{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Angular Reflectance Spectrum of a Planar Interface"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We turn to a similar but slightly different example for which there exists an analytic solution via the [Fresnel equations](https://en.wikipedia.org/wiki/Fresnel_equations): computing the broadband reflectance spectrum of a planar air-dielectric interface for an incident planewave over a range of angles. Similar to the previous example, we will need to run two simulations: (1) an empty cell with air/vacuum ($n$=1) everywhere to obtain the incident flux, and (2) with the dielectric ($n$=3.5) interface to obtain the reflected flux. For each angle of the incident planewave, a separate simulation is necessary.\n",
"\n",
"A 1d cell must be used since a higher-dimensional cell will introduce [artificial modes due to band folding](https://meep.readthedocs.io/en/latest/FAQ/#why-are-there-strange-peaks-in-my-reflectancetransmittance-spectrum-when-modeling-planar-or-periodic-structures). We will use a Gaussian source spanning visible wavelengths of 0.4 to 0.8 μm. Unlike a [continuous-wave](https://meep.readthedocs.io/en/latest/Python_User_Interface/#continuoussource) (CW) source, a pulsed source turns off. This enables a termination condition of when there are no fields remaining in the cell (due to absorption by the PMLs) via the [run function](https://meep.readthedocs.io/en/latest/Python_User_Interface/#run-functions) `stop_when_fields_decayed`, similar to the previous example.\n",
"\n",
"Creating an oblique planewave source typically requires specifying two parameters: (1) for periodic structures, the Bloch-periodic wavevector $\\vec{k}$ via [`k_point`](https://meep.readthedocs.io/en/latest/FAQ/#how-does-k_point-define-the-phase-relation-between-adjacent-unit-cells), and (2) the source amplitude function `amp_func` for setting the $e^{i\\vec{k} \\cdot \\vec{r}}$ spatial dependence ($\\vec{r}$ is the position vector). Since we have a 1d cell and the source is at a single point, it is not necessary to specify the source amplitude (see this [2d example](https://github.com/NanoComp/meep/blob/master/python/examples/pw-source.py) for how this is done). The magnitude of the Bloch-periodic wavevector is specified according to the dispersion relation formula for a planewave in homogeneous media with index $n$: $ω=c|\\vec{k}|/n$. As the source in this example is incident from air, $|\\vec{k}|$ is simply equal to the frequency $ω$ (the minimum frequency of the pulse which excludes the 2π factor). Note that a fixed wavevector only applies to a single frequency. Any broadband source is therefore incident at a specified angle for only a *single* frequency. This is described in more detail in Section 4.5 (\"Efficient Frequency-Angle Coverage\") in [Chapter 4](https://arxiv.org/abs/1301.5366) (\"Electromagnetic Wave Source Conditions\") of the book [Advances in FDTD Computational Electrodynamics: Photonics and Nanotechnology](https://www.amazon.com/Advances-FDTD-Computational-Electrodynamics-Nanotechnology/dp/1608071707).\n",
"\n",
"In this example, the plane of incidence which contains $\\vec{k}$ and the surface normal vector is $xz$. The source angle θ is defined in degrees in the counterclockwise (CCW) direction around the $y$ axis with 0 degrees along the +$z$ axis. In Meep, a 1d cell is defined along the $z$ direction. When $\\vec{k}$ is not set, only the $E_x$ and $H_y$ field components are permitted. A non-zero $\\vec{k}$ results in a 3d simulation where all field components are allowed and are complex (the fields are real, by default). A current source with $E_x$ polarization lies in the plane of incidence and corresponds to the convention of $\\mathcal{P}$-polarization. In order to model the $\\mathcal{S}$-polarization, we must use an $E_y$ source. This example involves just the $\\mathcal{P}$-polarization."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import meep as mp\n",
"import math\n",
"import numpy as np\n",
"import numpy.matlib\n",
"import matplotlib.pyplot as plt\n",
"\n",
"resolution = 50 # pixels/um\n",
"\n",
"dpml = 1.0 # PML thickness\n",
"sz = 10 + 2 * dpml\n",
"cell_size = mp.Vector3(z=sz)\n",
"pml_layers = [mp.PML(dpml)]\n",
"\n",
"wvl_min = 0.4 # min wavelength\n",
"wvl_max = 0.8 # max wavelength\n",
"fmin = 1 / wvl_max # min frequency\n",
"fmax = 1 / wvl_min # max frequency\n",
"fcen = 0.5 * (fmin + fmax) # center frequency\n",
"df = fmax - fmin # frequency width\n",
"nfreq = 50 # number of frequency bins\n",
"\n",
"\n",
"def planar_reflectance(theta):\n",
" # rotation angle (in degrees) of source: CCW around Y axis, 0 degrees along +Z axis\n",
" theta_r = math.radians(theta)\n",
"\n",
" # plane of incidence is XZ; rotate counter clockwise (CCW) about y-axis\n",
" k = mp.Vector3(z=fmin).rotate(mp.Vector3(y=1), theta_r)\n",
"\n",
" # if normal incidence, force number of dimensions to be 1\n",
" if theta_r == 0:\n",
" dimensions = 1\n",
" else:\n",
" dimensions = 3\n",
"\n",
" sources = [\n",
" mp.Source(\n",
" mp.GaussianSource(fcen, fwidth=df),\n",
" component=mp.Ex,\n",
" center=mp.Vector3(z=-0.5 * sz + dpml),\n",
" )\n",
" ]\n",
"\n",
" sim = mp.Simulation(\n",
" cell_size=cell_size,\n",
" boundary_layers=pml_layers,\n",
" sources=sources,\n",
" k_point=k,\n",
" dimensions=dimensions,\n",
" resolution=resolution,\n",
" )\n",
"\n",
" refl_fr = mp.FluxRegion(center=mp.Vector3(z=-0.25 * sz))\n",
" refl = sim.add_flux(fcen, df, nfreq, refl_fr)\n",
"\n",
" sim.run(\n",
" until_after_sources=mp.stop_when_fields_decayed(\n",
" 50, mp.Ex, mp.Vector3(z=-0.5 * sz + dpml), 1e-9\n",
" )\n",
" )\n",
"\n",
" empty_flux = mp.get_fluxes(refl)\n",
" empty_data = sim.get_flux_data(refl)\n",
"\n",
" sim.reset_meep()\n",
"\n",
" # add a block with n=3.5 for the air-dielectric interface\n",
" geometry = [\n",
" mp.Block(\n",
" mp.Vector3(mp.inf, mp.inf, 0.5 * sz),\n",
" center=mp.Vector3(z=0.25 * sz),\n",
" material=mp.Medium(index=3.5),\n",
" )\n",
" ]\n",
"\n",
" sim = mp.Simulation(\n",
" cell_size=cell_size,\n",
" geometry=geometry,\n",
" boundary_layers=pml_layers,\n",
" sources=sources,\n",
" k_point=k,\n",
" dimensions=dimensions,\n",
" resolution=resolution,\n",
" )\n",
"\n",
" refl = sim.add_flux(fcen, df, nfreq, refl_fr)\n",
" sim.load_minus_flux_data(refl, empty_data)\n",
"\n",
" sim.run(\n",
" until_after_sources=mp.stop_when_fields_decayed(\n",
" 50, mp.Ex, mp.Vector3(z=-0.5 * sz + dpml), 1e-9\n",
" )\n",
" )\n",
"\n",
" refl_flux = mp.get_fluxes(refl)\n",
" freqs = mp.get_flux_freqs(refl)\n",
"\n",
" wvls = np.empty(nfreq)\n",
" theta_out = np.empty(nfreq)\n",
" R = np.empty(nfreq)\n",
" for i in range(nfreq):\n",
" wvls[i] = 1 / freqs[i]\n",
" theta_out[i] = math.degrees(math.asin(k.x / freqs[i]))\n",
" R[i] = -refl_flux[i] / empty_flux[i]\n",
" print(\"refl:, {}, {}, {}, {}\".format(k.x, wvls[i], theta_out[i], R[i]))\n",
"\n",
" return k.x * np.ones(nfreq), wvls, theta_out, R"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The function `planar_reflectance` computes the reflectance at each frequency as well as the wavevector component $k_x$ and the corresponding angle for the ($k_x$, ω) pair. For those frequencies not equal to the minimum frequency of the source, this is *not* the same as the specified angle of the incident planewave, but rather sin-1(kx/ω).\n",
"\n",
"The reflectance spectrum is generated over the angular range of 0$^\\circ$ to 80$^\\circ$ in increments of 5$^\\circ$."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 2.40803e-05 s\n",
"Working in 1D dimensions.\n",
"Computational cell is 0 x 0 x 12 with resolution 50\n",
"time for set_epsilon = 7.39098e-05 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.25332329653323415 / 0.25332329653323415 = 1.0\n",
"field decay(t = 100.01): 6.806395978139866e-16 / 0.25332329653323415 = 2.686841704370019e-15\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 2.71797e-05 s\n",
"Working in 1D dimensions.\n",
"Computational cell is 0 x 0 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.000118971 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.25332329652480207 / 0.25332329652480207 = 1.0\n",
"field decay(t = 100.01): 1.9736380723733672e-11 / 0.25332329652480207 = 7.790985272371642e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.0, 0.8, 0.0, 0.2946488869770689\n",
"refl:, 0.0, 0.784, 0.0, 0.29411278345905817\n",
"refl:, 0.0, 0.7686274509803922, 0.0, 0.2935428929532476\n",
"refl:, 0.0, 0.7538461538461539, 0.0, 0.29293473702048123\n",
"refl:, 0.0, 0.739622641509434, 0.0, 0.2923073383425624\n",
"refl:, 0.0, 0.7259259259259259, 0.0, 0.29164890565286355\n",
"refl:, 0.0, 0.7127272727272727, 0.0, 0.29098366907954704\n",
"refl:, 0.0, 0.7, 0.0, 0.29030209388401956\n",
"refl:, 0.0, 0.6877192982456141, 0.0, 0.28959812074303476\n",
"refl:, 0.0, 0.6758620689655173, 0.0, 0.28888122149723194\n",
"refl:, 0.0, 0.664406779661017, 0.0, 0.28815027904146656\n",
"refl:, 0.0, 0.6533333333333333, 0.0, 0.2874049842378321\n",
"refl:, 0.0, 0.6426229508196721, 0.0, 0.2866449790098622\n",
"refl:, 0.0, 0.632258064516129, 0.0, 0.28586718403268657\n",
"refl:, 0.0, 0.6222222222222222, 0.0, 0.2850720751223629\n",
"refl:, 0.0, 0.6124999999999999, 0.0, 0.28425994421351475\n",
"refl:, 0.0, 0.6030769230769231, 0.0, 0.2834305476307166\n",
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"refl:, 0.0, 0.49, 0.0, 0.268910054299966\n",
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"refl:, 0.0, 0.4558139534883721, 0.0, 0.261846739625148\n",
"refl:, 0.0, 0.4505747126436782, 0.0, 0.2605925093678602\n",
"refl:, 0.0, 0.4454545454545454, 0.0, 0.2593113496920778\n",
"refl:, 0.0, 0.44044943820224725, 0.0, 0.2580054281160953\n",
"refl:, 0.0, 0.43555555555555553, 0.0, 0.25667922159327894\n",
"refl:, 0.0, 0.4307692307692308, 0.0, 0.2553302969233571\n",
"refl:, 0.0, 0.4260869565217391, 0.0, 0.25395270771108786\n",
"refl:, 0.0, 0.421505376344086, 0.0, 0.25254987709773263\n",
"refl:, 0.0, 0.41702127659574467, 0.0, 0.25113151895670055\n",
"refl:, 0.0, 0.4126315789473684, 0.0, 0.24969310724781182\n",
"refl:, 0.0, 0.4083333333333333, 0.0, 0.24821384020578532\n",
"refl:, 0.0, 0.4041237113402062, 0.0, 0.24668825253510232\n",
"refl:, 0.0, 0.4, 0.0, 0.24514471927281825\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.91006e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00191998 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.25242167342001054 / 0.25242167342001054 = 1.0\n",
"field decay(t = 100.01): 1.8867425273501205e-14 / 0.25242167342001054 = 7.474566275498553e-14\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.88622e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.00448012 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.2524216734361254 / 0.2524216734361254 = 1.0\n",
"field decay(t = 100.01): 2.0310851045086525e-11 / 0.2524216734361254 = 8.046397430379974e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.1089446784345727, 0.8, 5.0, 0.2933049593316432\n",
"refl:, 0.1089446784345727, 0.784, 4.899752997934953, 0.2928302248191875\n",
"refl:, 0.1089446784345727, 0.7686274509803922, 4.803451415694315, 0.2923055731561396\n",
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"refl:, 0.1089446784345727, 0.4, 2.4976190449198983, 0.24482106271892765\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.91006e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00183392 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.24974540035413884 / 0.24974540035413884 = 1.0\n",
"field decay(t = 100.01): 6.006906599019063e-14 / 0.24974540035413884 = 2.405212104207434e-13\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 4.19617e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.00453806 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.24974540044608917 / 0.24974540044608917 = 1.0\n",
"field decay(t = 100.01): 2.1519308385459792e-11 / 0.24974540044608917 = 8.616498380759976e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.2170602220836629, 0.8, 10.0, 0.2892656432100493\n",
