkiRJ0r81fxS81w/S\nk7OONzoZznoNYkqEJZYkFVaFsrjcpUsXJkyYwAMPPMBtt92W35fbb+vWrePrr79m5cqVxMXF0bBh\nQ7p27UpcXNxejxs6dCjr16+nRIkS3H777dnmX331VZYuXbrfOerXr0+/fv0ONH6uLC5L0r+3ddd2\nXvv2A/77zQds3L4513VHNWjJVSeeT+cmRxHhjjiSJEmStN+27trOpS/fxvcLpua6plxiafp16E3/\nDmdQuUyFEKaTpHwSDMKcT2D0bbBtdfb5Sg3hnLehSqPQZ5MkSZKkwi55G4y7Hya/nPnvr79L6g89\nn4Co6PBkk6RCrFAXl3/88UeOPvro/L5csWdxWZLyzq7UZN6bOJIXxg1nxYYc3kz6S6Ma9RjYtS+n\nJJ1AjP/QkSRJkqS92rB9M32euYbZK3/Lcb52xRoMOL4PZx91Molx7oAjqQhK2QHfPQ4/PQsZaVnn\nYhKg11PQsk94skmSJElSYTTvi8yn3OR0k2jnW6HTLeBmZJJ0UAplcfmKK67gxRdfZPTo0Zx00kn5\nfbliz+KyJOW99Ix0Rs74hufGvM2cXN5YByifWIY29VvQpl4L2tZvQbNahxEbHRPCpJIkSZJUsK3Z\nsp6zhg7itz+zP7HsyDpNubLreZzU4jiiIqPCkE6SQmzdgszHF6+dl33uyAuhx6M+wliSJEmS9mbr\nKhh5A8z/MvtcRGTmjaGt+4c+lyQVIYWyuDxt2jRat27NgAEDePHFF/P7csWexWVJyj/BYJDv50/h\nuTFv88OCaftcXyImjpZ1mtD2rzJzUt1mlCqRGIKkkiRJklTwrNz4J2c+fTXL1v+RZbxVnSbce8Y1\ntK7XPEzJJCmMUnfBF4Nh5vDsc1WbwjlvQcX6oc8lSZIkSQVZIAMmvwxj74fUHdnnyx0Kpz4L9TqE\nPJokFTWFsrgMcOutt/LYY48xfPhwzjrrrFBcstiyuCxJofHL8vn85+t3+HLmNwSCgf06JjIiksaH\n1KdNvea0rX8ERx92JBVL+fe0JEmSpKJvydoVnPX01azavDbL+HGHt+b1Kx4lMc4dRSUVc9PfySww\npydnHY8rBac9B01PC08uSZIkSSpo/vwVPh0Eq2Zkn4uMhmMGQcebIDYh9NkkqQgqtMVlgCeeeIK7\n7rqLLl26cNZZZ9GwYUMSEvb+A6J+/frEx8eHKGHRYHFZkkJr6bqVvDB2OJ9MHcP25J0HdGxsdAzn\ntO/BVV3Pp1bF6vmUUJIkSZLCa/6qJZw19GrWb9uUZbxr82N4+dIHiI+JC1MySSpg1syBERfAhsXZ\n59oNgJOGQLR/Z0qSJEkqplJ3woSHYOJ/Mndc/qeabeCUoVC1SeizSVIRVqiLy1OnTuWGG27g+++/\nP6BjkpKS8jFV0WNxWZLCIyOQwfxVS5i0+BemLJ7F5MWzWLt1w34dGxUZRe82JzLopAupX7V2PieV\nJEmSpNCZtXwB5zwziM07t2UZPyXpeJ7rfw8xUdFhSiZJBVTytsydw+Z8nH2uRis4500o5+tHkiRJ\nkoqZhV/DF9fDlhXZ5+JKQ9d7oPVFEBkZ8miSVNQV2uLyE088wY033siBXs7i8oGzuCxJBUMwGGTF\nxj+ZsngWU5ZkFpl/+3PpXo+JiIig15FduOakC2l8SIMQJZUkSZKk/DFl8SzOe25wtqfTnNO+B0/0\nvZWoyKgwJZOkAi4YhMmvwOhbISMt61yJstD7JTi8W1iiSZIkSdK/krwtc+fkjDQIpEFG+l+fUzPH\n9vw5DQLpmZ9nf5zzzZ0ATU6Fkx+B0tVC+m1IUnFSKIvLEydO5OijjwagVq1a9O3bl+bNm1OuXDki\n93GXS9u2bSlVqlR+RyxSLC5LUsG1acdWpv3+K5MXz+KzaeP4Y9OaXNee1OI4runWj5aHNg5hQkmS\nJEnKG9/Pn8KFL9zE7tTkLOMXdTyDIWcN3ufrgpIk4I/pMKIfbFmefa7p6ZB0AdTt6I5ikiRJkgqe\n1F2wfiGsnffXx1xYOx+2/5k35y9TE3o+7k2dkhQChbK43L9/f9544w3atm3L+PHjSUxMzO9LFmsW\nlyWpcEjLSOfjKV/zzFdvsmRtDo+z+UvHxm25tlt/2jU4InThJEmSJOlfGPPrD1z68u2kpKdmGb/q\nxPO5/dQriYiICFMySSqEdm+Gj66ABaNyni9TE1r2gVbnQfk6oc0mSZIkSRnpsHEJrJsHa+bCuvmZ\nJeVNSzOfJpPXIiLhqCugy+0QVzLvzy9JyqZQFpePO+44fvjhBz766CNOP/30/L5csWdxWZIKl4xA\nBl/MmMDQ0W8wf9WSXNe1a9CS60++iGMPbx3CdJIkSZJ0YD6bNo6Br91NeiAjy/gtvQZwTbd+lpYl\n6WAEg/DTszDmbvjH369Z1Dkus8Dc5BSITQhdPkmSJEnFz7KJMG4IrJwCGan7Xp8Xqh8BpwyFGi1D\ncz1JElBIi8unnHIKn3/+OT/99BPt27fP78sVexaXJalwCgQCjJ39I0+NeoNfls/Ldd0Zbbsx5Kzr\nKJtYOoTpJEmSJGnfRkwcyeC3HyQQDGQZv+/Ma7msyzlhSiVJRcjySfDJQNiwaO/r4kpDs95wZF84\nJAm8aUSSJElSXgkGYfIrMOrmvd9YmZuoGChRPvNzZHTm56gYiIz5x9fR//91TAmo3xlanJ05LkkK\nqUJZXH7iiSe44YYbeO211+jfv39+X67Ys7gsSYVbMBjku/lTeHr0G0xaNDPHNVXLVOKJ82+lS1Nv\nCJIkSZIUfrNXLOSxka8w5tcfs4xHRETw2Lk30/fYU8MTTJKKokAAlk+E6W/D3E8hbffe11c6DI48\nHw7vDuUO9U1+SZIkSQcvPRVG3gDT3ti/9eUOhapNoHKjvz43hgr1IDo2P1NKkvJYoSwub9myhRYt\nWlC2bFkmT55MfHx8fl+yWLO4LElFx8+LZjJ09Bt8O29yjvPnHt2Te864htIlSoY4mSRJkiTB/FWL\neXzkf/ly5rfZ5qIio3jmwjvp3fak0AeTpOIieRvM/hhmvJP5eOZ9iYrJLAlUbAiVGkLF+n99bgDx\nZfI/ryRJkqTCa8c6GN4XVkzKPleyClRpnPWj8uEQmxj6nJKkPFcoi8sAc+fOpVevXtSsWZNXXnmF\nBg0ahOKyxZLFZUkqeqb/Pocbhj3E/FVLss3VKFeFpy64neMatQlDMkmSJEnF0W9/LuXxkf/l8+nj\nc5yPiYrmpUuG0L1lx5DmkqRibd3CzALzL+9mFgoOVKmqmQXm/xWZqzaF2u3doVmSJEkSrP4Fhp0L\nW//IOh5bEs58BRqdHJZYkqTQKJTF5SFDhrBs2TJ27NjBhx9+SCAQoGXLlhx22GEkJCTs9dg777yT\n2rVr53fEIsXisiQVTanpaTz55as8+/XbZAQyss1feNzp3HX6VSTG7/1nqyRJkiQdrCVrV/Dkl6/y\n8dQx5Pay4pF1mnLfmddyZN2mIU4nSQIgIw1+G5tZYl74FQTSD/5cFetD59ug6ekQGZl3GSVJkiQV\nHr9+CJ8MhLTdWcfLHQp9R2TurixJKtIKZXE5KSmJ6dOnH9SxU6dOJSkpKY8TFW0WlyWpaJu5bB6D\n3riPRWuWZZurVbE6T19wB+0btgp9MEmSJElF1vL1q3hy1Gt8MGk0gWAgxzUtajfipp6X0rnJUURE\nRIQ4oSQpRzvWwS/vZRaY1y88uJ2YIXP35S53wOHdwL/jJUmSpOIhkAHj7ofvn8w+V7cjnPM6JFQI\neSxJUugVyuLyOeecw5w5cw7q2Pfee48mTZrkcaKizeKyJBV9yWkpPPr5y7wwbniOu5xd0uksbjvt\nShJi48OQTpIkSVJBkpKWyg8LpvHVrO+Y+vtsIiMiKFOiFKUTSlK6RCnKJJSkTEJpypQoSemEUlk+\nR0ZG8to3H/Dez1+SnsOTXwCaHNKAm3peStfmx1pYlqSCbvcW2LAI1v+W+fl/X29csn87Mx+SBMff\nCfU6WmCWJEmSirLkrfDBJbDw6+xzR10BJz0AUdGhzyVJCotCWVxWaFlclqTiY+qSX7nmzfv5fd3K\nbHN1K9fk6QvuoE39FmFIJkmSJCmctu3ewfg5Exn9y3eMn/MzO1N25fk1Dq9ejxt7XkK3Fh2IjIzM\n8/NLkkIoIw02L4P1f5WZV82EeZ9l7rCWkzrHwgl3Qa22IY0pSZIkKQQ2LIZh52Te5Ph3UbHQ62k4\nsm9YYkmSwqdQFpd//vlntm7dSvv27SldunR+X67Ys7gsScXLrtRkHvr0BV6Z8F6O812bH8O13frT\nqo5PMJAkSZKKsrVbN/D1rB8Y/ct3/LhwGmkZ+7Fz5kFoULU21/e4hF6tulhYlqSibMMiGP8gzP4o\n9zUNu2buwFzdG+clSZKkImHROHjvIkjeknW8ZGU4d5g3L0pSMVUoi8utW7dm2rRpTJ06laSkpPy+\nXLFncVmSiqeJv83g2reGsGLD6hznOzRqw7Xd+3NUg5YhTiZJkiQpv/y+dgWjfvmOr2Z9z/Slc8jP\nl/rqVDqE63tczGmtuxIVGZVv15EkFTBr5sC4IbBgVO5rmpwKXW6HyoeFLJYkSZKkPBQMwk/Pwdd3\nQjCQda5GSzh3OJSpEZ5skqSwK5TF5eOPP57x48czZcoUWrdund+XK/YsLktS8bUzeRf3ffwcb37/\nca5r2tU/gmu796dDozZERESEMJ0kSZKkvLJy459c/cZ9TFo0c7/WVy5dgZNaHMeJLY6lSpmKbN21\nnW27d7Bl13a27drO1t07sn7etZ2tu7ezbdcOqperzLnHnMKZbU8iOio6n78zSVKB9cc0GHs/LPkm\n5/mISGjVF7o9CPE+fVOSJEkqNFJ3wqdXw68fZp9rcRac+izElAh9LklSgVEoi8uXX345L730El9+\n+SXdu3fP78sVexaXJUk/LpjGA58+z8xl83Jdc0TtxlzXvR8nNDvGxztLkiRJhciC1b/T55lr+HPL\n+r2uq1u5Jt2O6ED3IzrS8tDG/t4vScobv/8A4+6DFZNznq9QD/q8A1WbhDaXJEmSpAO3YRG8ez6s\n/cf7yhER0PU+OGZQ5teSpGKtUBaXf/jhB4477jguu+wyXnrppfy+XLFncVmSBBAMBvlhwVSeGvU6\nP+9lF7ZGNepxTbd+9GzV2cc9S5IkSQXc9N/ncN5zg9mya1uO80fUbky3I46j2xEdaFD1UJ+yIknK\nH8Eg/DYGxg2BP2dln48pAacMhSPOCX02SZIkSftn3kj46HJI+cfrTPFl4KxXoWHX8OSSJBU4hbK4\nDDBw4EBeeukl3n//fU4//fRQXLLYsrgsSfqnSYt+YejoN/hm3qRc19SrUovLupxD12bHUK1c5RCm\nkyRJkrQ/vpk7iYteuoXdqclZxlvXbcZpbU7kpBbHUd3f5SVJoRQIwPwvYNz9sP637PNtLobuD0N0\nXOizSZIkScpZRjqMHwLfP5l9rnIjOPcdqNgg9LkkSQVWoSwub926lZSUFJ544gmefPJJevbsyTnn\nnEOLFi0oW7YsUVG57+5YtmxZoqOj8ztikWJxWZKUm5nL5jF09Bt8Nev7va5rXKM+XZq2p3PTo0iq\n24yYKH8WS5IkSeH06bSxXP36vaRlpGcZ79ehNw+efT2RkZFhSiZJEpC2G0beCNPfyj5XoxWc8xaU\nqxX6XJIkSZKy2rkB3rsIfv82+1zzM+DUZyE2MeSxJEkFW6EsLiclJTF9+vSDOnbq1KkkJSXlcaKi\nzeKyJGlf5q9azNDRb/LZ9HHs61eBUvGJHNeoTWaRuUk7qpatFKKUkiRJkgDe+O4jbh3xeLbf3Qef\nfDE39riEiIiIMCWTJOkfpr8NX1wP6VmfDkCJcnDmf6HhCeHJJUmSJAn+mAbDz4dtq7KOR0ZDtweg\n3eXg60ySpBxYXNY+WVyWJO2vxWuW8+zXb/Hh5K/ICGTs1zFNDmlA5yZH0aVpe5LqNiXa3ZglSZKk\nfBEMBnl69Os88vnL2eaGnD2YSzqdFYZUkiTtw+pZ8O75sHlZ1vGICOh4M3S6GSJzfxKnJEmSpDwW\nDMLU1+HLmyAjNetcqaqZT0ip3S482SRJhUKhLC6PHj2ajRs3HtSx3bt33/MNa/9YXJYkHagVG1bz\nweTRTJjzMzOWzd3nLsz/U75kWU5rfQJntTuZ5rUOc6c3SZIkKY8EAgHu/nAor0x4L8t4dGQUQy+8\nk95tTwpTMkmS9sPuLfDR5bBgVPa5+p3hzFchsULIY0mSJEnFTtpu+HwwzByWfe7Qo+HsN6BUlZDH\nkiQVLoWyuKzQsrgsSfo3Nu7YwnfzJjNh7s9MmDuJTTu27NdxDavV4ax23end5kSqlaucvyElSZKk\nIiwtI53r3hrCh5O/yjJeIiaOVy57iOObtQ9TMkmSDkAgAD8OhbH3QjCQda7MIdDnLTjEJ25KkiRJ\n+WbT0synofz5a/a5o6+CrvdCVEzoc0mSCh2Ly9oni8uSpLwSCASYtWIB4+dMZMLcn5m5bN4+d2OO\njIjkuEatObNtN7q17EhCbHxowkqSJElFwK7UZC575XbGzf4py3iZhFK8feXjtKnfIkzJJEk6SL9/\nD+/1h53rs45HxUD3h6HNJeBTvCRJkqR/Lz0Vtv6R+bF+IYy7P/NpKH8Xmwin/QeanR6WiJKkwsni\nsvbJ4rIkKb/8fTfmsbN/Yuuu7XtdXzI+gZ6tunBmu260q38EkZGRIUoqSZIkFT5bd23n/P9cz5Ql\nWXfBqVy6AiMGPU3jQxqEKZkkSf/SttUwoh+smJR9rnpLaN0Pmp8BcaVCnUySJEkqHIJB2L05s5S8\n5Q/YsiL71zvWZq7LTcUGcO4wqHx46HJLkoqEIlNcTk1NZdmyZWzZsoUSJUpQrVo1KlasGI4oRY7F\nZUlSKCSnpTD21594f9KXTJg7iYxAxl7X16xQjT7te3JxpzMpk+CbUJIkSdLfrdz4Jxc+fyPzVi3O\nMl67Yg3ev+YZaleqEaZkkiTlkYw0+PoumPifnOdjE6HZGZkl5hqt3IVZkiRJRU9GGkx6Caa9CVtX\n5bIolxpXIB3SUw7+2k1OydxpOb70wZ9DklRsFfri8siRIxk6dCg//PADKSlZf6A2aNCACy+8kKuv\nvprSpf1BebAsLkuSQm39tk18MnUMH0waxeyVv+11bZmEUlx+fB8u7Xw2JeMTQ5RQkiRJKpiS01J4\nfswwnv3qTXanZX2trHGN+owYNJTKZSqEKZ0kSflgzqfwyUBI2cuTvKo2yywwtzgL4suEKpkkSZKU\nf5ZNhC8Gw9p5ob1uRCSceB8cfbU3B0qSDlqhLS6np6fTr18/hg0bts+1derU4bPPPqNZs2YhSFb0\nWFyWJIXT/FWLeX/SaD6a/BXrtm3MdV35xDJc2bUv/TueQWJciRAmlCRJksIvGAzy1azvufvDoazY\nsDrbfNv6LXjrysd9WokkqWhavwi+ug1+G7P3R1nHlICmp2eWmGu2sWghSZKkwmfHOvjqTvjl3fy/\nVkQElKwKZWtC2UOgXB1ocSZUaZz/15YkFWmFtrh8+eWX89JLLwFQqlQpTj31VI488kgqVKhAcnIy\nixcvZuTIkcydOxeAatWq8csvv1C5cuVQxCtSLC5LkgqC9Ix0vps/hQ8mjearWd+TnJbzo4sqlS7P\noBMv5PzjTiU+Ji7EKSVJkqTQW7RmGXe+/xTfzpuc4/wJzY7mpUsfICE2PsTJJEkKsc0rYPpbMOMd\n2Jb9Rp4sKjfKLDAfegwklM/8iPFmeEmSJBVQgQyY8iqMux+St+bNOWNKZJaSyxwCZWv99flvX5eu\nDtGxeXMtSZL+plAWl3/99VeOOOIIgsEgZ555Ji+99FKuwd9++20uu+wykpOTufrqq3nmmWfyO16R\nY3FZklTQbNu9gze++4jnxwxjy65tOa6pVrYS13bvT5/2PYmNjglxQkmSJCn/bd+9kye+fJX/TniP\n9EBGtvnyJcty+6lX0Kd9TyIjI8OQUJKkMMlIh0VjYerrf+3CHNi/42ISIKHC/xeZE8pDYgUo8bfP\n5WtDjSTwZ6skSZJCZeVU+OJ6WP1LzvNH9IHj74ASZXM5QQ5PGomIyPz916eQSJLCoFAWl2+77TYe\neugh2rdvzw8//LDPN17eeOMN+vfvT6VKlVi7di0R/tA9IBaXJUkF1bbdO3hp3Lu8NP5ddiTvynFN\nzQrVuK77RZzVrhvRUdEhTihJkiTlvUAgwAeTRzPkk/+wftumbPNRkVH079CbG3pcQtnE0mFIKElS\nAbJ1FUx/O3Mn5q1/5M05yxwCLftAy3OhQr28OackSZL0T7s2wph7YfqbkFMdq0pj6PkkHNo+9Nkk\nSfoXCmVxuXv37owePZphw4Zx7rnn7nN9eno6lSpVYsuWLaxYsYKaNWvmd8QixeKyJKmg27RjKy+M\nHcZ/v3mf3anJOa6pU+kQru9xMacmnWCBWZIkSWGREchg1aa1LN+wimXrV7F+2yZKJ5SkYqlyVCxV\nnkqlylOxdDnKJZTO9Ub9X5bP5/YRTzB96Zwc59s3bMUDZw+mUY36+fmtSJJU+AQyYNE4mPYmLByd\n+ee8ULs9tDoPmp4KcaXy5pySJEkq3gIBmPE2jLkbdmW/aZ3YktDlNmg3AKJ88qwkqfAplMXl9u3b\n8/PPP/PTTz/Rvv3+3TXUvHlzZs+ezaxZs2jevHk+JyxaLC5LkgqL9ds28dyYt3nzu49JTkvJcU2d\nSodw9UkXckbbk4iN9h/ykiRJylu7UpNZvn5V5sdfBeVlG/5g+fpVrNz4J2kZ6fs8R1RkFBVKlqVi\nqXJUKl0+s9hcujwbt2/hoylfkdPLbzXKVeHuMwbRs1VnnzYmSdK+bPsTZrwDS76DnesyyyC7Nv67\nMnNMAjQ5BVr1hUOPhn08LVSSJEnK0epZ8MVgWDk15/lmp0O3B6F09dDmkiQpDxXK4vKJJ57ImDFj\n+OCDDzjjjDP2uT4YDFK5cmU2bNjAsmXLqF27dn5HLFIsLkuSCps1W9YzdPSbvPPjp7kWQ2qUr8rA\nrn059+iexMfEhTihJEmSipIVG1bz6Bcv88OCaazduiGk146LjuXKrn25+qQLSIiND+m1JUkqUoJB\nSNkGOzfC7k2Zn/9XaN61KfNj+xpY8g2k7d77ucrWhpZ9oOW5UP7QkMSXJElSIRcMwg9Pw9h7IRjI\nPl+xAfR8Aup1DHUySZLyXKEsLt9www088cQTdOvWjVGjRu1z/RdffEGvXr0oW7YsGzZsICoqKr8j\nFikWlyVJhdXKjX/y9KjXGfHzl2TksmNO5dIVuLLreZx/7GkkxpUIcUJJkiQVdj8vmsnFL97Cpp1b\nQ37tbi06cM8Zg6hdqUbIry1JUrGVvA3mfAozh8Hyn/e9vs6xcNTl0KgH+FQESZIk5SQ9FT67JvN3\nzH+KKQEdb4Kjr4JoN2OSJBUNhbK4PGnSJI466iggs8T84IMPEhOT86Pef/zxR0499VQ2btxI//79\nee211/I7XpFjcVmSVNgtW/8Hz3z1Ju//PIr0XArM5RPLcFmXc7io05mULlEyxAklSZJUGA3/6XNu\nHv5ork/5yEmFUuU4tGINDq1Ug2rlKrNt9w42bt/M+m2b2LB9Mxu2b2bb7h17PUf9KrUZcvZgOjZu\n+2+/BUmS9G9sWAwzh8PMd2Hbqr2vbXo69HoSEsqHJpskSZIKh50b4d2+sOyn7HONekD3h6FcrdDn\nkiQpHxXK4jLAmWeeyYcffghAvXr16NOnD61ataJcuXKkpKSwePFiRo8ezahRowgGg5QpU4ZZs2ZR\nu3btUMQrUiwuS5KKipUb/+T5McMY/tPnpKSn5rimdImSXNzpLC7tfDblS5YJcUJJkiQVBhmBDO77\n6FleGj8i21xUZBQ1ylf5q5x8CLUr1aB2xeqZX1esQakSifs8f3JaChu3b2HDnkLzpj2F5sY16tO9\nZUdio3O+iV+SJIVBIAN+/w5mvAPzRkJ6cs7rSleH3i9BvQ6hzSdJkqSCaf1v8PaZsGlp1vH4snDG\nS3B4t7DEkiQpvxXa4vLOnTvp1asXEyZM2Ofa8uXL8/HHH9Ohgy8EHQyLy5Kkombt1g28MHY4b37/\nMbtTc34jKSGuBH2PPoWz259M4xr1ifBRnpIkSQK27d7BgP/ewTdzJ2Wbu7HnpQw66UJioqLDkEyS\nJBUIu7fAnE8yS8wrp+a85uir4YS7fNS3JElScbb4GxhxASRvzTpeoS70/QAqNQhPLkmSQqDQFpcB\nAoEAr7zyCs8++yxz587NNl+mTBnOPfdcbr/9dmrUqBGqWEWOxWVJUlG1cccWXhk/gle/+YDtyTtz\nXdewWh1Ob92V01p3pXYlf6eQJEkqrpat/4Pz/3MDi9YsyzJeIiaOof3uoteRXcITTJIkFUx/zoaP\nr4Q/Z2Wfq9oUznwVqjQKfS5JkiSF15RXYeQNmU/u+LtDj4Fz34aECuHJJUlSiBTq4vLfrVmzhgUL\nFrB161bi4+OpXr06TZo0ITIyMhxxihSLy5Kkom7rru28/u2HvDx+BJt2bt3r2lZ1mnB66670OvJ4\nKpfxRQNJkqTi4qeF07nk5VvZvHNblvFqZSvxxhWP0aL24WFKJkmSCrT0VBj/APz4NPzzLbToODjx\nPmh3Ofi0L0mSpKIvkAGjb4OfX8g+1+p86PUURMeGPpckSSFWZIrLyj8WlyVJxcXO5F289cMnPD92\nGOu3bdrr2siISI49PInTWnele8uOlC5RMjQhJUmSFHJv//Apt777GOn/2AWn5aGNeeOKR6lSpmKY\nkkmSpEJj6Y/w4WWw9Y/scw26wOkvQKmqoc8lSZKk0EjeBu9fBL+NyToeEQFd74NjBnkzmySp2LC4\nrH2yuCxJKm52pyYzaua3fDJtLN/OnZStoPJPcdGxHN+sPb2OPJ5OTdpZYpYkSSoi0jPSufvDobz6\nzQfZ5k5v3ZUnzr+NErHxYUgmSZIKpd1b4IvB8OuH2ecSysOpz0HjHiGPJUmSpHy2eQW8cxasnZd1\nPCYBzvyvvwNKkoodi8vaJ4vLkqTibOOOLYycMYFPpoxh0uJf9rk+OjKKNvVb0KVpe7o0bc9h1eoQ\n4d3RkiRJhc6WndsY8N87+G7+lGxzt55yOYNOutDf8yRJ0sGZ9T58PhhStmWfO/JC6P4QxHljvCRJ\nUpGwcgq80wd2rs86Xro69H0PqrcITy5JksKowBeXBw4cyMKFC/PsfM8//zwNGzbMs/MVBxaXJUnK\n9MemNXw6dSyfTB3D3D8W7dcxh5SvSpem7Tm+2dEcfdiRJLgjnyRJUoG3eM1yLnzhRpasXZFlvERs\nPP/pfw/dW3YMSy5JklSEbF4BH14Gyydmn6tQN/Nx4Y1Ohsio0GeTJEnSv5eeknnD2heDM7/+uxot\n4bwRULpaeLJJkhRmBb64nJSUxPTp0/PsfFOnTiUpKSnPzlccWFyWJCm7Bat/59OpY/hk6liWb1i1\nX8fERcfS/rBWHN/0aI5v2p7alWrkc0pJkiQdiGAwyNs/fMrdHw5ld2pylrka5arw5pWP0bSmN8RL\nkqQ8EsiAH4bC+CEQSM8+X+5QOGoAtDof4kuHPJ4kSZIOUPJW+G0szB+Z+Tlle/Y1TU6F3i9CbELI\n40mSVFAU+OLyGWecwZw5cw76+OTkZJYvX77nzxaXD5zFZUmSchcMBpm5bC6fTR/PhDkTWbRm+b4P\n+kvDanXo3eZEerc9iUPKV83HlJIkSdqX9ds2MvjtBxk7+6dsc0l1m/H65Q9TqXSFMCSTJElF3qqZ\n8MElsCGXJ3zFlYIjL4B2A6D8oSGNJkmSpH3Yvgbmf5lZVv79e8hIy31thxugyx0QGRm6fJIkFUAF\nvrh8sNLS0njttde4//77WbXq/3dBnDVrFs2bNw9jssLH4rIkSftv+fpVjJszkfFzJjLxtxkkp6Xs\n+yCgfcNWnNG2Gz1bdaZUicR8TilJkqS/+3rW9wx+5yE2bt+cbe6Mtt14vO8txMfEhSGZJEkqNlJ3\nwVe3w5RXc18TEQmNekD7gVC7HUREhC6fJElSUZOyHdJ2Q2xJiClxYL9brV+UWVSePxJWTt33+qhY\nOPVZaNnn4PNKklSEFLniciAQYPjw4dx99938/vvve8a7dOnCgw8+SJs2bcKYrnCyuCxJ0sHZlZrM\nTwunM37ORMbN/ok/Nq3Z5zHxMXGc1OI4zmjbjY6N2xAdFR2CpJIkScXTzuRd3PXB0wz76fNsc4lx\nCdx/1nX0ad+DCEtBkiQpVNbMgYnPw6z3ISM193U1WmYWmJueBlExocsnSZJUmG1dBXM/hTmfworJ\n/z8eGZVZYI4tCXF/fcSWgvhSfxsrlfn72W9jYP1v+3e9klXg8O5w1OVQpVF+fEeSJBVKRaq4/Mkn\nn3DnnXcyd+7cPWNHHXUUDz74IB07dgxXrELP4rIkSf9eMBjktz+XZZaY5/zElMWzSA9k7PWYiqXK\ncXrrEzmj3Uk0q3mYhRlJkqQ8NO332Vz1+r0sW/9HtrnWdZvxXP97qF2pRhiSSZIkATvWZe6+PPm/\nsHN97utKVYN2l0H9zlCiHJQoC3Glffy4JEnS/2xbDXM/g9mfwIpJ+X+9CvWgcU9odDIc0trfyyRJ\nykGRKC6PGTOG22+/nWnTpu0Za9GiBffffz89e/YMdZwix+KyJEl5b8P2zXw2bRwfTh7NzGXz9rm+\nYbU6nNWuO+ce3YvyJcuEIKEkSVLRlJaRzpNfvsbQ0W8QCAayzEVHRnF9j4u5+sQLfPKFJEkqGNKS\n4dcPYeJ/YO3cfa8HiIjMLDCXKJf5kVAO4stmfv7fWOnqULM1lPFGLUmSVARt+zOzrDznr7JyfleZ\narT6q6zcAyo1BDcjkiRprwp1cfmnn37i9ttv57vvvtsz1rBhQ+69917OPvtsdyXMIxaXJUnKX4vX\nLOfDyaP5cPJX/LFpzV7XloiNp0/7HlzW5RwOrXRIiBJKkiQVDUvWrmDga/fwy/LsN47Vr1Kb5y66\nhyNq+9hOSZJUAAWD8Pv3mQXmhV/l3XnLHAK12mZ+1G4HVZqCN3BJkqTCaPuav8rKn8LyiftXVk4o\nD6k7IT3lwK4VGQ11joXGPeDw7t4MJknSASqUxeVffvmF22+/nVGjRu0Zq1WrFnfddRf9+vUjKioq\nvyMUKxaXJUkKjUAgwOQls/hw0mg+nz6e7ck7c10bERFB9yM6cMUJ55FUt1kIU0qSJOWtnxfN5KVx\n77JozTJKxMZTIiaOhLgSJMSWICEunoS4EpSIid/zdUJsfOa62Hhio2OIjY796/P/f8RExRAXHUNM\ndAxx0bHEREfz+fTx3PPhM+xOTc6WoV+H3tzV+2oSYuPD8J+AJEnSAdqwCH5+AWYMh7RdeXvu2EQ4\nJOn/y8y12kC8T/+SJEkF2Np5MOpW+P3b/SsrH3IkND0dmpwC5WpljmWkQcp2SNkBqTv++vqvP6fs\ngNS/vk7bDZUOg8O6Zj7FQpIkHZRCVVxeuHAhd911Fx988AH/u0yVKlW47bbbGDBgAHFxcfl16WLN\n4rIkSaG3OzWZMb/+yIeTR/PN3EmkBzJyXZtUtxlXnHAuJ7U4jqhIb+CSJEmFw9Zd2xnyyX94+4dP\nw5ahcukKPHXB7XRp2j5sGSRJkg7ark0w/W1YPAF2boDdmzM/UnO/Gf6ARURA5UZQqx006QX1Ovno\nc0mSVDAEgzDtTfjyJkjPfqN6FjVaQbP/lZVrhyafJEnKVaEoLi9fvpx7772Xt956i4yMzNJOuXLl\nuOGGG7jmmmtITEzM60vqbywuS5IUXhu2b2bExJG8+s37/Lllfa7rDq10CJd1OYezjzqZxLgSIUwo\nSZJ0YEbN/JZbRzzO2q0bwpah+xEdeKzvrVQoWTZsGSRJkvJFeiokb4Fdm/+/zPy/j12bYddGWDMX\nVs888Mei1+8M3R6CKo3yJbokSdJ+Sd4Gn10Dsz/KfU2Nlv+/s3L5Q0MWTZIk7VuBLy7fc889PPTQ\nQ6SmpgKQmJjINddcw4033kjZsmXz8lLKhcVlSZIKhtT0ND6bNo4Xxw1n7h+Lcl1XLrE0Fx53Ohd1\nPJPKZSqEMKEkSdLerdmynttGPM6oX74LW4bEuASGnD2Yc446mQh3C5QkScVZegqs/gVWTIblk2DF\npMydm/clIhLaXASdb4dEX3uSJEkhtmomvNcPNi3NPlf9CGh6GjQ9FcrXCXEwSZK0vwp8cTkpKYnp\n06cDUL58eQYOHEjlypUP+nxnn302lSpVyqt4xYLFZUmSCpZgMMgPC6bywrjhfDN3Uq7rYqKiOalF\nB849uifHNWpNVGRUCFNKkiT9v0AgwLCfPue+j55le3L2R5fXr1Kbe8+8hkqly7MrJZldqbvZlbKb\n3akpOX69KzWZ3anJpKWnkZqRzv+1d9/hUZV5G8fvmUnvhYSEhCT00HsXEBQUFBXBjm3Fvq67q64i\n7qq8Ku7a2664oghiWxVFUVBR6RAIJfQQAiSQBEgjvc68f0wyJKSHTAp8P9c11zlznuc853cSYJiZ\n+zynqLjIuiwpUnFJsQpLiq1tJcUqKrUuDTLoosgh+vu0BxUeENICPwUAAIBWzmKR0uPLQsxR1iDz\nyX0193fxlsY/Lg2/R3Jwar46AQDAhclikTa9K614Siotrtzm5C5NfVUaeFPL1AYAABqkTQWXm8KW\nLVs0ZMiQJhvvQkBwGQCA1mvf8UOav+pTfbV5hYpLS2rsF+LbXjeOulI3jrpSHf2Dm7FCAABwoYtL\nOapHl7yoTQe3V2lzMJr00OW36eHJd8jF0bkFqgMAAECt8jOsMzKve0s6vLb6Pv5dpMkvSD0ul7ij\nBQAAsIe8dGnpH6V931dtC+oj3fCRFNCt+esCAACNQnAZdSK4DABA63fidKo++O1/+mjNUmXmZdXY\nz2AwaGzkUN08+ipd3n+snB2ZDQcAANhHUUmx/v3Tx3rthw9VWFJUpX1Qp956ZeZs9Qzp2gLVAQAA\noEEsFmnfcmnFnOpvyy5JXcZbA8xBvZu3NgAAcH5L2Cx9/gfpdGLVtmF3Wf//4eja/HUBAIBGa/XB\n5aNHjyo/P7/JxouIiJCLi0uTjXchILgMAEDbkVuQp882LteC375Q/MlqPsCpwM/dW9OHX66bR08l\nMAQAAJrUtsN79MjHL2jf8UNV2tycXfXk1ffpzotnyGQ0tUB1AAAAaLSSQmnTfOm3f0mF1Vw8bzBK\nQ++ULpkjubdr/voAAMD5w2yW1r0h/TJXMpdWbnP2kqa9LfW5pkVKAwAA56bVB5fR8gguAwDQ9lgs\nFm2K26FP1n+n76NXKb+4sNb+AyN66YaRV2hcz2GKCAiVgdt6AgCARiguLdE/l83XOz99rOo+IprQ\ne6T+efPf1NE/uAWqAwAAQJPJOSWtel7aulCymKu2u3hL4x+Xhs2SHJlQCAAANFDOKemre6SDq6q2\nhQySbvhQ8uvU/HUBAIAmQXAZdSK4DABA25aVn6NvtvysJeuXaefRfXX2D/IO0KjuAzWy+yCN7DZQ\nXdqHEWQGAAB1Ssk8pXvff0qb43ZWafPz8NFz1/9F04ZO4v8VAAAA55OU3dIPs6X41dW3ewRKI+61\n3sbdza95awMAAG3TodXSl3dL2SlV20b/UZr4jOTg1OxlAQCApkNwGXUiuAwAwPlj77GD+mT9d/py\n8wpl5lVzO89qBHr5a2T3gRrZbaBGdR+kbkERBI4AAEAla/dv0f0L/qHU7IwqbTOGT9az1z0sfw+f\n5i8MAAAA9mexSPt/lFY8KaXFV9/H0U0afKs06kHJL6JZywMAAG2AxSLFr5HWvCod+q1qu6uvNP1d\nKXJy89cGAACaHMFl1IngMgAA55+C4kKt2LFGn6xfpjX7tzRo33aevhpRFmIeEzlEXduHE2QGAOAC\nZTab9caKhXrpu/dlPusW4cE+AXrttqd0ca/hLVQdAAAAmlVJkbRpvvTbP6XCGi6YNxil3tdIY/5k\nvc07AAC4sJnN0v4fpDWvSMeiq+8TPlK6boHkE9q8tQEAALshuIw6EVwGAOD8djQ1SUujVmp9bLS2\nHtql/OLCBu0f7BOgiyKHamzkUI2JHKIgnwA7VQoAAFqT9JzT+uOHz+jXPRurtF3ca7jevvMZtfPk\nMwQAAIALTm6qdbbELQulopya+0VcZA0wd5skGY3NVh4AAGgFSoulmP9Ja1+XTu6vvo/BII19RJrw\npGRyaNbyAACAfRFcRp0ILgMAcOEoKinWjiN7tfHgdm08uF2b43Yqv6igQWN0C4rQmMghGhs5TKN6\nDJKXq4edqgUAAC1l2+Hduvu9OTqecaLSdoPBoEeuuEt/mXKnTEZTC1UHAACAViE/U9q6UNrwHyk7\nueZ+gZHS6Iek/tdLDs7NVR0AAGgJxflS9GJp3ZtSZkLN/SIuki59SooY1Xy1AQCAZkNwGXUiuAwA\nwIWruLREMUf3a8PBbdoQu01RcTHKLcyr9/5Gg1EDInpqTI8hGttzmEZ0G0CICQCANsxisWjB7//T\ns1++qeLSkkptfh4++s8fntW4XsNbqDoAAAC0SiVF1hkV178lndhbcz+P9lLkZMmrg+QdInkFS15l\nSxdv66yLAACgbSo4LW1+X9rwbyn3VM39IidLY/8qhfH5EgAA5zOCy6gTwWUAAFCupLREuxJjtSF2\nm9bt36pNcTsaNCNziF+Qbh49VTeNmqoOvoF2rBQAADS17Pxc/XXxC/pu26oqbUM799X8u5/n9R0A\nAAA1s1ikgz9L696S4lc3bF8n98pB5vKld6jkGyb5hEkuXvapGwAAnGGxSKXFUkmBVFJYYVm+XlS2\nrLD9xB4p6gOpMKv6MQ1Gqd8MacxfpKDezXs+AACgRRBcRp0ILgMAgJoUFhcp+vBurd2/VWv3b9H2\nI3tVai6tcz+jwagJfUZq5uirdUnfUXI0OTRDtQAAoLH2HY/TrPee1KETVW/hee+lN+mpaQ/yeg4A\nAID6O77deov4Pd9I9fgsqV5cfSTfCGuIuTzM7BtuffiESc4eTXMcAADOdyWFUkaClB4vpR+2PjKO\nlK0fsYaSm4KDszRopnTRnyS/Tk0zJgAAaBMILqNOBJcBAEB9ZefnauPBbVq7f6vW7N+iA0nxde7T\n3rudbhh5hW4ZfZXCA0KaoUoAAM4PFotF24/s0ffbflNGbpZC/NorrF0HdfQPVph/BwX5tJPJaGrw\nuAXFhTqWlqKEtCQlpiUr/mSiFq3+WvnFhZX6ebq46/Xbn9IVA8c31SkBAADgQpNx1HrL+OhFUlGu\nfY/l5m8NNIeNkIbeKQVG2vd4AAC0dpmJUuKWM+Hk8mBy1jHrzMr24uwpDbtLGvWA5Blkv+MAAIBW\ni+Ay6kRwGQAANNaJ06lat3+rft2zUT9s/71K4OlsYyKH6JaLrtbk/uPk7OjUTFUCANC2pOec1leb\nV2jJ+mXan3Soxn6OJgeF+gUprF0H68O/LNTcLljebl46np6ixLRkJaRaA8oJaclKTEvWidOpddbQ\nO7Sb3r/nBXUK7NiUpwYAAIALVX6mdHiddDpRykqWTh+3LrPKlk01s2NFncZIw2dJPa+UTI5NPz4A\nAK1V2iFp1QvSri/tG1A+m5u/NPJ+acTdkiu5EwAALmQEl1EngssAAKApnM7L1tdRK7Vk/TLtToyt\nta+fh4+uGzFZN468Uj1DujRThQAAtF5ms1nrDmzVkvXL9OOO1SoqKW6xWm4ePVXP3/CIXJ1cWqwG\nAAAAXEAsFik/vSzInCSdTrIus5KsM0VmJliXpUWNG9+jvTT0DmnIHZI3dwMDAJzHMo9Jv/9L2rZY\nMpc2fhyjg+TgIjk4V3i4lD2cqmlzlToOkfpfLzm5N935AACANovgMupEcBkAADQli8WinQn7tWTd\nt/o66iflFubV2r9fWA9dP2KKpg27TP4ePs1TJAAArURSxkl9vvF7fbL+OyWmJbdoLa6Ozpp302O6\ncdSVLVoHAAAAUIXZLOWkSBkJUsZRa5g546j1eeZR6fQxqbSOi/+MJinyCusszJ3HSQZD89QOAIC9\n5ZyUVr8iRS2o/4U+Xh0kv05nPSKsS1c/XicBAMA5IbiMOhFcBgAA9pJbkKdvo3/Rx+u+1bbDe2rt\n62hy0KV9Ruv6kVN0SZ9RcnLgFp4AgPNTcWmJfo5ZpyXrl+m3PZtktphr7GsymnRpn1Ea3WOwkjNP\nKTEtWQmpSUpMS1JGblajjm80GBXsG6iO/sEK8w9WR/9ghQeE6JI+o7iICAAAAG2TudQ6Y3PCJmto\n68j62vu36yYNu0saeLPk6tMsJQIA0OTyM6S1b0ob/yMV1zCJTGCk9YIdWzi5s+QbLjlypy0AAGA/\nBJdRJ4LLAACgOew7Hqcl65bpy80rlJlXe9DKz8NH1w6dpOtHTlHfjj1k4Mp+AMB5wGw2a+Gar/Xa\nDx/oVFZ6rX0jAkJ18+ipun7EFAX5BFTbJzs/V4lpSUpITVZCWpISUpOUkJakxLRkZeXnqoNPgMLa\ndbAGlMuX/h0U7BvIBUIAAAA4v53YK0W9L23/TCrKqbmfo6vU73ppxN1ScL/mqw8AgHNRmGMNK697\nUyo4XX0f/87ShCelvtOtdx0AAABoRgSXUSeCywAAoDnlFxXoxx2r9fnG5Vqzf4vq+u9lZIcuumHk\nFE0fdrkCvf2bqUoAAJpWcsZJ/XnRc1q9L6rGPs4OTrpy0HjdPPoqjew2UEajsRkrBAAAAM5DhdnS\njs+lzf+VTu6rvW/YCGnkvVKvqyQTF/oBAFqh4gLrhTlrXpVyU6vv4x0qjX/celcBXs8AAEALIbiM\nOhFcBgAALSUp46S+2rxCn29crrgTR2vtazAY1D24kwaE97Q+InqpV0hXOTs6NVO1AAA0zjdbf9YT\nn7xU4x0Heod2082jr9L0YZfJx92rmasDAAAALgAWi3R0ozXAvOdbyVxSc1/PIGnoH6Shd0qe7Zuv\nRgAAalJSJG37WPr9JSnrePV93AOkix+VhtwpObo0b30AAABnIbiMOhFcBgAALc1isWj7kT36fOMP\n+mbrzzqdl12v/ZwcHNUrpJsGRJwJM3cLCpeJ254BAFqB03nZevKzl/VV1Moqbe7Obpo+/DLdMvpq\n9QvrIYPB0AIVAgAAABeg7BPS1o+kLR/WHP6SrLNU9r7GOgtz6FCJ/7MDAJpbSaEUvUha85p0+lj1\nfVx8pDEPSyPvk5zcm7U8AACAmhBcRp0ILgMAgNakoLhQP8Ws0xebftBvezap1FzaoP3dnd3UL6yH\nBkT0soWZw/yDCYQBAJrVuv1b9aeP5iop42SVtlHdB+nNO/6hUL+gFqgMAAAAgCSptEQ68KO06T0p\nfnXtfTsMlEbcI/WdziyWAAD7Ky6Qti6U1r4uZSVV38fJQxp1vzT6IcnVpxmLAwAAqBvBZdSJ4DIA\nAGitTp5O09dbVurLzSu0OzG20eP4efjYQswDwntqYERPBXj5N2GlAABYFRQXat6372r+L59WaXNy\ncNST19yveybcKKPR2ALVAQAAAKjWyf3SpvnSjs+kotya+7n5S0PukPpfL/l3kRycmq1EAMAFoChP\n2vqhtPYNKTul+j4OztLwu6Wxf5Xc2zVvfQAAAPVEcBl1IrgMAADagtN52YpJ2K8dR/Zpx9G92nFk\nn45nnGj0eCF+QWVh5p4aGN5L/cIj5eXq0YQVAwAuNHuOHdQDHzytA0nxVdp6hXTVO394Rj1DujZ/\nYQAAAADqp+C0tG2JtPk9Ka3q/+srMRgl33CpXVdriNm/a9l6V8k7VOJiRQBAfRXlSlEfSOvekHKq\n3r1LkuTgIg29QxrzZ8mrQ3NWBwAA0GAEl1EngssAAKCtOnk6TTuO7tX2sjDzziP7lJ57ulFjGQwG\nDevST1cNvlRTB01QoDczMgMA6qfUXKr//PyJ/rlsvopLSyq1GQwG3X/pzXr8qnvl7MhsbAAAAECb\nYDZLcausszAf/Flq6NejDi6Sf+czgWa/TpK7v+TiI7l6ly19JGdPyWCwwwkAANqEwhwp6n1p3ZtS\nbmr1fRxdpaF/kMY8LHkGNW99AAAAjURwGXUiuAwAAM4XFotFCWnJ2n5kT9nMzPsUk7BfeYX5DRrH\naDBqZPeBunrwpbpi0Hj5e/jYp2AAQJtmsVh0IPmwnvj0JW06uL1Ke4hfkN664x8a1X1QC1QHAAAA\noEmkHZI2vy9t+9g6I3NTMpokF29riNnFp2zd1/rcr5PUZZwU1I/ZmwHgfGGxWAPK6fFS/BppwztS\nXnr1fR3dpOGzpIv+JHkENm+dAAAA54jgMupEcBkAAJzPSs2lOphyVDuO7NX2I3u14+g+7T12sMqM\nmDUxGU0aEzlEVw2+VFMGjJOPu5edKwYAtGbpOae1dv8WrdkXpd/3Rel4ekq1/a4bMUXP3/BXebl6\nNHOFAAAAAOyiMEfa+bm0Z5l06oCUldQ8x3Xzl7pcLHWdIHUZL/mENs9xAQCNYzZL2clS+mEpLd4a\nUi5fph+WCrNr39/JXRp+jzT6j5JHQPPUDAAA0MQILqNOBJcBAMCFprC4SHuPx2lHWZB52+E9Ophy\npM79HE0OGtdruK4efKku7z9Wnq7u9i8WANBoFotFSRknlVuYpwAvP/m4ecnQwNswFxYXaWv8Lq3e\nF6XV+6IUk7BftX004uvupX/d/ISmDp5wruUDAAAAaM0Kc8rCaIek1DjrIy3O+rym2TObQkB3a4C5\n6wSp00WSs6f9jgUAF7qSImvQuDBLKsgqW8+2zsBfmC0VlLUVZklZyWUB5cNSSUHDj+XsKY24Vxr1\noOTu3/TnAgAA0IwILqNOBJcBAACko6eOa1n0Kn0b/Yt2J8bW2d/ZwUkX9xquyQPGaVK/MfLz8G6G\nKgEANSkpLVHciQTtTjyg3YkHtTsxVnuOxSojN8vWx9HkoEAvfwV4+SvQ20+BXv4K9G6nQK/ydWtb\nflGB1pQFlTfEblN+Uf2+bBrfa4Reu22OgnyYDQcAAAC4oOWlnQk0px2SMo9JBZlS/umyZdmjOO/c\njmN0kDoOk7qOtz5CBktG07nXDwAXooyj0oEV1kfyLmtQuTEB5IZy9pJG3ieNekBy87P/8QAAAJoB\nwWXUieAyAABAZYdOJOjbrb/o2+hfdCApvs7+JqNJI7sN1OQB4zR5wDh18A1shioB4MKVV1Sg/cfj\ntCsxVnsSD2pX4gHtO35IBcWFzV6Li6OzhnftrxnDJ2vG8MsbPKMzAAAAgAtYSVGFQHPGmUBzzknp\nyAYpfo11Fs/68gyW+l8n9b9BCuoj8f4EAGpmLpUSt1iDyvt/lE7ua57jOrlLfp0kv85Sx6HSkNsl\nV5/mOTYAAEAzIbiMOhFcBgAAqNn+pHh9u/UXLYv+RYdOJNRrn4ERvTRl4MWaMuBidWkfZt8CAeAC\nUVRSrCXrvtXitd9of1K8zBZzi9XSp2N3jY0cqnE9h2lY1/5ydXJpsVoAAAAAnMdKS6Tj0VLcr1Lc\nb9KxLdagXX2072UNMPe7TvIJtW+dANBWFJyWDq6yhpVjf5Ly0u1zHBcfyb8snOzf2bosX/cI5MIS\nAABw3iO4jDoRXAYAAKibxWLRnmMHbTMxJ6Qm1Wu/7sGddMXAizV5wDj1Ce0uo9Fo30IB4DxTUlqi\nLzev0CvLFygxLbnB+7s7u6mdp69SszOUW9i42zAHeQdobM+hurjXcI2JHKIAL/9GjQMAAAAA56Qg\nSzq8TopbJR36TUqNq3sfg0GKGCMNuEHqfZXk4m3/OgGgNUk7VDar8grpyHrJXFL/fY0mydlTcvaS\nXLzK1j3L1r0qrHtKbn5nQspufvY7HwAAgDaA4DLqRHAZAACgYcpDzMu3/64fd6zW/qRD9drPzdlV\nXduHq3twJ3UPjlD3oE7qFhyh8HYd5GBysHPVANC2mM1mfbftV7303X8Vd+JovfZp5+mrvh17qE/H\n7rZHp4BQ20UjuQV5OpWdrpOn03QyK00ns9J1KiutyvPCkmINCO+pcT2HaVzP4eoeHCEDM+EAAAAA\naG0yE60zMcf9KsWulIpya+/v4CxFTrHOxNztUsnBqXnqBIDmVpAlxXwpRX8kHd9ev32MJilspBR5\nudR9kuTTUXJ0Y3ZkAACARiC4jDoRXAYAADg38ScS9MOO1fphx+/adnhPg/d3cnBU58AwdQuKUPfg\nCHULjlCP4E7qHBgmZ0e+QAJwYbFYLPp513r9c9l87Tl2sMZ+EQGh6h3aTX07dlefjj3UN6y7Ar38\nCRgDAAAAuDAV5Ur7lks7P7cGmc2ltfd39ZV6TZU69JcCe0lBvazbAKCtsliko5usYeXd30jF9bjz\nlquP1G2i1ONyqdslzJQMAADQRAguo04ElwEAAJpOcsZJ/bhzjX7c8bs2xG5XaV1fEtXCaDAqvF0H\ndQ+2zszcPbiTugVFqFtQuDxc3JuwagBoHdYdiNaL376rrfG7qm13NDlo5kXX6E+X36Zg38Bmrg4A\nAAAA2oick9Kur6Qdn0vHt9V/P68OUvteUvve1mVQb6ldd8nRxX61AsC5yjkl7fhU2vqRlFrzRfA2\nAd2tQeUek6Ww4RJ3QwQAAGhyBJdRJ4LLAAAA9pGec1o/71qnH7b/ro0HtysrP6fJxg7xbW8NMweV\nh5oj1Du0G4FmAG1SdPxuvbjsXa3dv7XadqPBqOtHTtFfp/xBYe06NHN1AAAAANCGnTponYV55xdS\nxpGG7280Sf5drGHmwJ6Su7/k6GYNMzu6SY6uZY+zt7lJDs4Sd8UBYA/mUilulRS92DrbvLmk5r4G\ngxQxRuo52RpY9u/SfHUCAABcoAguo04ElwEAAOzPYrHoZFaaDiYf0YHkwzqYckSxZctTWelNcgwH\no0nDuvbXhN4jdUmfkYrs0EUGvhwC0EoVl5Zo88Edeu/Xz/RTzLoa+1095FI9duXd6hoU3ozVAQAA\nAMB5xmKREqOkHZ9ZZ2POz7T/MQ0GycVb8usstetqDQv6d5XadbGuu3jbvwYA5w+LxXoBxvZPpOiP\npazjtff3DpUGzbQ+fMOapUQAAABYEVxGnQguAwAAtKyM3NM6mHzEFmaOTTmi2OQjOp6eck7jBvsE\naHzvEZrQe6TG9hwmL1ePJqoYABonKz9Hv+7eqJUxa7Vq94ZaZ6Kf2He0Hr/qXvXp2L0ZKwQAAACA\nC0BJkXR4jZS0UzqxRzqxVzoVW/uMpfbgHlAWZu5SIdjcRQrobp2tGcCFy1wqpcZJyTul5F1ScoyU\nskvKTa19P5OjFHmFNPhWqesE66zxAAAAaHYEl1EngssAAACtU25BnuJOJNhmZi5fHj55TGaLuUFj\nmYwmDe3cVxP6jNT4XiPUp2N3ZmMG0CwSUpP00651+mnnWm2I3aYSc2mt/cdEDtETV92nwZ37NFOF\nAAAAAACVFEmpB88EmcsfmQnNX4ujqxQxSuoyXupysdS+j2Q0Nn8dAJpHUa71357kXVJSjJQSY/33\npzi//mMEdJcG3y4NuFHyCLBfrQAAAKgXgsuoE8FlAACAtqWwuEjxJxMrhZl3JRxQ/MnEeo8R6OWv\ncb2Ga2S3gRrZbYAiAkIJMgNoEmazWTsT9uunmLVauXOt9h6Pq9d+Qzr31RNX36eLegy2c4UAAAAA\ngHoryJJO7pNS9khph6TiPKkoTyopKFvPty6L86WS/LLnZdtKi5qmBvd2UudxZ4LMvmFNMy6ApmEu\nlbKSpMxEqTDb+m9AUe6ZfwuK8sr+nShbL6qwnp0spcVJjYmhOLpJfaZJQ26XwoZLfL4NAADQahBc\nRp0ILgMAAJwfjp46rlV7Nuq3PRu17kC08osK6r1vkHeARnYfqBHdBmhkt4HqFhRBkBk4z+UW5uvk\n6VSdOJ2mE6dTKzzSrNuzrMucgjw5GE0ymUxyMDqULU0VtpnkYHIoW5ps49WHv6evJvYdrasHX6qL\new3n3x0AAAAAOJ+Ulkg5J6TUOGvoOe2QNaCYdkhKPyyVFjduXP/OZ0LMncZIbn5NWjaAahScltKP\nSBlHKiwPSxlHrTOzN/bvc0M5ukodBlhnVu47XXLxap7jAgAAoEEILqNOBJcBAADOPwXFhdp8cId+\n3bNRv+7ZpIMpRxq0v7+nr0Z0HaCR3QdqVLeBiuzQRUZuyQm0WanZGfpxx2q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          }
        }
      ],
      "source": [
        "_, ax = plt.subplots(1, 1, figsize=(15, 4))\n",
        "for ind, (key, data) in enumerate(batch_data.items()):\n",
        "    ax.plot(wvls, batch_data[key][\"out\"].amps.sel(direction=\"+\", mode_index=0).abs ** 2)\n",
        "\n",
        "ax.set_title(\"Output Port\")\n",
        "ax.set_xlabel(\"Wavelength (um)\")\n",
        "ax.set_ylabel(\"Normalized transmission power\")\n",
        "ax.legend([\"0 V\", \"0.95 V\"])\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "id": "1cfd1914"
    }
  ],
  "nbformat": 4,
  "nbformat_minor": 5,
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    }
  }
}