"refl:, 0.2170602220836629, 0.784, 9.798006528153513, 0.288965065351793\n",
"refl:, 0.2170602220836629, 0.7686274509803922, 9.604050171837292, 0.2885818690170257\n",
"refl:, 0.2170602220836629, 0.7538461538461539, 9.417658416993296, 0.28817212668801895\n",
"refl:, 0.2170602220836629, 0.739622641509434, 9.238395240840497, 0.28771910655279653\n",
"refl:, 0.2170602220836629, 0.7259259259259259, 9.06585764090149, 0.2872339286740473\n",
"refl:, 0.2170602220836629, 0.7127272727272727, 8.899672554443574, 0.2867321699029375\n",
"refl:, 0.2170602220836629, 0.7, 8.739494117841588, 0.2861987897084524\n",
"refl:, 0.2170602220836629, 0.6877192982456141, 8.585001222725978, 0.28564000163622033\n",
"refl:, 0.2170602220836629, 0.6758620689655173, 8.435895331947279, 0.2850609513737311\n",
"refl:, 0.2170602220836629, 0.664406779661017, 8.291898523577625, 0.2844608473128053\n",
"refl:, 0.2170602220836629, 0.6533333333333333, 8.152751735551202, 0.2838419805391297\n",
"refl:, 0.2170602220836629, 0.6426229508196721, 8.018213187256704, 0.28320005732998216\n",
"refl:, 0.2170602220836629, 0.632258064516129, 7.88805695754783, 0.28253271331372304\n",
"refl:, 0.2170602220836629, 0.6222222222222222, 7.762071701325296, 0.28184393698477367\n",
"refl:, 0.2170602220836629, 0.6124999999999999, 7.640059489140416, 0.2811344534194306\n",
"refl:, 0.2170602220836629, 0.6030769230769231, 7.521834756238996, 0.28040341723697604\n",
"refl:, 0.2170602220836629, 0.593939393939394, 7.407223349155971, 0.27965263406145413\n",
"refl:, 0.2170602220836629, 0.5850746268656717, 7.296061659428915, 0.2788825964767311\n",
"refl:, 0.2170602220836629, 0.5764705882352942, 7.188195835257705, 0.27809153810572734\n",
"refl:, 0.2170602220836629, 0.5681159420289855, 7.083481063027822, 0.27727879066309463\n",
"refl:, 0.2170602220836629, 0.56, 6.981780911561047, 0.2764453605102568\n",
"refl:, 0.2170602220836629, 0.552112676056338, 6.882966732780441, 0.2755918264938716\n",
"refl:, 0.2170602220836629, 0.5444444444444444, 6.786917113194022, 0.274717044631823\n",
"refl:, 0.2170602220836629, 0.536986301369863, 6.693517371228444, 0.2738198627903547\n",
"refl:, 0.2170602220836629, 0.5297297297297298, 6.602659095992853, 0.2729014096931157\n",
"refl:, 0.2170602220836629, 0.5226666666666667, 6.514239723534344, 0.27196303613184486\n",
"refl:, 0.2170602220836629, 0.5157894736842105, 6.428162147069652, 0.2710031700214432\n",
"refl:, 0.2170602220836629, 0.509090909090909, 6.3443343580501015, 0.2700199119299729\n",
"refl:, 0.2170602220836629, 0.5025641025641026, 6.262669115245526, 0.26901445255671513\n",
"refl:, 0.2170602220836629, 0.4962025316455696, 6.1830836393232005, 0.2679878933990742\n",
"refl:, 0.2170602220836629, 0.49, 6.105499330654852, 0.2669382978356776\n",
"refl:, 0.2170602220836629, 0.4839506172839506, 6.029841508312739, 0.2658645437475429\n",
"refl:, 0.2170602220836629, 0.47804878048780486, 5.956039168418179, 0.26476841577725835\n",
"refl:, 0.2170602220836629, 0.47228915662650606, 5.884024760185935, 0.26365019399207895\n",
"refl:, 0.2170602220836629, 0.4666666666666667, 5.813733978168244, 0.2625075913337705\n",
"refl:, 0.2170602220836629, 0.4611764705882353, 5.745105569345401, 0.26134055474931606\n",
"refl:, 0.2170602220836629, 0.4558139534883721, 5.678081153837623, 0.2601509047307578\n",
"refl:, 0.2170602220836629, 0.4505747126436782, 5.612605058127373, 0.2589367681695608\n",
"refl:, 0.2170602220836629, 0.4454545454545454, 5.5486241597837695, 0.2576946836654639\n",
"refl:, 0.2170602220836629, 0.44044943820224725, 5.486087742772728, 0.256426818319966\n",
"refl:, 0.2170602220836629, 0.43555555555555553, 5.424947362519055, 0.2551375207965109\n",
"refl:, 0.2170602220836629, 0.4307692307692308, 5.365156719961124, 0.2538238582454513\n",
"refl:, 0.2170602220836629, 0.4260869565217391, 5.306671543905553, 0.25248026000140456\n",
"refl:, 0.2170602220836629, 0.421505376344086, 5.249449481049872, 0.25111138429336477\n",
"refl:, 0.2170602220836629, 0.41702127659574467, 5.19344999309547, 0.24972542744836562\n",
"refl:, 0.2170602220836629, 0.4126315789473684, 5.138634260422533, 0.24831408973125035\n",
"refl:, 0.2170602220836629, 0.4083333333333333, 5.08496509184317, 0.24685936094756866\n",
"refl:, 0.2170602220836629, 0.4041237113402062, 5.032406839989342, 0.24536500901018427\n",
"refl:, 0.2170602220836629, 0.4, 4.980925321928872, 0.24385884403865477\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.69549e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00182509 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.24537918139687429 / 0.24537918139687429 = 1.0\n",
"field decay(t = 100.01): 1.2755953350203158e-13 / 0.24537918139687429 = 5.198466013941004e-13\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 4.3869e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.00469923 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.2453791816184804 / 0.2453791816184804 = 1.0\n",
"field decay(t = 100.01): 2.2796495624696677e-11 / 0.2453791816184804 = 9.290313658369374e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.3235238063781509, 0.8, 14.999999999999998, 0.28250329291621734\n",
"refl:, 0.3235238063781509, 0.784, 14.693171512000124, 0.2824643918340546\n",
"refl:, 0.3235238063781509, 0.7686274509803922, 14.398780921441814, 0.2823434344182011\n",
"refl:, 0.3235238063781509, 0.7538461538461539, 14.116078899389818, 0.2821736091292865\n",
"refl:, 0.3235238063781509, 0.739622641509434, 13.844375746673084, 0.2819428557616974\n",
"refl:, 0.3235238063781509, 0.7259259259259259, 13.583035518835887, 0.28168405270433\n",
"refl:, 0.3235238063781509, 0.7127272727272727, 13.331470838933798, 0.28138555830619527\n",
"refl:, 0.3235238063781509, 0.7, 13.089138305160036, 0.28104620398023994\n",
"refl:, 0.3235238063781509, 0.6877192982456141, 12.855534414514684, 0.2806783763575039\n",
"refl:, 0.3235238063781509, 0.6758620689655173, 12.630191935533823, 0.28027812041674527\n",
"refl:, 0.3235238063781509, 0.664406779661017, 12.412676672931594, 0.27984738142823545\n",
"refl:, 0.3235238063781509, 0.6533333333333333, 12.202584575236058, 0.27938821203729947\n",
"refl:, 0.3235238063781509, 0.6426229508196721, 11.999539143408532, 0.27889571979963745\n",
"refl:, 0.3235238063781509, 0.632258064516129, 11.803189104258525, 0.2783707318747749\n",
"refl:, 0.3235238063781509, 0.6222222222222222, 11.613206317390016, 0.27781778136422264\n",
"refl:, 0.3235238063781509, 0.6124999999999999, 11.429283888592414, 0.277238647976418\n",
"refl:, 0.3235238063781509, 0.6030769230769231, 11.25113446614539, 0.2766335972563\n",
"refl:, 0.3235238063781509, 0.593939393939394, 11.078488699542484, 0.2760021980086433\n",
"refl:, 0.3235238063781509, 0.5850746268656717, 10.91109384273803, 0.2753445983679576\n",
"refl:, 0.3235238063781509, 0.5764705882352942, 10.748712486253877, 0.2746618737814714\n",
"refl:, 0.3235238063781509, 0.5681159420289855, 10.591121404404543, 0.27395346744418553\n",
"refl:, 0.3235238063781509, 0.56, 10.438110505558328, 0.273218482798473\n",
"refl:, 0.3235238063781509, 0.552112676056338, 10.289481874787974, 0.272458491647809\n",
"refl:, 0.3235238063781509, 0.5444444444444444, 10.145048899510067, 0.27167442241968504\n",
"refl:, 0.3235238063781509, 0.536986301369863, 10.004635469795673, 0.27086454108766905\n",
"refl:, 0.3235238063781509, 0.5297297297297298, 9.868075245978739, 0.2700288346581343\n",
"refl:, 0.3235238063781509, 0.5226666666666667, 9.735210987013529, 0.2691696679864803\n",
"refl:, 0.3235238063781509, 0.5157894736842105, 9.60589393375409, 0.26828660843247504\n",
"refl:, 0.3235238063781509, 0.509090909090909, 9.479983241961918, 0.26737703033509175\n",
"refl:, 0.3235238063781509, 0.5025641025641026, 9.3573454604044, 0.26644151143474176\n",
"refl:, 0.3235238063781509, 0.4962025316455696, 9.237854049896542, 0.26548236142478776\n",
"refl:, 0.3235238063781509, 0.49, 9.121388939570695, 0.26449868322216635\n",
"refl:, 0.3235238063781509, 0.4839506172839506, 9.00783611704105, 0.2634884411439653\n",
"refl:, 0.3235238063781509, 0.47804878048780486, 8.897087249467761, 0.26245254376131855\n",
"refl:, 0.3235238063781509, 0.47228915662650606, 8.789039332825531, 0.2613924415313307\n",
"refl:, 0.3235238063781509, 0.4666666666666667, 8.683594366947904, 0.2603070110071445\n",
"refl:, 0.3235238063781509, 0.4611764705882353, 8.5806590541555, 0.25919500218989733\n",
"refl:, 0.3235238063781509, 0.4558139534883721, 8.480144519487721, 0.2580569212415155\n",
"refl:, 0.3235238063781509, 0.4505747126436782, 8.381966050745921, 0.2568924101657985\n",
"refl:, 0.3235238063781509, 0.4454545454545454, 8.286042856724524, 0.2557000732428357\n",
"refl:, 0.3235238063781509, 0.44044943820224725, 8.192297842157469, 0.2544810421270595\n",
"refl:, 0.3235238063781509, 0.43555555555555553, 8.100657398042404, 0.25323728280622937\n",
"refl:, 0.3235238063781509, 0.4307692307692308, 8.011051206126568, 0.25196641359587585\n",
"refl:, 0.3235238063781509, 0.4260869565217391, 7.923412056447124, 0.2506655440913078\n",
"refl:, 0.3235238063781509, 0.421505376344086, 7.837675676917115, 0.2493388062231876\n",
"refl:, 0.3235238063781509, 0.41702127659574467, 7.753780574036344, 0.24799024185005186\n",
"refl:, 0.3235238063781509, 0.4126315789473684, 7.671667883886533, 0.24661141415700796\n",
"refl:, 0.3235238063781509, 0.4083333333333333, 7.591281232641979, 0.24519197231834583\n",
"refl:, 0.3235238063781509, 0.4041237113402062, 7.512566605892175, 0.2437413870063278\n",
"refl:, 0.3235238063781509, 0.4, 7.435472226131853, 0.24228102145492145\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.69549e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00182009 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.2394607243108125 / 0.2394607243108125 = 1.0\n",
"field decay(t = 100.01): 2.1433673054356211e-13 / 0.2394607243108125 = 8.950809413963009e-13\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 4.19617e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.00456595 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.23946072470582733 / 0.23946072470582733 = 1.0\n",
"field decay(t = 100.01): 2.292441064702724e-11 / 0.23946072470582733 = 9.57334889685539e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.4275251791570859, 0.8, 20.0, 0.27291140903435845\n",
"refl:, 0.4275251791570859, 0.784, 19.583468236198428, 0.2732447943229538\n",
"refl:, 0.4275251791570859, 0.7686274509803922, 19.184283570762837, 0.2735018552296093\n",
"refl:, 0.4275251791570859, 0.7538461538461539, 18.80136282780684, 0.27366446189146665\n",
"refl:, 0.4275251791570859, 0.739622641509434, 18.433712921276232, 0.273781793501152\n",
"refl:, 0.4275251791570859, 0.7259259259259259, 18.080421505473552, 0.27384858957084335\n",
"refl:, 0.4275251791570859, 0.7127272727272727, 17.74064878668832, 0.27385095593564335\n",
"refl:, 0.4275251791570859, 0.7, 17.413620328364388, 0.27380597771345955\n",
"refl:, 0.4275251791570859, 0.6877192982456141, 17.098620709730763, 0.2737136095477295\n",
"refl:, 0.4275251791570859, 0.6758620689655173, 16.794987920274295, 0.273573243892546\n",
"refl:, 0.4275251791570859, 0.664406779661017, 16.50210839086207, 0.2733876760611016\n",
"refl:, 0.4275251791570859, 0.6533333333333333, 16.21941257752279, 0.27315442100604564\n",
"refl:, 0.4275251791570859, 0.6426229508196721, 15.946371026493122, 0.2728767468514616\n",
"refl:, 0.4275251791570859, 0.632258064516129, 15.682490859619808, 0.27255955817684324\n",
"refl:, 0.4275251791570859, 0.6222222222222222, 15.427312627971409, 0.27220355920057415\n",
"refl:, 0.4275251791570859, 0.6124999999999999, 15.18040748886694, 0.2718114250177165\n",
"refl:, 0.4275251791570859, 0.6030769230769231, 14.941374667722823, 0.2713856767538751\n",
"refl:, 0.4275251791570859, 0.593939393939394, 14.709839171355561, 0.2709245485567433\n",
"refl:, 0.4275251791570859, 0.5850746268656717, 14.485449723819883, 0.27042763367941924\n",
"refl:, 0.4275251791570859, 0.5764705882352942, 14.267876899642369, 0.2698980098701011\n",
"refl:, 0.4275251791570859, 0.5681159420289855, 14.056811432538773, 0.2693367446910556\n",
"refl:, 0.4275251791570859, 0.56, 13.851962680467771, 0.2687424115671181\n",
"refl:, 0.4275251791570859, 0.552112676056338, 13.653057230248155, 0.2681156337689324\n",
"refl:, 0.4275251791570859, 0.5444444444444444, 13.459837627011849, 0.26745868029520964\n",
"refl:, 0.4275251791570859, 0.536986301369863, 13.272061215531336, 0.2667718443134419\n",
"refl:, 0.4275251791570859, 0.5297297297297298, 13.089499081989581, 0.2660542100897866\n",
"refl:, 0.4275251791570859, 0.5226666666666667, 12.911935086088024, 0.26530649401202394\n",
"refl:, 0.4275251791570859, 0.5157894736842105, 12.73916497454351, 0.2645300141858129\n",
"refl:, 0.4275251791570859, 0.509090909090909, 12.570995568032437, 0.2637243046129653\n",
"refl:, 0.4275251791570859, 0.5025641025641026, 12.407244014521105, 0.26288850346304676\n",
"refl:, 0.4275251791570859, 0.4962025316455696, 12.247737102692609, 0.2620237658492669\n",
"refl:, 0.4275251791570859, 0.49, 12.092310629857906, 0.2611315394355365\n",
"refl:, 0.4275251791570859, 0.4839506172839506, 11.94080881933422, 0.26021080661473406\n",
"refl:, 0.4275251791570859, 0.47804878048780486, 11.793083782798943, 0.259260103032999\n",
"refl:, 0.4275251791570859, 0.47228915662650606, 11.648995023590732, 0.25828076720993753\n",
"refl:, 0.4275251791570859, 0.4666666666666667, 11.508408977339421, 0.2572746105587765\n",
"refl:, 0.4275251791570859, 0.4611764705882353, 11.37119858666983, 0.25624008547337146\n",
"refl:, 0.4275251791570859, 0.4558139534883721, 11.23724290704701, 0.2551747627993682\n",
"refl:, 0.4275251791570859, 0.4505747126436782, 11.106426741117268, 0.254079676475692\n",
"refl:, 0.4275251791570859, 0.4454545454545454, 10.978640299154753, 0.2529572394711134\n",
"refl:, 0.4275251791570859, 0.44044943820224725, 10.853778883451254, 0.25180680229382696\n",
"refl:, 0.4275251791570859, 0.43555555555555553, 10.731742594690267, 0.25062573390797804\n",
"refl:, 0.4275251791570859, 0.4307692307692308, 10.61243605852877, 0.2494136021716301\n",
"refl:, 0.4275251791570859, 0.4260869565217391, 10.495768170772996, 0.24817270591418827\n",
"refl:, 0.4275251791570859, 0.421505376344086, 10.381651859681224, 0.24690457932715454\n",
"refl:, 0.4275251791570859, 0.41702127659574467, 10.270003864057921, 0.24560713839504952\n",
"refl:, 0.4275251791570859, 0.4126315789473684, 10.160744525922071, 0.24427619924007887\n",
"refl:, 0.4275251791570859, 0.4083333333333333, 10.053797596639106, 0.24291142234897387\n",
"refl:, 0.4275251791570859, 0.4041237113402062, 9.949090055502005, 0.24152100364291515\n",
"refl:, 0.4275251791570859, 0.4, 9.846551939834079, 0.2401173303544212\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.60012e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00180292 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.2321756751554577 / 0.2321756751554577 = 1.0\n",
"field decay(t = 100.01): 3.189584689866576e-13 / 0.2321756751554577 = 1.373780732081829e-12\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 4.1008e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.00448799 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.23217567572618025 / 0.23217567572618025 = 1.0\n",
"field decay(t = 100.01): 2.5113865846466273e-11 / 0.23217567572618025 = 1.0816751482650867e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.5282728271758743, 0.8, 25.0, 0.26019389637751095\n",
"refl:, 0.5282728271758743, 0.784, 24.46679999189225, 0.26109407463193457\n",
"refl:, 0.5282728271758743, 0.7686274509803922, 23.95662859236144, 0.2618692444514501\n",
"refl:, 0.5282728271758743, 0.7538461538461539, 23.46797596156662, 0.26257268253476557\n",
"refl:, 0.5282728271758743, 0.739622641509434, 22.99946566139384, 0.26318360986138806\n",
"refl:, 0.5282728271758743, 0.7259259259259259, 22.54983979533518, 0.2636884917611983\n",
"refl:, 0.5282728271758743, 0.7127272727272727, 22.117946146436154, 0.2641153624871549\n",
"refl:, 0.5282728271758743, 0.7, 21.70272699899909, 0.26446400131053266\n",
"refl:, 0.5282728271758743, 0.6877192982456141, 21.303209386217617, 0.2647361502445863\n",
"refl:, 0.5282728271758743, 0.6758620689655173, 20.91849655102253, 0.26494127762665987\n",
"refl:, 0.5282728271758743, 0.664406779661017, 20.54776044367494, 0.26507870572225684\n",
"refl:, 0.5282728271758743, 0.6533333333333333, 20.19023510896709, 0.2651506958652906\n",
"refl:, 0.5282728271758743, 0.6426229508196721, 19.84521083974841, 0.26516452813944175\n",
"refl:, 0.5282728271758743, 0.632258064516129, 19.51202899301187, 0.2651243633954837\n",
"refl:, 0.5282728271758743, 0.6222222222222222, 19.190077380825585, 0.2650321194109797\n",
"refl:, 0.5282728271758743, 0.6124999999999999, 18.878786161658894, 0.26488903211488374\n",
"refl:, 0.5282728271758743, 0.6030769230769231, 18.577624168665142, 0.2646966666638105\n",
"refl:, 0.5282728271758743, 0.593939393939394, 18.28609562066815, 0.2644576983261531\n",
"refl:, 0.5282728271758743, 0.5850746268656717, 18.003737169291743, 0.26417368977600525\n",
"refl:, 0.5282728271758743, 0.5764705882352942, 17.730115242139682, 0.26384517442033967\n",
"refl:, 0.5282728271758743, 0.5681159420289855, 17.46482364739322, 0.2634743009887046\n",
"refl:, 0.5282728271758743, 0.56, 17.207481409818527, 0.2630632173645374\n",
"refl:, 0.5282728271758743, 0.552112676056338, 16.957730812108316, 0.2626116463801122\n",
"refl:, 0.5282728271758743, 0.5444444444444444, 16.715235618835717, 0.26212001269997814\n",
"refl:, 0.5282728271758743, 0.536986301369863, 16.479679463167955, 0.2615912946581222\n",
"refl:, 0.5282728271758743, 0.5297297297297298, 16.250764378950514, 0.26102663469509957\n",
"refl:, 0.5282728271758743, 0.5226666666666667, 16.028209462892256, 0.26042439141314616\n",
"refl:, 0.5282728271758743, 0.5157894736842105, 15.811749653412038, 0.2597853758930952\n",
"refl:, 0.5282728271758743, 0.509090909090909, 15.60113461429131, 0.25911262730709367\n",
"refl:, 0.5282728271758743, 0.5025641025641026, 15.396127712651408, 0.2584060888970194\n",
"refl:, 0.5282728271758743, 0.4962025316455696, 15.196505081970068, 0.2576642746546754\n",
"refl:, 0.5282728271758743, 0.49, 15.002054761894165, 0.2568888948983748\n",
"refl:, 0.5282728271758743, 0.4839506172839506, 14.81257590751694, 0.25608173235353965\n",
"refl:, 0.5282728271758743, 0.47804878048780486, 14.627878061586326, 0.25524132391655996\n",
"refl:, 0.5282728271758743, 0.47228915662650606, 14.44778048381156, 0.254367293135576\n",
"refl:, 0.5282728271758743, 0.4666666666666667, 14.272111532051735, 0.2534621115579794\n",
"refl:, 0.5282728271758743, 0.4611764705882353, 14.100708090713411, 0.25252576242439695\n",
"refl:, 0.5282728271758743, 0.4558139534883721, 13.933415042164041, 0.25155529986985325\n",
"refl:, 0.5282728271758743, 0.4505747126436782, 13.770084777392734, 0.2505511615005892\n",
"refl:, 0.5282728271758743, 0.4454545454545454, 13.610576742526133, 0.2495168318010228\n",
"refl:, 0.5282728271758743, 0.44044943820224725, 13.454757018141454, 0.24845156231536186\n",
"refl:, 0.5282728271758743, 0.43555555555555553, 13.30249792861589, 0.2473511491305419\n",
"refl:, 0.5282728271758743, 0.4307692307692308, 13.153677679016674, 0.24621635842933665\n",
"refl:, 0.5282728271758743, 0.4260869565217391, 13.008180017272103, 0.2450522325472059\n",
"refl:, 0.5282728271758743, 0.421505376344086, 12.865893919575512, 0.24385875474669194\n",
"refl:, 0.5282728271758743, 0.41702127659574467, 12.726713297162874, 0.24263075122017086\n",
"refl:, 0.5282728271758743, 0.4126315789473684, 12.590536722774571, 0.24136640786665386\n",
"refl:, 0.5282728271758743, 0.4083333333333333, 12.457267175263851, 0.24006853393330466\n",
"refl:, 0.5282728271758743, 0.4041237113402062, 12.326811800951434, 0.23874368705732368\n",
"refl:, 0.5282728271758743, 0.4, 12.199081690448809, 0.23740409018120856\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.8147e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00182295 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.22375100718842017 / 0.22375100718842017 = 1.0\n",
"field decay(t = 100.01): 4.405483227742841e-13 / 0.22375100718842017 = 1.9689221885973432e-12\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.91006e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.00455689 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.22375100783150073 / 0.22375100783150073 = 1.0\n",
"field decay(t = 100.01): 2.6045908524047717e-11 / 0.22375100783150073 = 1.1640577075595567e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.6249999999999999, 0.8, 29.999999999999993, 0.2441304698440292\n",
"refl:, 0.6249999999999999, 0.784, 29.34058157502373, 0.2458848744990323\n",
"refl:, 0.6249999999999999, 0.7686274509803922, 28.711017527148794, 0.2474738617848535\n",
"refl:, 0.6249999999999999, 0.7538461538461539, 28.10922128260952, 0.24886145900455134\n",
"refl:, 0.6249999999999999, 0.739622641509434, 27.53330580109674, 0.2500790166042368\n",
"refl:, 0.6249999999999999, 0.7259259259259259, 26.98155921981659, 0.2511706573365747\n",
"refl:, 0.6249999999999999, 0.7127272727272727, 26.452424118557172, 0.25213606232996266\n",
"refl:, 0.6249999999999999, 0.7, 25.944479772370002, 0.25298936027517865\n",
"refl:, 0.6249999999999999, 0.6877192982456141, 25.45642688540588, 0.2537413324767768\n",
"refl:, 0.6249999999999999, 0.6758620689655173, 24.98707439783817, 0.2543902864127213\n",
"refl:, 0.6249999999999999, 0.664406779661017, 24.53532803474182, 0.25494503656419537\n",
"refl:, 0.6249999999999999, 0.6533333333333333, 24.10018032643974, 0.25541541144304014\n",
"refl:, 0.6249999999999999, 0.6426229508196721, 23.680701877992792, 0.2558038470011666\n",
"refl:, 0.6249999999999999, 0.632258064516129, 23.276033704033082, 0.25611422492454605\n",
"refl:, 0.6249999999999999, 0.6222222222222222, 22.885380476158563, 0.25635226359269697\n",
"refl:, 0.6249999999999999, 0.6124999999999999, 22.508004555237044, 0.2565212690513844\n",
"refl:, 0.6249999999999999, 0.6030769230769231, 22.14322070144805, 0.25662363175125674\n",
"refl:, 0.6249999999999999, 0.593939393939394, 21.79039137167391, 0.25666316405820044\n",
"refl:, 0.6249999999999999, 0.5850746268656717, 21.448922527676533, 0.256643853974939\n",
"refl:, 0.6249999999999999, 0.5764705882352942, 21.118259889941786, 0.25656744769664874\n",
"refl:, 0.6249999999999999, 0.5681159420289855, 20.797885581592283, 0.2564348059692535\n",
"refl:, 0.6249999999999999, 0.56, 20.487315114722662, 0.2562488813390074\n",
"refl:, 0.6249999999999999, 0.552112676056338, 20.186094678183196, 0.2560129738604307\n",
"refl:, 0.6249999999999999, 0.5444444444444444, 19.89379869145801, 0.25572798412991815\n",
"refl:, 0.6249999999999999, 0.536986301369863, 19.610027594036424, 0.2553946757545203\n",
"refl:, 0.6249999999999999, 0.5297297297297298, 19.33440584370919, 0.2550156190782023\n",
"refl:, 0.6249999999999999, 0.5226666666666667, 19.066580100655866, 0.2545925551142987\n",
"refl:, 0.6249999999999999, 0.5157894736842105, 18.806217577124535, 0.25412540391688965\n",
"refl:, 0.6249999999999999, 0.509090909090909, 18.553004535020655, 0.25361528880754325\n",
"refl:, 0.6249999999999999, 0.5025641025641026, 18.306644915884704, 0.25306481668131153\n",
"refl:, 0.6249999999999999, 0.4962025316455696, 18.066859089603533, 0.25247461257562936\n",
"refl:, 0.6249999999999999, 0.49, 17.833382709813034, 0.2518436268795026\n",
"refl:, 0.6249999999999999, 0.4839506172839506, 17.605965665348197, 0.2511731587087493\n",
"refl:, 0.6249999999999999, 0.47804878048780486, 17.38437111831227, 0.25046601975628274\n",
"refl:, 0.6249999999999999, 0.47228915662650606, 17.168374620396104, 0.24972209992178607\n",
"refl:, 0.6249999999999999, 0.4666666666666667, 16.957763300004142, 0.24893969262180818\n",
"refl:, 0.6249999999999999, 0.4611764705882353, 16.752335113553887, 0.24811981145545228\n",
"refl:, 0.6249999999999999, 0.4558139534883721, 16.551898155026578, 0.24726440526511775\n",
"refl:, 0.6249999999999999, 0.4505747126436782, 16.35627001847215, 0.24637290574011259\n",
"refl:, 0.6249999999999999, 0.4454545454545454, 16.165277208722518, 0.24544450395766448\n",
"refl:, 0.6249999999999999, 0.44044943820224725, 15.978754596053776, 0.24448027110760395\n",
"refl:, 0.6249999999999999, 0.43555555555555553, 15.796544910968182, 0.2434805663315552\n",
"refl:, 0.6249999999999999, 0.4307692307692308, 15.618498275648548, 0.2424444686589383\n",
"refl:, 0.6249999999999999, 0.4260869565217391, 15.44447176897603, 0.24137271247893222\n",
"refl:, 0.6249999999999999, 0.421505376344086, 15.274329022304034, 0.24026658833730827\n",
"refl:, 0.6249999999999999, 0.41702127659574467, 15.107939843449019, 0.23912295725148944\n",
"refl:, 0.6249999999999999, 0.4126315789473684, 14.94517986659885, 0.2379359418651507\n",
"refl:, 0.6249999999999999, 0.4083333333333333, 14.78593022605342, 0.23670966886718617\n",
"refl:, 0.6249999999999999, 0.4041237113402062, 14.630077251904048, 0.23546524192379745\n",
"refl:, 0.6249999999999999, 0.4, 14.477512185929921, 0.23421631294354242\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.69549e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00170493 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.21444706390029775 / 0.21444706390029775 = 1.0\n",
"field decay(t = 100.01): 5.749510873093161e-13 / 0.21444706390029775 = 2.681086310310252e-12\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.98159e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.00455904 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.21444706445458084 / 0.21444706445458084 = 1.0\n",
"field decay(t = 100.01): 2.737725033432578e-11 / 0.21444706445458084 = 1.2766437444110684e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.7169705454388076, 0.8, 35.0, 0.22495734929489236\n",
"refl:, 0.7169705454388076, 0.784, 34.201491482224874, 0.2276898082643635\n",
"refl:, 0.7169705454388076, 0.7686274509803922, 33.4413597291606, 0.23011693205976114\n",
"refl:, 0.7169705454388076, 0.7538461538461539, 32.71669424141867, 0.23234222429680992\n",
"refl:, 0.7169705454388076, 0.739622641509434, 32.02489215108529, 0.23437969108695692\n",
"refl:, 0.7169705454388076, 0.7259259259259259, 31.363616172201723, 0.23622265510793064\n",
"refl:, 0.7169705454388076, 0.7127272727272727, 30.73075960358516, 0.23789643333674684\n",
"refl:, 0.7169705454388076, 0.7, 30.12441698853809, 0.23940633852434773\n",
"refl:, 0.7169705454388076, 0.6877192982456141, 29.542859352190995, 0.24075746810602938\n",
"refl:, 0.7169705454388076, 0.6758620689655173, 28.984513173223203, 0.2419699286741594\n",
"refl:, 0.7169705454388076, 0.664406779661017, 28.447942424882076, 0.24305307471225007\n",
"refl:, 0.7169705454388076, 0.6533333333333333, 27.931833156170086, 0.2440117580982575\n",
"refl:, 0.7169705454388076, 0.6426229508196721, 27.43498018882287, 0.24485799959527518\n",
"refl:, 0.7169705454388076, 0.632258064516129, 26.95627558715663, 0.24559973015569014\n",
"refl:, 0.7169705454388076, 0.6222222222222222, 26.49469862174186, 0.246240896723184\n",
"refl:, 0.7169705454388076, 0.6124999999999999, 26.049306998353728, 0.2467892899221832\n",
"refl:, 0.7169705454388076, 0.6030769230769231, 25.619229163859046, 0.24725182835118295\n",
"refl:, 0.7169705454388076, 0.593939393939394, 25.20365753294407, 0.24763129782088683\n",
"refl:, 0.7169705454388076, 0.5850746268656717, 24.80184250561243, 0.24793098018363321\n",
"refl:, 0.7169705454388076, 0.5764705882352942, 24.41308716651858, 0.24815599140237504\n",
"refl:, 0.7169705454388076, 0.5681159420289855, 24.036742574466203, 0.24831042769942835\n",
"refl:, 0.7169705454388076, 0.56, 23.672203564580393, 0.24839661296784196\n",
"refl:, 0.7169705454388076, 0.552112676056338, 23.318904997368072, 0.24841763613734327\n",
"refl:, 0.7169705454388076, 0.5444444444444444, 22.976318398592397, 0.2483776953869765\n",
"refl:, 0.7169705454388076, 0.536986301369863, 22.643948941980693, 0.2482787140153355\n",
"refl:, 0.7169705454388076, 0.5297297297297298, 22.321332733561132, 0.24812129287197915\n",
"refl:, 0.7169705454388076, 0.5226666666666667, 22.008034362119382, 0.24790881905698\n",
"refl:, 0.7169705454388076, 0.5157894736842105, 21.703644685073712, 0.2476447465584906\n",
"refl:, 0.7169705454388076, 0.509090909090909, 21.407778823139967, 0.2473290950751843\n",
"refl:, 0.7169705454388076, 0.5025641025641026, 21.120074340620857, 0.24696260849110413\n",
"refl:, 0.7169705454388076, 0.4962025316455696, 20.840189591108683, 0.24654850371687256\n",
"refl:, 0.7169705454388076, 0.49, 20.56780221092012, 0.24608799987122265\n",
"refl:, 0.7169705454388076, 0.4839506172839506, 20.302607744753697, 0.24558075371549817\n",
"refl:, 0.7169705454388076, 0.47804878048780486, 20.044318389931625, 0.24502869978373035\n",
"refl:, 0.7169705454388076, 0.47228915662650606, 19.79266184720379, 0.24443385311897003\n",
"refl:, 0.7169705454388076, 0.4666666666666667, 19.54738026749198, 0.24379544974149034\n",
"refl:, 0.7169705454388076, 0.4611764705882353, 19.308229285168313, 0.24311337479355408\n",
"refl:, 0.7169705454388076, 0.4558139534883721, 19.07497712952083, 0.24239050667955775\n",
"refl:, 0.7169705454388076, 0.4505747126436782, 18.847403806983923, 0.24162858318113342\n",
"refl:, 0.7169705454388076, 0.4454545454545454, 18.62530034751981, 0.24082594853100417\n",
"refl:, 0.7169705454388076, 0.44044943820224725, 18.408468109247096, 0.23998192730485585\n",
"refl:, 0.7169705454388076, 0.43555555555555553, 18.196718136035763, 0.23909849717321205\n",
"refl:, 0.7169705454388076, 0.4307692307692308, 17.98987056333767, 0.23817577312539148\n",
"refl:, 0.7169705454388076, 0.4260869565217391, 17.787754068005896, 0.23721144993308976\n",
"refl:, 0.7169705454388076, 0.421505376344086, 17.590205358285754, 0.2362040994387872\n",
"refl:, 0.7169705454388076, 0.41702127659574467, 17.39706870053973, 0.23515140286483463\n",
"refl:, 0.7169705454388076, 0.4126315789473684, 17.20819547960629, 0.23405349223820357\n",
"refl:, 0.7169705454388076, 0.4083333333333333, 17.02344378999232, 0.23292711235344504\n",
"refl:, 0.7169705454388076, 0.4041237113402062, 16.842678055366356, 0.23179557860673924\n",
"refl:, 0.7169705454388076, 0.4, 16.665768674058118, 0.2306452929106223\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.88622e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.001827 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.20454876789491913 / 0.20454876789491913 = 1.0\n",
"field decay(t = 100.01): 7.178635176478305e-13 / 0.20454876789491913 = 3.5094981262200107e-12\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 4.1008e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.00457597 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.20454876813558653 / 0.20454876813558653 = 1.0\n",
"field decay(t = 100.01): 2.817457244887082e-11 / 0.20454876813558653 = 1.3774012283562185e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.8034845121081741, 0.8, 39.99999999999999, 0.20174574732399359\n",
"refl:, 0.8034845121081741, 0.784, 39.04509528455022, 0.20589297541852558\n",
"refl:, 0.8034845121081741, 0.7686274509803922, 38.139646206191365, 0.20966853236552122\n",
"refl:, 0.8034845121081741, 0.7538461538461539, 37.27949726994566, 0.21305998243366164\n",
"refl:, 0.8034845121081741, 0.739622641509434, 36.46098976062103, 0.2161315876607331\n",
"refl:, 0.8034845121081741, 0.7259259259259259, 35.680884053707004, 0.21892504829192913\n",
"refl:, 0.8034845121081741, 0.7127272727272727, 34.93629688867566, 0.22145999607107203\n",
"refl:, 0.8034845121081741, 0.7, 34.22465020933728, 0.22376578875003042\n",
"refl:, 0.8034845121081741, 0.6877192982456141, 33.54362905484555, 0.22586507657858915\n",
"refl:, 0.8034845121081741, 0.6758620689655173, 32.89114661043291, 0.22776751087226974\n",
"refl:, 0.8034845121081741, 0.664406779661017, 32.265314978971055, 0.22948642344304926\n",
"refl:, 0.8034845121081741, 0.6533333333333333, 31.664420565727855, 0.23104021748754944\n",
"refl:, 0.8034845121081741, 0.6426229508196721, 31.086903214629274, 0.23243958627884664\n",
"refl:, 0.8034845121081741, 0.632258064516129, 30.531338419096144, 0.2336946954040348\n",
"refl:, 0.8034845121081741, 0.6222222222222222, 29.996422070856152, 0.23482007111973577\n",
"refl:, 0.8034845121081741, 0.6124999999999999, 29.480957317802616, 0.23582329675340516\n",
"refl:, 0.8034845121081741, 0.6030769230769231, 28.983843185365757, 0.2367091706706393\n",
"refl:, 0.8034845121081741, 0.593939393939394, 28.504064681021994, 0.2374872020062935\n",
"refl:, 0.8034845121081741, 0.5850746268656717, 28.0406841528977, 0.238164188713723\n",
"refl:, 0.8034845121081741, 0.5764705882352942, 27.592833714170844, 0.23874383693611143\n",
"refl:, 0.8034845121081741, 0.5681159420289855, 27.159708577552564, 0.2392325677866777\n",
"refl:, 0.8034845121081741, 0.56, 26.740561170354134, 0.23963653341947785\n",
"refl:, 0.8034845121081741, 0.552112676056338, 26.33469592188663, 0.23995882233761215\n",
"refl:, 0.8034845121081741, 0.5444444444444444, 25.94146463225064, 0.2402024441340643\n",
"refl:, 0.8034845121081741, 0.536986301369863, 25.560262345758233, 0.24037225972376797\n",
"refl:, 0.8034845121081741, 0.5297297297297298, 25.190523663916437, 0.24047264456383183\n",
"refl:, 0.8034845121081741, 0.5226666666666667, 24.831719442577725, 0.24050529500914392\n",
"refl:, 0.8034845121081741, 0.5157894736842105, 24.483353825914165, 0.24047249027879555\n",
"refl:, 0.8034845121081741, 0.509090909090909, 24.144961576600384, 0.2403786028523382\n",
"refl:, 0.8034845121081741, 0.5025641025641026, 23.816105667237974, 0.24022523323130834\n",
"refl:, 0.8034845121081741, 0.4962025316455696, 23.496375102814216, 0.24001232236295097\n",
"refl:, 0.8034845121081741, 0.49, 23.185382948015043, 0.23974362785116177\n",
"refl:, 0.8034845121081741, 0.4839506172839506, 22.882764536632674, 0.23942247402605424\n",
"refl:, 0.8034845121081741, 0.47804878048780486, 22.58817584322306, 0.23904770280781232\n",
"refl:, 0.8034845121081741, 0.47228915662650606, 22.301291999661412, 0.23862003627448614\n",
"refl:, 0.8034845121081741, 0.4666666666666667, 22.021805941382443, 0.23814371157526962\n",
"refl:, 0.8034845121081741, 0.4611764705882353, 21.749427169932794, 0.23762004855970983\n",
"refl:, 0.8034845121081741, 0.4558139534883721, 21.483880620051718, 0.2370480859309985\n",
"refl:, 0.8034845121081741, 0.4505747126436782, 21.224905620871482, 0.2364296182998171\n",
"refl:, 0.8034845121081741, 0.4454545454545454, 20.972254942022712, 0.23576666887769465\n",
"refl:, 0.8034845121081741, 0.44044943820224725, 20.725693916468796, 0.23505766085138496\n",
"refl:, 0.8034845121081741, 0.43555555555555553, 20.48499963280006, 0.2343015839900727\n",
"refl:, 0.8034845121081741, 0.4307692307692308, 20.249960190511292, 0.2335015406593809\n",
"refl:, 0.8034845121081741, 0.4260869565217391, 20.020374012481035, 0.23265820727265243\n",
"refl:, 0.8034845121081741, 0.421505376344086, 19.79604920948226, 0.23176538827635734\n",
"refl:, 0.8034845121081741, 0.41702127659574467, 19.576802992091316, 0.2308222435106821\n",
"refl:, 0.8034845121081741, 0.4126315789473684, 19.362461125837058, 0.22984486603425214\n",
"refl:, 0.8034845121081741, 0.4083333333333333, 19.15285742585141, 0.22884869903534621\n",
"refl:, 0.8034845121081741, 0.4041237113402062, 18.9478332876545, 0.22781887957732183\n",
"refl:, 0.8034845121081741, 0.4, 18.747237251037504, 0.22672147973970627\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.69549e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00182915 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.1943564114319852 / 0.1943564114319852 = 1.0\n",
"field decay(t = 100.01): 8.613369502151169e-13 / 0.1943564114319852 = 4.431739317828168e-12\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 4.1008e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.0045619 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.19435641121678224 / 0.19435641121678224 = 1.0\n",
"field decay(t = 100.01): 2.929219089204079e-11 / 0.19435641121678224 = 1.507137876680009e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.8838834764831843, 0.8, 44.99999999999999, 0.17502993854504276\n",
"refl:, 0.8838834764831843, 0.784, 43.865246854678944, 0.1808719938626426\n",
"refl:, 0.8838834764831843, 0.7686274509803922, 42.79498686880298, 0.1861559520009496\n",
"refl:, 0.8838834764831843, 0.7538461538461539, 41.78306957363623, 0.19097169679998788\n",
"refl:, 0.8838834764831843, 0.739622641509434, 40.82419653278361, 0.19534107187624397\n",
"refl:, 0.8838834764831843, 0.7259259259259259, 39.913765803587594, 0.1993129093290473\n",
"refl:, 0.8838834764831843, 0.7127272727272727, 39.047751315763335, 0.2029343832170293\n",
"refl:, 0.8838834764831843, 0.7, 38.2226079814105, 0.20622282929854657\n",
"refl:, 0.8838834764831843, 0.6877192982456141, 37.435196089128915, 0.20921161798306928\n",
"refl:, 0.8838834764831843, 0.6758620689655173, 36.682720369951866, 0.21193294983781294\n",
"refl:, 0.8838834764831843, 0.664406779661017, 35.962680378531154, 0.2144100930400042\n",
"refl:, 0.8838834764831843, 0.6533333333333333, 35.272829708778914, 0.21666480283186992\n",
"refl:, 0.8838834764831843, 0.6426229508196721, 34.61114218453038, 0.21871574748298628\n",
"refl:, 0.8838834764831843, 0.632258064516129, 33.975783613579615, 0.2205809372467119\n",
"refl:, 0.8838834764831843, 0.6222222222222222, 33.36508802077569, 0.22227155758719339\n",
"refl:, 0.8838834764831843, 0.6124999999999999, 32.77753751829758, 0.22379898710754023\n",
"refl:, 0.8838834764831843, 0.6030769230769231, 32.21174515294742, 0.2251782492582617\n",
"refl:, 0.8838834764831843, 0.593939393939394, 31.666440208036935, 0.22641733524917368\n",
"refl:, 0.8838834764831843, 0.5850746268656717, 31.14045554291693, 0.22752444186490398\n",
"refl:, 0.8838834764831843, 0.5764705882352942, 30.6327166347442, 0.22851133567283208\n",
"refl:, 0.8838834764831843, 0.5681159420289855, 30.142232050688204, 0.22938387252712697\n",
"refl:, 0.8838834764831843, 0.56, 29.66808512880701, 0.2301469724038025\n",
"refl:, 0.8838834764831843, 0.552112676056338, 29.20942668547734, 0.23080897055556673\n",
"refl:, 0.8838834764831843, 0.5444444444444444, 28.765468598924116, 0.23137563774572306\n",
"refl:, 0.8838834764831843, 0.536986301369863, 28.33547814384704, 0.23185070033374858\n",
"refl:, 0.8838834764831843, 0.5297297297297298, 27.91877297273401, 0.2322392190088606\n",
"refl:, 0.8838834764831843, 0.5226666666666667, 27.514716656212954, 0.23254636390929412\n",
"refl:, 0.8838834764831843, 0.5157894736842105, 27.12271470851516, 0.23277522069046336\n",
"refl:, 0.8838834764831843, 0.509090909090909, 26.742211035417114, 0.2329277669161597\n",
"refl:, 0.8838834764831843, 0.5025641025641026, 26.372684751370738, 0.233008303204484\n",
"refl:, 0.8838834764831843, 0.4962025316455696, 26.013647320299032, 0.2330211687709118\n",
"refl:, 0.8838834764831843, 0.49, 25.66463998102006, 0.23296698717426295\n",
"refl:, 0.8838834764831843, 0.4839506172839506, 25.32523142370283, 0.23284755035583113\n",
"refl:, 0.8838834764831843, 0.47804878048780486, 24.99501568834094, 0.2326674384773264\n",
"refl:, 0.8838834764831843, 0.47228915662650606, 24.673610260104642, 0.23242802131165444\n",
"refl:, 0.8838834764831843, 0.4666666666666667, 24.360654339720863, 0.2321295593079615\n",
"refl:, 0.8838834764831843, 0.4611764705882353, 24.055807269832574, 0.23177582439583932\n",
"refl:, 0.8838834764831843, 0.4558139534883721, 23.75874710068368, 0.2313690613476082\n",
"refl:, 0.8838834764831843, 0.4505747126436782, 23.46916928052956, 0.23090791937820976\n",
"refl:, 0.8838834764831843, 0.4454545454545454, 23.18678545794031, 0.23039322072655252\n",
"refl:, 0.8838834764831843, 0.44044943820224725, 22.911322384688706, 0.2298284080169662\n",
"refl:, 0.8838834764831843, 0.43555555555555553, 22.64252090923418, 0.22921510204235154\n",
"refl:, 0.8838834764831843, 0.4307692307692308, 22.380135051959574, 0.2285521481969639\n",
"refl:, 0.8838834764831843, 0.4260869565217391, 22.123931154313652, 0.22783726183812486\n",
"refl:, 0.8838834764831843, 0.421505376344086, 21.873687094881706, 0.22707071257620573\n",
"refl:, 0.8838834764831843, 0.41702127659574467, 21.629191566166806, 0.22625950710942383\n",
"refl:, 0.8838834764831843, 0.4126315789473684, 21.390243406530644, 0.22541142020660002\n",
"refl:, 0.8838834764831843, 0.4083333333333333, 21.156650982328358, 0.22451918835662907\n",
"refl:, 0.8838834764831843, 0.4041237113402062, 20.928231615787418, 0.22356313569076627\n",
"refl:, 0.8838834764831843, 0.4, 20.704811054635428, 0.2225460542244332\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.8147e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00170398 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.18417632037527296 / 0.18417632037527296 = 1.0\n",
"field decay(t = 100.01): 1.0178427596032929e-12 / 0.18417632037527296 = 5.526458328244166e-12\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 4.19617e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.00469804 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.1841763197552185 / 0.1841763197552185 = 1.0\n",
"field decay(t = 100.01): 2.871301261786922e-11 / 0.1841763197552185 = 1.5589958935019742e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.9575555538987225, 0.8, 50.0, 0.14423305713624324\n",
"refl:, 0.9575555538987225, 0.784, 48.6530933185261, 0.15238194243131842\n",
"refl:, 0.9575555538987225, 0.7686274509803922, 47.39207738436693, 0.15968064236197976\n",
"refl:, 0.9575555538987225, 0.7538461538461539, 46.207396358038395, 0.166276599415515\n",
"refl:, 0.9575555538987225, 0.739622641509434, 45.091066324150106, 0.172235759713748\n",
"refl:, 0.9575555538987225, 0.7259259259259259, 44.036334278275795, 0.17762992926260002\n",
"refl:, 0.9575555538987225, 0.7127272727272727, 43.037427456538545, 0.18252108862299557\n",
"refl:, 0.9575555538987225, 0.7, 42.089365210987516, 0.18696921001018088\n",
"refl:, 0.9575555538987225, 0.6877192982456141, 41.18781524255363, 0.1910237249088231\n",
"refl:, 0.9575555538987225, 0.6758620689655173, 40.32898196453324, 0.1947139212974769\n",
"refl:, 0.9575555538987225, 0.664406779661017, 39.50951857909891, 0.1980824834747826\n",
"refl:, 0.9575555538987225, 0.6533333333333333, 38.726456948394606, 0.20115657663131353\n",
"refl:, 0.9575555538987225, 0.6426229508196721, 37.97715101972185, 0.2039606150416146\n",
"refl:, 0.9575555538987225, 0.632258064516129, 37.25923071465613, 0.2065188140121264\n",
"refl:, 0.9575555538987225, 0.6222222222222222, 36.57056399547784, 0.2088504663121866\n",
"refl:, 0.9575555538987225, 0.6124999999999999, 35.909225393217994, 0.21097639595491705\n",
"refl:, 0.9575555538987225, 0.6030769230769231, 35.273469693564564, 0.2129096520737003\n",
"refl:, 0.9575555538987225, 0.593939393939394, 34.6617097783444, 0.21466551482576457\n",
"refl:, 0.9575555538987225, 0.5850746268656717, 34.07249784378941, 0.21625947963710546\n",
"refl:, 0.9575555538987225, 0.5764705882352942, 33.504509384470694, 0.2176988158642594\n",
"refl:, 0.9575555538987225, 0.5681159420289855, 32.95652945897567, 0.21899518230958334\n",
"refl:, 0.9575555538987225, 0.56, 32.42744085087325, 0.2201600193505694\n",
"refl:, 0.9575555538987225, 0.552112676056338, 31.91621381391884, 0.2211986038256294\n",
"refl:, 0.9575555538987225, 0.5444444444444444, 31.42189714930561, 0.2221192201942536\n",
"refl:, 0.9575555538987225, 0.536986301369863, 30.943610409083956, 0.22293005892732626\n",
"refl:, 0.9575555538987225, 0.5297297297297298, 30.480537056602333, 0.22363546953064717\n",
"refl:, 0.9575555538987225, 0.5226666666666667, 30.031918444163345, 0.22424057729239344\n",
"refl:, 0.9575555538987225, 0.5157894736842105, 29.597048491686717, 0.22475131722696567\n",
"refl:, 0.9575555538987225, 0.509090909090909, 29.17526896927061, 0.22517270735852093\n",
"refl:, 0.9575555538987225, 0.5025641025641026, 28.76596530209651, 0.22550829130360708\n",
"refl:, 0.9575555538987225, 0.4962025316455696, 28.36856282886028, 0.22576168560272664\n",
"refl:, 0.9575555538987225, 0.49, 27.982523455399697, 0.22593769488637538\n",
"refl:, 0.9575555538987225, 0.4839506172839506, 27.60734265386835, 0.22603879926079012\n",
"refl:, 0.9575555538987225, 0.47804878048780486, 27.24254676502359, 0.22606671684807417\n",
"refl:, 0.9575555538987225, 0.47228915662650606, 26.88769056722596, 0.22602615267005247\n",
"refl:, 0.9575555538987225, 0.4666666666666667, 26.54235508080712, 0.2259196867892714\n",
"refl:, 0.9575555538987225, 0.4611764705882353, 26.206145580726076, 0.22574707111781514\n",
"refl:, 0.9575555538987225, 0.4558139534883721, 25.878689794039474, 0.22551123719165922\n",
"refl:, 0.9575555538987225, 0.4505747126436782, 25.55963626177365, 0.22521534349380676\n",
"refl:, 0.9575555538987225, 0.4454545454545454, 25.248652847395146, 0.2248599992539298\n",
"refl:, 0.9575555538987225, 0.44044943820224725, 24.945425376307522, 0.22444833597837902\n",
"refl:, 0.9575555538987225, 0.43555555555555553, 24.64965639271632, 0.2239834956983558\n",
"refl:, 0.9575555538987225, 0.4307692307692308, 24.361064021851533, 0.2234627996648224\n",
"refl:, 0.9575555538987225, 0.4260869565217391, 24.079380926958596, 0.22288475662006782\n",
"refl:, 0.9575555538987225, 0.421505376344086, 23.804353351700417, 0.22225599445518354\n",
"refl:, 0.9575555538987225, 0.41702127659574467, 23.535740239681235, 0.221581310984325\n",
"refl:, 0.9575555538987225, 0.4126315789473684, 23.27331242373393, 0.22085233490014997\n",
"refl:, 0.9575555538987225, 0.4083333333333333, 23.016851878423925, 0.22005799710068308\n",
"refl:, 0.9575555538987225, 0.4041237113402062, 22.76615102993319, 0.2192050777671104\n",
"refl:, 0.9575555538987225, 0.4, 22.521012118111, 0.21831293144861783\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.69549e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00181794 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.17431196343224817 / 0.17431196343224817 = 1.0\n",
"field decay(t = 100.01): 1.2265996190910864e-12 / 0.17431196343224817 = 7.036806854440848e-12\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 4.1008e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.00457215 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.1743119626418479 / 0.1743119626418479 = 1.0\n",
"field decay(t = 100.01): 2.9177363352545384e-11 / 0.1743119626418479 = 1.6738589199695374e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 1.0239400553612397, 0.8, 54.99999999999999, 0.11017776540639429\n",
"refl:, 1.0239400553612397, 0.784, 53.39534223243568, 0.12101496561527146\n",
"refl:, 1.0239400553612397, 0.7686274509803922, 51.90867481651075, 0.1306771391774596\n",
"refl:, 1.0239400553612397, 0.7538461538461539, 50.524208813748004, 0.13937263755149704\n",
"refl:, 1.0239400553612397, 0.739622641509434, 49.22931269112476, 0.14718623029207292\n",
"refl:, 1.0239400553612397, 0.7259259259259259, 48.013685667151286, 0.15426411470561957\n",
"refl:, 1.0239400553612397, 0.7127272727272727, 46.86879216202182, 0.16065288211741083\n",
"refl:, 1.0239400553612397, 0.7, 45.787462696319906, 0.16645430349254092\n",
"refl:, 1.0239400553612397, 0.6877192982456141, 44.7636047370949, 0.17172280994961617\n",
"refl:, 1.0239400553612397, 0.6758620689655173, 43.79198840588911, 0.17652234609536085\n",
"refl:, 1.0239400553612397, 0.664406779661017, 42.868084512177944, 0.18089733371336672\n",
"refl:, 1.0239400553612397, 0.6533333333333333, 41.98794000564178, 0.18488560841000873\n",
"refl:, 1.0239400553612397, 0.6426229508196721, 41.148080731197126, 0.18853239113664866\n",
"refl:, 1.0239400553612397, 0.632258064516129, 40.345434464399176, 0.1918629583011057\n",
"refl:, 1.0239400553612397, 0.6222222222222222, 39.57726925315509, 0.19490950570711735\n",
"refl:, 1.0239400553612397, 0.6124999999999999, 38.841143478370526, 0.197693493807791\n",
"refl:, 1.0239400553612397, 0.6030769230769231, 38.13486500383326, 0.2002377008340049\n",
"refl:, 1.0239400553612397, 0.593939393939394, 37.45645745905701, 0.20256263625319026\n",
"refl:, 1.0239400553612397, 0.5850746268656717, 36.80413218014341, 0.20468094633969736\n",
"refl:, 1.0239400553612397, 0.5764705882352942, 36.176264682924305, 0.2066127525275387\n",
"refl:, 1.0239400553612397, 0.5681159420289855, 35.57137479946729, 0.20837010022232308\n",
"refl:, 1.0239400553612397, 0.56, 34.98810980028866, 0.2099625922722152\n",
"refl:, 1.0239400553612397, 0.552112676056338, 34.42522996870841, 0.21140498333943816\n",
"refl:, 1.0239400553612397, 0.5444444444444444, 33.881596203503065, 0.21270480827886393\n",
"refl:, 1.0239400553612397, 0.536986301369863, 33.35615931039313, 0.2138698898904216\n",
"refl:, 1.0239400553612397, 0.5297297297297298, 32.847950708397136, 0.2149102942440705\n",
"refl:, 1.0239400553612397, 0.5226666666666667, 32.3560743283589, 0.21583196386549577\n",
"refl:, 1.0239400553612397, 0.5157894736842105, 31.87969952142079, 0.21664120771803203\n",
"refl:, 1.0239400553612397, 0.509090909090909, 31.41805482739263, 0.2173447451325115\n",
"refl:, 1.0239400553612397, 0.5025641025641026, 30.97042247873359, 0.21794797391235327\n",
"refl:, 1.0239400553612397, 0.4962025316455696, 30.536133536635912, 0.21845532089955091\n",
"refl:, 1.0239400553612397, 0.49, 30.114563572550164, 0.21887060442537454\n",
"refl:, 1.0239400553612397, 0.4839506172839506, 29.70512882224086, 0.21919938384338775\n",
"refl:, 1.0239400553612397, 0.47804878048780486, 29.307282750744406, 0.21944555930181503\n",
"refl:, 1.0239400553612397, 0.47228915662650606, 28.920512975908146, 0.21961061853019698\n",
"refl:, 1.0239400553612397, 0.4666666666666667, 28.544338505905493, 0.21969923529515722\n",
"refl:, 1.0239400553612397, 0.4611764705882353, 28.178307252549438, 0.2197148009196021\n",
"refl:, 1.0239400553612397, 0.4558139534883721, 27.821993787605123, 0.2196570179143748\n",
"refl:, 1.0239400553612397, 0.4505747126436782, 27.474997313821564, 0.21953044408992073\n",
"refl:, 1.0239400553612397, 0.4454545454545454, 27.13693982621647, 0.21934102718237625\n",
"refl:, 1.0239400553612397, 0.44044943820224725, 26.80746444237855, 0.2190876250731135\n",
"refl:, 1.0239400553612397, 0.43555555555555553, 26.486233883298294, 0.21876881981339763\n",
"refl:, 1.0239400553612397, 0.4307692307692308, 26.172929088582443, 0.2183889418977696\n",
"refl:, 1.0239400553612397, 0.4260869565217391, 25.867247951913267, 0.21795300571421844\n",
"refl:, 1.0239400553612397, 0.421505376344086, 25.56890416433822, 0.2174619823180691\n",
"refl:, 1.0239400553612397, 0.41702127659574467, 25.277626154460066, 0.21691277583436266\n",
"refl:, 1.0239400553612397, 0.4126315789473684, 24.993156115881433, 0.21630289003159692\n",
"refl:, 1.0239400553612397, 0.4083333333333333, 24.715249113370163, 0.21563472861478358\n",
"refl:, 1.0239400553612397, 0.4041237113402062, 24.443672260178424, 0.21491428731801748\n",
"refl:, 1.0239400553612397, 0.4, 24.178203959791162, 0.21414224338441656\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.69549e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00193405 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.16505586379118406 / 0.16505586379118406 = 1.0\n",
"field decay(t = 100.01): 1.6796657965795737e-12 / 0.16505586379118406 = 1.0176347316594321e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 4.1008e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.00460005 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.16505586311279843 / 0.16505586311279843 = 1.0\n",
"field decay(t = 100.01): 3.3223715036954263e-11 / 0.16505586311279843 = 2.0128769987558289e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 1.0825317547305482, 0.8, 59.99999999999999, 0.0735591806237639\n",
"refl:, 1.0825317547305482, 0.784, 58.07108488083593, 0.08751326272230432\n",
"refl:, 1.0825317547305482, 0.7686274509803922, 56.311309260669624, 0.09991502299592077\n",
"refl:, 1.0825317547305482, 0.7538461538461539, 54.69254540505164, 0.11103055503068811\n",
"refl:, 1.0825317547305482, 0.739622641509434, 53.19365179333026, 0.12095912989771326\n",
"refl:, 1.0825317547305482, 0.7259259259259259, 51.798237196004614, 0.12988938721094026\n",
"refl:, 1.0825317547305482, 0.7127272727272727, 50.49327371888257, 0.13795276336817966\n",
"refl:, 1.0825317547305482, 0.7, 49.268194122622916, 0.14525663007066364\n",
"refl:, 1.0825317547305482, 0.6877192982456141, 48.11428082873218, 0.15187367313781958\n",
"refl:, 1.0825317547305482, 0.6758620689655173, 47.024238635081495, 0.15789709160960827\n",
"refl:, 1.0825317547305482, 0.664406779661017, 45.99188753936469, 0.1633722181385885\n",
"refl:, 1.0825317547305482, 0.6533333333333333, 45.01193662107726, 0.16837298204602447\n",
"refl:, 1.0825317547305482, 0.6426229508196721, 44.07981414374115, 0.17292974882236836\n",
"refl:, 1.0825317547305482, 0.632258064516129, 43.191537588393835, 0.17709784614849625\n",
"refl:, 1.0825317547305482, 0.6222222222222222, 42.34361264736431, 0.1809078709487836\n",
"refl:, 1.0825317547305482, 0.6124999999999999, 41.53295361356457, 0.18439488499615878\n",
"refl:, 1.0825317547305482, 0.6030769230769231, 40.756819839298586, 0.1875870463998401\n",
"refl:, 1.0825317547305482, 0.593939393939394, 40.01276444425686, 0.1905058338431826\n",
"refl:, 1.0825317547305482, 0.5850746268656717, 39.298592486049785, 0.19318024997825003\n",
"refl:, 1.0825317547305482, 0.5764705882352942, 38.61232652957572, 0.19562392092427208\n",
"refl:, 1.0825317547305482, 0.5681159420289855, 37.9521780657052, 0.19785775786220766\n",
"refl:, 1.0825317547305482, 0.56, 37.31652360111115, 0.19989832950774553\n",
"refl:, 1.0825317547305482, 0.552112676056338, 36.70388451304266, 0.20175483810150383\n",
"refl:, 1.0825317547305482, 0.5444444444444444, 36.112909964600526, 0.20344366885684412\n",
"refl:, 1.0825317547305482, 0.536986301369863, 35.54236232752769, 0.20497463489294676\n",
"refl:, 1.0825317547305482, 0.5297297297297298, 34.991104674473426, 0.20635674385823924\n",
"refl:, 1.0825317547305482, 0.5226666666666667, 34.4580899908132, 0.20760148101525444\n",
"refl:, 1.0825317547305482, 0.5157894736842105, 33.94235182430718, 0.2087154840835457\n",
"refl:, 1.0825317547305482, 0.509090909090909, 33.442996144127704, 0.2097054505580977\n",
"refl:, 1.0825317547305482, 0.5025641025641026, 32.95919422270091, 0.21057842554599443\n",
"refl:, 1.0825317547305482, 0.4962025316455696, 32.4901763870572, 0.21134139847096645\n",
"refl:, 1.0825317547305482, 0.49, 32.035226512949734, 0.2120001650839906\n",
"refl:, 1.0825317547305482, 0.4839506172839506, 31.593677156370052, 0.21255799660930014\n",
"refl:, 1.0825317547305482, 0.47804878048780486, 31.164905234389202, 0.2130209470984357\n",
"refl:, 1.0825317547305482, 0.47228915662650606, 30.748328181342448, 0.2133940857681709\n",
"refl:, 1.0825317547305482, 0.4666666666666667, 30.343400517915825, 0.21367846587930897\n",
"refl:, 1.0825317547305482, 0.4611764705882353, 29.949610780196405, 0.21387912459727104\n",
"refl:, 1.0825317547305482, 0.4558139534883721, 29.566478763613983, 0.21400172267644174\n",
"refl:, 1.0825317547305482, 0.4505747126436782, 29.193553043244272, 0.2140466258675452\n",
"refl:, 1.0825317547305482, 0.4454545454545454, 28.830408737409662, 0.21401666370463251\n",
"refl:, 1.0825317547305482, 0.44044943820224725, 28.47664548610104, 0.21391675944760216\n",
"refl:, 1.0825317547305482, 0.43555555555555553, 28.131885619609587, 0.21374717744561747\n",
"refl:, 1.0825317547305482, 0.4307692307692308, 27.79577249602797, 0.21350966862372817\n",
"refl:, 1.0825317547305482, 0.4260869565217391, 27.46796898905743, 0.2132082256317414\n",
"refl:, 1.0825317547305482, 0.421505376344086, 27.14815610992485, 0.21284457069627338\n",
"refl:, 1.0825317547305482, 0.41702127659574467, 26.836031749237822, 0.21242137686646906\n",
"refl:, 1.0825317547305482, 0.4126315789473684, 26.531309526343414, 0.2119364849641077\n",
"refl:, 1.0825317547305482, 0.4083333333333333, 26.23371773525153, 0.21138678961842441\n",
"refl:, 1.0825317547305482, 0.4041237113402062, 25.94299837747481, 0.210778113086434\n",
"refl:, 1.0825317547305482, 0.4, 25.65890627325528, 0.21012210961113728\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.79086e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00197196 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.15668265201002066 / 0.15668265201002066 = 1.0\n",
"field decay(t = 100.01): 2.244682331122525e-12 / 0.15668265201002066 = 1.432629778936194e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.91006e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.00452209 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.1566826516265942 / 0.1566826516265942 = 1.0\n",
"field decay(t = 100.01): 3.452976999440086e-11 / 0.1566826516265942 = 2.2038030143051282e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 1.1328847337958123, 0.8, 64.99999999999999, 0.037128559862592\n",
"refl:, 1.1328847337958123, 0.784, 62.645633431180784, 0.0536330451598086\n",
"refl:, 1.1328847337958123, 0.7686274509803922, 60.547811567584965, 0.06876671939925749\n",
"refl:, 1.1328847337958123, 0.7538461538461539, 58.65172469781183, 0.08235712625730884\n",
"refl:, 1.1328847337958123, 0.739622641509434, 56.919780417243786, 0.09463354363126596\n",
"refl:, 1.1328847337958123, 0.7259259259259259, 55.32480276439999, 0.10558417457801342\n",
"refl:, 1.1328847337958123, 0.7127272727272727, 53.84635215217889, 0.11545216623293213\n",
"refl:, 1.1328847337958123, 0.7, 52.468573108244414, 0.12431529050720325\n",
"refl:, 1.1328847337958123, 0.6877192982456141, 51.17885777022349, 0.13235617584005718\n",
"refl:, 1.1328847337958123, 0.6758620689655173, 49.96697533403755, 0.1396274674220686\n",
"refl:, 1.1328847337958123, 0.664406779661017, 48.82448244349733, 0.14625610319510743\n",
"refl:, 1.1328847337958123, 0.6533333333333333, 47.744310665402864, 0.15227959565841903\n",
"refl:, 1.1328847337958123, 0.6426229508196721, 46.720469815981424, 0.15778582117204662\n",
"refl:, 1.1328847337958123, 0.632258064516129, 45.7478295128327, 0.16280641813158056\n",
"refl:, 1.1328847337958123, 0.6222222222222222, 44.82195500406973, 0.16739947756546966\n",
"refl:, 1.1328847337958123, 0.6124999999999999, 43.93898156096055, 0.17159829305125546\n",
"refl:, 1.1328847337958123, 0.6030769230769231, 43.09551684594588, 0.17544425185043788\n",
"refl:, 1.1328847337958123, 0.593939393939394, 42.288563952640665, 0.17897035579329929\n",
"refl:, 1.1328847337958123, 0.5850746268656717, 41.51545997434592, 0.1821986118653532\n",
"refl:, 1.1328847337958123, 0.5764705882352942, 40.77382641078957, 0.18516054972374968\n",
"refl:, 1.1328847337958123, 0.5681159420289855, 40.06152872079658, 0.18786984191653888\n",
"refl:, 1.1328847337958123, 0.56, 39.37664302675111, 0.19035023250949035\n",
"refl:, 1.1328847337958123, 0.552112676056338, 38.717428473384835, 0.19261983460766804\n",
"refl:, 1.1328847337958123, 0.5444444444444444, 38.08230410219336, 0.19469085220660431\n",
"refl:, 1.1328847337958123, 0.536986301369863, 37.4698293655767, 0.19658114960976503\n",
"refl:, 1.1328847337958123, 0.5297297297297298, 36.87868759977799, 0.1983001785222384\n",
"refl:, 1.1328847337958123, 0.5226666666666667, 36.307671922074825, 0.19985845493543128\n",
"refl:, 1.1328847337958123, 0.5157894736842105, 35.75567312877807, 0.2012671524485849\n",
"refl:, 1.1328847337958123, 0.509090909090909, 35.22166925577522, 0.2025355459067762\n",
"refl:, 1.1328847337958123, 0.5025641025641026, 34.70471652928195, 0.20367251569638592\n",
"refl:, 1.1328847337958123, 0.4962025316455696, 34.203941485939055, 0.2046830665024618\n",
"refl:, 1.1328847337958123, 0.49, 33.7185340819115, 0.20557518603611066\n",
"refl:, 1.1328847337958123, 0.4839506172839506, 33.247741642788455, 0.20635576080782017\n",
"refl:, 1.1328847337958123, 0.47804878048780486, 32.790863531764046, 0.20702823770770473\n",
"refl:, 1.1328847337958123, 0.47228915662650606, 32.347246434236666, 0.20759985728196045\n",
"refl:, 1.1328847337958123, 0.4666666666666667, 31.91628017368787, 0.2080745784918885\n",
"refl:, 1.1328847337958123, 0.4611764705882353, 31.497393987322308, 0.20845408884561908\n",
"refl:, 1.1328847337958123, 0.4558139534883721, 31.090053201105746, 0.20874542652135622\n",
"refl:, 1.1328847337958123, 0.4505747126436782, 30.693756253024553, 0.208954041733091\n",
"refl:, 1.1328847337958123, 0.4454545454545454, 30.308032020994055, 0.20908048492966044\n",
"refl:, 1.1328847337958123, 0.44044943820224725, 29.9324374181665, 0.2091260332602117\n",
"refl:, 1.1328847337958123, 0.43555555555555553, 29.5665552236732, 0.20909503137987662\n",
"refl:, 1.1328847337958123, 0.4307692307692308, 29.209992121269647, 0.2089911211638158\n",
"refl:, 1.1328847337958123, 0.4260869565217391, 28.86237692208816, 0.2088197236636275\n",
"refl:, 1.1328847337958123, 0.421505376344086, 28.523358950864424, 0.20858506970983773\n",
"refl:, 1.1328847337958123, 0.41702127659574467, 28.192606577687982, 0.20827627963637158\n",
"refl:, 1.1328847337958123, 0.4126315789473684, 27.86980587961545, 0.20789057239525374\n",
"refl:, 1.1328847337958123, 0.4083333333333333, 27.554659418441407, 0.20744945601962797\n",
"refl:, 1.1328847337958123, 0.4041237113402062, 27.246885122601544, 0.2069758959357581\n",
"refl:, 1.1328847337958123, 0.4, 26.946215262627685, 0.2064567398821898\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.91006e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00178099 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.14944315649486128 / 0.14944315649486128 = 1.0\n",
"field decay(t = 100.01): 4.987937476668207e-12 / 0.14944315649486128 = 3.337682095091267e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 4.19617e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.00460696 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.14944315644072229 / 0.14944315644072229 = 1.0\n",
"field decay(t = 100.01): 3.807851695152499e-11 / 0.14944315644072229 = 2.5480268122300477e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 1.1746157759823854, 0.8, 70.0, 0.008739943705374597\n",
"refl:, 1.1746157759823854, 0.784, 67.05783140972835, 0.024245008080781356\n",
"refl:, 1.1746157759823854, 0.7686274509803922, 64.53417775149677, 0.040309353659514456\n",
"refl:, 1.1746157759823854, 0.7538461538461539, 62.31059707934406, 0.05557589230945354\n",
"refl:, 1.1746157759823854, 0.739622641509434, 60.31629899672389, 0.06970273468511892\n",
"refl:, 1.1746157759823854, 0.7259259259259259, 58.50481213939229, 0.08255233289128476\n",
"refl:, 1.1746157759823854, 0.7127272727272727, 56.843594941553754, 0.09413192002673795\n",
"refl:, 1.1746157759823854, 0.7, 55.30875739675561, 0.10463895552192765\n",
"refl:, 1.1746157759823854, 0.6877192982456141, 53.88211612099151, 0.11407537277856838\n",
"refl:, 1.1746157759823854, 0.6758620689655173, 52.54943143507829, 0.12264564757179623\n",
"refl:, 1.1746157759823854, 0.664406779661017, 51.29929235382265, 0.130398421159986\n",
"refl:, 1.1746157759823854, 0.6533333333333333, 50.122379445158494, 0.13744278277017355\n",
"refl:, 1.1746157759823854, 0.6426229508196721, 49.010959419193355, 0.14384756806524446\n",
"refl:, 1.1746157759823854, 0.632258064516129, 47.958527855818005, 0.1496895084660299\n",
"refl:, 1.1746157759823854, 0.6222222222222222, 46.9595500055931, 0.1550183718219218\n",
"refl:, 1.1746157759823854, 0.6124999999999999, 46.00926848902442, 0.15990604921366627\n",
"refl:, 1.1746157759823854, 0.6030769230769231, 45.103557823882895, 0.16437489242095366\n",
"refl:, 1.1746157759823854, 0.593939393939394, 44.23881248012816, 0.16847755182701835\n",
"refl:, 1.1746157759823854, 0.5850746268656717, 43.41185942214757, 0.17223577319827998\n",
"refl:, 1.1746157759823854, 0.5764705882352942, 42.619888854495166, 0.17567909726641667\n",
"refl:, 1.1746157759823854, 0.5681159420289855, 41.860398715356425, 0.17883983394634828\n",
"refl:, 1.1746157759823854, 0.56, 41.131149701242414, 0.18173430538711705\n",
"refl:, 1.1746157759823854, 0.552112676056338, 40.430128463310105, 0.18439052329945838\n",
"refl:, 1.1746157759823854, 0.5444444444444444, 39.75551721886283, 0.18682349494977193\n",
"refl:, 1.1746157759823854, 0.536986301369863, 39.10566845306894, 0.18904694018036272\n",
"refl:, 1.1746157759823854, 0.5297297297297298, 38.479083699202135, 0.19107722550893155\n",
"refl:, 1.1746157759823854, 0.5226666666666667, 37.87439561623927, 0.19292653635113324\n",
"refl:, 1.1746157759823854, 0.5157894736842105, 37.29035275442276, 0.19460885764872243\n",
"refl:, 1.1746157759823854, 0.509090909090909, 36.72580652885898, 0.19613444229151364\n",
"refl:, 1.1746157759823854, 0.5025641025641026, 36.179700019842116, 0.19751218330354978\n",
"refl:, 1.1746157759823854, 0.4962025316455696, 35.651058294458764, 0.19875050713230683\n",
"refl:, 1.1746157759823854, 0.49, 35.138980002927255, 0.19985575200201458\n",
"refl:, 1.1746157759823854, 0.4839506172839506, 34.64263004924646, 0.20083821988564857\n",
"refl:, 1.1746157759823854, 0.47804878048780486, 34.161233172132036, 0.20170489252979734\n",
"refl:, 1.1746157759823854, 0.47228915662650606, 33.69406830116886, 0.20245705085154594\n",
"refl:, 1.1746157759823854, 0.4666666666666667, 33.24046357629389, 0.20310286904519861\n",
"refl:, 1.1746157759823854, 0.4611764705882353, 32.79979193741594, 0.20364737629446264\n",
"refl:, 1.1746157759823854, 0.4558139534883721, 32.37146720614281, 0.2040929385314762\n",
"refl:, 1.1746157759823854, 0.4505747126436782, 31.954940593960732, 0.20445102567587897\n",
"refl:, 1.1746157759823854, 0.4454545454545454, 31.549697581364857, 0.20471965623854066\n",
"refl:, 1.1746157759823854, 0.44044943820224725, 31.155255120816925, 0.2048962694167634\n",
"refl:, 1.1746157759823854, 0.43555555555555553, 30.771159123350074, 0.204990790346435\n",
"refl:, 1.1746157759823854, 0.4307692307692308, 30.396982194426784, 0.20500592934593215\n",
"refl:, 1.1746157759823854, 0.4260869565217391, 30.032321589495837, 0.20495712156136717\n",
"refl:, 1.1746157759823854, 0.421505376344086, 29.67679736376329, 0.2048311249915097\n",
"refl:, 1.1746157759823854, 0.41702127659574467, 29.33005069412437, 0.2046077238887242\n",
"refl:, 1.1746157759823854, 0.4126315789473684, 28.991742354111988, 0.20432648650919877\n",
"refl:, 1.1746157759823854, 0.4083333333333333, 28.66155132518973, 0.20399611274158247\n",
"refl:, 1.1746157759823854, 0.4041237113402062, 28.339173529827534, 0.20365744502245528\n",
"refl:, 1.1746157759823854, 0.4, 28.024320673604695, 0.20323355142072505\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.8147e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00180006 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.14355855111904067 / 0.14355855111904067 = 1.0\n",
"field decay(t = 100.01): 9.667874472848302e-12 / 0.14355855111904067 = 6.73444695386454e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 4.19617e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.00464296 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.14355855132715553 / 0.14355855132715553 = 1.0\n",
"field decay(t = 100.01): 5.780725980834341e-11 / 0.14355855132715553 = 4.0267374721974217e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 1.2074072828613354, 0.8, 75.0, 0.002256637590250018\n",
"refl:, 1.2074072828613354, 0.784, 71.19254305121969, 0.004043927155760674\n",
"refl:, 1.2074072828613354, 0.7686274509803922, 68.13230108184366, 0.017666840957282458\n",
"refl:, 1.2074072828613354, 0.7538461538461539, 65.5329128763873, 0.0333568804620509\n",
"refl:, 1.2074072828613354, 0.739622641509434, 63.25596068464814, 0.04865237243003264\n",
"refl:, 1.2074072828613354, 0.7259259259259259, 61.22160180379117, 0.06275076172785536\n",
"refl:, 1.2074072828613354, 0.7127272727272727, 59.378629248099124, 0.07575594386491534\n",
"refl:, 1.2074072828613354, 0.7, 57.691773022139905, 0.08757338578695935\n",
"refl:, 1.2074072828613354, 0.6877192982456141, 56.13545775731428, 0.09824417945974033\n",
"refl:, 1.2074072828613354, 0.6758620689655173, 54.69040263962552, 0.10794438844280667\n",
"refl:, 1.2074072828613354, 0.664406779661017, 53.3416232015308, 0.11670036595288552\n",
"refl:, 1.2074072828613354, 0.6533333333333333, 52.0771858356392, 0.12465519843605913\n",
"refl:, 1.2074072828613354, 0.6426229508196721, 50.88739414232009, 0.1318734346297872\n",
"refl:, 1.2074072828613354, 0.632258064516129, 49.76423655717566, 0.13846190112373255\n",
"refl:, 1.2074072828613354, 0.6222222222222222, 48.70099913863975, 0.14446187315076348\n",
"refl:, 1.2074072828613354, 0.6124999999999999, 47.69198665804526, 0.14995944852053927\n",
"refl:, 1.2074072828613354, 0.6030769230769231, 46.73231696062462, 0.1549820926980573\n",
"refl:, 1.2074072828613354, 0.593939393939394, 45.817766249324485, 0.1595835789325249\n",
"refl:, 1.2074072828613354, 0.5850746268656717, 44.94465059915575, 0.16380210131720174\n",
"refl:, 1.2074072828613354, 0.5764705882352942, 44.109733785683, 0.16766536391558942\n",
"refl:, 1.2074072828613354, 0.5681159420289855, 43.31015457776125, 0.17121616499277004\n",
"refl:, 1.2074072828613354, 0.56, 42.543368664412704, 0.17447361559923755\n",
"refl:, 1.2074072828613354, 0.552112676056338, 41.80710174663229, 0.17746600029237136\n",
"refl:, 1.2074072828613354, 0.5444444444444444, 41.099311260706344, 0.1802097333049947\n",
"refl:, 1.2074072828613354, 0.536986301369863, 40.418154855029364, 0.18272225722756205\n",
"refl:, 1.2074072828613354, 0.5297297297297298, 39.76196420912173, 0.18502166386205582\n",
"refl:, 1.2074072828613354, 0.5226666666666667, 39.12922312098109, 0.18712270741981965\n",
"refl:, 1.2074072828613354, 0.5157894736842105, 38.51854903626071, 0.18904224669910968\n",
"refl:, 1.2074072828613354, 0.509090909090909, 37.928677376424204, 0.19078915859924261\n",
"refl:, 1.2074072828613354, 0.5025641025641026, 37.35844816099257, 0.19237299906480013\n",
"refl:, 1.2074072828613354, 0.4962025316455696, 36.806794523773725, 0.19380527183932186\n",
"refl:, 1.2074072828613354, 0.49, 36.272732803336254, 0.19509371745070436\n",
"refl:, 1.2074072828613354, 0.4839506172839506, 35.755353950220794, 0.19624819583455538\n",
"refl:, 1.2074072828613354, 0.47804878048780486, 35.253816041990945, 0.1972786745002075\n",
"refl:, 1.2074072828613354, 0.47228915662650606, 34.76733773550362, 0.1981865257168301\n",
"refl:, 1.2074072828613354, 0.4666666666666667, 34.295192516152845, 0.19897642469530394\n",
"refl:, 1.2074072828613354, 0.4611764705882353, 33.83670362811667, 0.19965916344877177\n",
"refl:, 1.2074072828613354, 0.4558139534883721, 33.391239589169516, 0.2002382841140244\n",
"refl:, 1.2074072828613354, 0.4505747126436782, 32.95821020943854, 0.20072161188836213\n",
"refl:, 1.2074072828613354, 0.4454545454545454, 32.537063046367535, 0.2011093588503599\n",
"refl:, 1.2074072828613354, 0.44044943820224725, 32.12728023870626, 0.20139529444222973\n",
"refl:, 1.2074072828613354, 0.43555555555555553, 31.728375671037586, 0.2015949789880908\n",
"refl:, 1.2074072828613354, 0.4307692307692308, 31.33989242755132, 0.20171523571194905\n",
"refl:, 1.2074072828613354, 0.4260869565217391, 30.96140049976025, 0.20176487549210922\n",
"refl:, 1.2074072828613354, 0.421505376344086, 30.592494717856905, 0.20173258595752414\n",
"refl:, 1.2074072828613354, 0.41702127659574467, 30.23279287960783, 0.20158399392540655\n",
"refl:, 1.2074072828613354, 0.4126315789473684, 29.88193405422147, 0.20138903983141088\n",
"refl:, 1.2074072828613354, 0.4083333333333333, 29.539577041619506, 0.20117661380600185\n",
"refl:, 1.2074072828613354, 0.4041237113402062, 29.2053989700849, 0.2009185301554802\n",
"refl:, 1.2074072828613354, 0.4, 28.879094017427605, 0.2005570833595033\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 3.71933e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00173497 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.13921342756108773 / 0.13921342756108773 = 1.0\n",
"field decay(t = 100.01): 1.3144200426074514e-11 / 0.13921342756108773 = 9.441761945202273e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 4.31538e-05 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.00474286 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.1392134279350055 / 0.1392134279350055 = 1.0\n",
"field decay(t = 100.01): 9.871965143904996e-11 / 0.1392134279350055 = 7.091244925391763e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 1.23100969126526, 0.8, 79.99999999999994, 0.028668309855084118\n",
"refl:, 1.23100969126526, 0.784, 74.82079670263325, 0.002131947030522914\n",
"refl:, 1.23100969126526, 0.7686274509803922, 71.11813585396203, 0.004117095029749368\n",
"refl:, 1.23100969126526, 0.7538461538461539, 68.12392493650243, 0.01750499625965161\n",
"refl:, 1.23100969126526, 0.739622641509434, 65.57213417097068, 0.032817770182446984\n",
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]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.007622 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.23946072431081186 / 0.23946072431081186 = 1.0\n",
"field decay(t = 100.01): 2.143367304660103e-13 / 0.23946072431081186 = 8.950809410724429e-13\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000111818 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.0173719 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.23946072470582727 / 0.23946072470582727 = 1.0\n",
"field decay(t = 100.01): 2.2924410648414684e-11 / 0.23946072470582727 = 9.573348897434795e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.4275251791570859, 0.8, 20.0, 0.27287026974445927\n",
"refl:, 0.4275251791570859, 0.784, 19.583468236198428, 0.2732024101218738\n",
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"refl:, 0.4275251791570859, 0.4260869565217391, 10.495768170772996, 0.2481743775271508\n",
"refl:, 0.4275251791570859, 0.421505376344086, 10.381651859681224, 0.24690419443990608\n",
"refl:, 0.4275251791570859, 0.41702127659574467, 10.270003864057921, 0.2456037441531416\n",
"refl:, 0.4275251791570859, 0.4126315789473684, 10.160744525922071, 0.24427554305470142\n",
"refl:, 0.4275251791570859, 0.4083333333333333, 10.053797596639106, 0.2429193465329389\n",
"refl:, 0.4275251791570859, 0.4041237113402062, 9.949090055502005, 0.24153322642643202\n",
"refl:, 0.4275251791570859, 0.4, 9.846551939834079, 0.2401180039660742\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000110865 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00934601 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.23217567515545764 / 0.23217567515545764 = 1.0\n",
"field decay(t = 100.01): 3.1895846890533654e-13 / 0.23217567515545764 = 1.3737807317315728e-12\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000108957 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.016118 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.23217567572617967 / 0.23217567572617967 = 1.0\n",
"field decay(t = 100.01): 2.511386584143695e-11 / 0.23217567572617967 = 1.0816751480484724e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.5282728271758743, 0.8, 25.0, 0.2601481976279196\n",
"refl:, 0.5282728271758743, 0.784, 24.46679999189225, 0.2610696372423531\n",
"refl:, 0.5282728271758743, 0.7686274509803922, 23.95662859236144, 0.2618770325163737\n",
"refl:, 0.5282728271758743, 0.7538461538461539, 23.467975961566616, 0.2625788276586943\n",
"refl:, 0.5282728271758743, 0.739622641509434, 22.99946566139384, 0.2631817618626755\n",
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"refl:, 0.5282728271758743, 0.49, 15.002054761894165, 0.2568889467859571\n",
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"refl:, 0.5282728271758743, 0.47228915662650606, 14.44778048381156, 0.25436772779199046\n",
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"refl:, 0.5282728271758743, 0.4260869565217391, 13.008180017272103, 0.24505436171970374\n",
"refl:, 0.5282728271758743, 0.421505376344086, 12.865893919575512, 0.24385825418409707\n",
"refl:, 0.5282728271758743, 0.41702127659574467, 12.726713297162874, 0.2426284381212972\n",
"refl:, 0.5282728271758743, 0.4126315789473684, 12.590536722774571, 0.24136614460408662\n",
"refl:, 0.5282728271758743, 0.4083333333333333, 12.457267175263851, 0.24007405600657153\n",
"refl:, 0.5282728271758743, 0.4041237113402062, 12.326811800951434, 0.238751417728497\n",
"refl:, 0.5282728271758743, 0.4, 12.199081690448809, 0.2373967326334257\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000108004 s\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00868416 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.22375100718842 / 0.22375100718842 = 1.0\n",
"field decay(t = 100.01): 4.4054832270861915e-13 / 0.22375100718842 = 1.9689221883038714e-12\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000108957 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.0171471 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.22375100783149995 / 0.22375100783149995 = 1.0\n",
"field decay(t = 100.01): 2.604590852088861e-11 / 0.22375100783149995 = 1.1640577074183724e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.6249999999999999, 0.8, 29.999999999999993, 0.2442050337697129\n",
"refl:, 0.6249999999999999, 0.784, 29.34058157502373, 0.24592026654412946\n",
"refl:, 0.6249999999999999, 0.7686274509803922, 28.711017527148794, 0.2474593095717218\n",
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"refl:, 0.6249999999999999, 0.7, 25.944479772370002, 0.2529918131418104\n",
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"refl:, 0.6249999999999999, 0.56, 20.487315114722662, 0.256248873599916\n",
"refl:, 0.6249999999999999, 0.552112676056338, 20.186094678183196, 0.25601329709669296\n",
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"refl:, 0.6249999999999999, 0.49, 17.833382709813034, 0.251843602956665\n",
"refl:, 0.6249999999999999, 0.4839506172839506, 17.605965665348197, 0.25117351956545597\n",
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"refl:, 0.6249999999999999, 0.47228915662650606, 17.168374620396104, 0.2497220477831976\n",
"refl:, 0.6249999999999999, 0.4666666666666667, 16.957763300004142, 0.24893902021832587\n",
"refl:, 0.6249999999999999, 0.4611764705882353, 16.752335113553887, 0.24811948817045582\n",
"refl:, 0.6249999999999999, 0.4558139534883721, 16.551898155026578, 0.24726486187036864\n",
"refl:, 0.6249999999999999, 0.4505747126436782, 16.35627001847215, 0.24637335126615545\n",
"refl:, 0.6249999999999999, 0.4454545454545454, 16.165277208722518, 0.24544445758208924\n",
"refl:, 0.6249999999999999, 0.44044943820224725, 15.978754596053776, 0.24448044797494067\n",
"refl:, 0.6249999999999999, 0.43555555555555553, 15.796544910968182, 0.24348141406546195\n",
"refl:, 0.6249999999999999, 0.4307692307692308, 15.618498275648548, 0.24244508607372425\n",
"refl:, 0.6249999999999999, 0.4260869565217391, 15.44447176897603, 0.24137187009594935\n",
"refl:, 0.6249999999999999, 0.421505376344086, 15.274329022304034, 0.2402639528246127\n",
"refl:, 0.6249999999999999, 0.41702127659574467, 15.107939843449019, 0.23912065251888115\n",
"refl:, 0.6249999999999999, 0.4126315789473684, 14.94517986659885, 0.23794038016947253\n",
"refl:, 0.6249999999999999, 0.4083333333333333, 14.78593022605342, 0.23672496742401775\n",
"refl:, 0.6249999999999999, 0.4041237113402062, 14.630077251904048, 0.23547697979370008\n",
"refl:, 0.6249999999999999, 0.4, 14.477512185929921, 0.23419574038931623\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000112057 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00802183 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.2144470639002981 / 0.2144470639002981 = 1.0\n",
"field decay(t = 100.01): 5.749510870152026e-13 / 0.2144470639002981 = 2.6810863089387505e-12\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000110865 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.016397 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.21444706445458073 / 0.21444706445458073 = 1.0\n",
"field decay(t = 100.01): 2.737725032991902e-11 / 0.21444706445458073 = 1.276643744205575e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.7169705454388076, 0.8, 35.0, 0.22482605012853205\n",
"refl:, 0.7169705454388076, 0.784, 34.201491482224874, 0.2275879297659293\n",
"refl:, 0.7169705454388076, 0.7686274509803922, 33.4413597291606, 0.2300861771421993\n",
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"refl:, 0.7169705454388076, 0.4260869565217391, 17.787754068005896, 0.23720797538105634\n",
"refl:, 0.7169705454388076, 0.421505376344086, 17.590205358285754, 0.236202366418755\n",
"refl:, 0.7169705454388076, 0.41702127659574467, 17.39706870053973, 0.23515820136339463\n",
"refl:, 0.7169705454388076, 0.4126315789473684, 17.20819547960629, 0.2340750107196232\n",
"refl:, 0.7169705454388076, 0.4083333333333333, 17.02344378999232, 0.2329510888033509\n",
"refl:, 0.7169705454388076, 0.4041237113402062, 16.842678055366356, 0.23178864386805378\n",
"refl:, 0.7169705454388076, 0.4, 16.665768674058118, 0.2305906700422077\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000108957 s\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00882411 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.20454876789491885 / 0.20454876789491885 = 1.0\n",
"field decay(t = 100.01): 7.178635175771892e-13 / 0.20454876789491885 = 3.509498125874663e-12\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000108004 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.018625 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.20454876813558592 / 0.20454876813558592 = 1.0\n",
"field decay(t = 100.01): 2.8174572450318613e-11 / 0.20454876813558592 = 1.3774012284270024e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.8034845121081741, 0.8, 39.99999999999999, 0.20179462162966672\n",
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"refl:, 0.8034845121081741, 0.4126315789473684, 19.362461125837058, 0.22986107450928206\n",
"refl:, 0.8034845121081741, 0.4083333333333333, 19.15285742585141, 0.2288423958877941\n",
"refl:, 0.8034845121081741, 0.4041237113402062, 18.9478332876545, 0.22777913143869027\n",
"refl:, 0.8034845121081741, 0.4, 18.747237251037504, 0.22667336344348024\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000111103 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.006598 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.1943564114319847 / 0.1943564114319847 = 1.0\n",
"field decay(t = 100.01): 8.613369505850488e-13 / 0.1943564114319847 = 4.431739319731548e-12\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000108004 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.0163691 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.1943564112167818 / 0.1943564112167818 = 1.0\n",
"field decay(t = 100.01): 2.929219089217826e-11 / 0.1943564112167818 = 1.5071378766870859e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.8838834764831843, 0.8, 44.99999999999999, 0.1749506546010766\n",
"refl:, 0.8838834764831843, 0.784, 43.865246854678944, 0.18084614262894314\n",
"refl:, 0.8838834764831843, 0.7686274509803922, 42.79498686880298, 0.18616490888473136\n",
"refl:, 0.8838834764831843, 0.7538461538461539, 41.78306957363623, 0.1909834896778329\n",
"refl:, 0.8838834764831843, 0.739622641509434, 40.82419653278361, 0.1953532231998348\n",
"refl:, 0.8838834764831843, 0.7259259259259259, 39.913765803587594, 0.19932045676242707\n",
"refl:, 0.8838834764831843, 0.7127272727272727, 39.047751315763335, 0.20293092176670602\n",
"refl:, 0.8838834764831843, 0.7, 38.2226079814105, 0.20621465898807328\n",
"refl:, 0.8838834764831843, 0.6877192982456141, 37.435196089128915, 0.20920558346668153\n",
"refl:, 0.8838834764831843, 0.6758620689655173, 36.682720369951866, 0.21192936258982145\n",
"refl:, 0.8838834764831843, 0.664406779661017, 35.962680378531154, 0.2144091185242741\n",
"refl:, 0.8838834764831843, 0.6533333333333333, 35.272829708778914, 0.21666666414632094\n",
"refl:, 0.8838834764831843, 0.6426229508196721, 34.61114218453038, 0.2187182335956619\n",
"refl:, 0.8838834764831843, 0.632258064516129, 33.975783613579615, 0.22058228827610923\n",
"refl:, 0.8838834764831843, 0.6222222222222222, 33.36508802077569, 0.22227211810191635\n",
"refl:, 0.8838834764831843, 0.6124999999999999, 32.77753751829758, 0.22379917822267162\n",
"refl:, 0.8838834764831843, 0.6030769230769231, 32.21174515294742, 0.225178014297656\n",
"refl:, 0.8838834764831843, 0.593939393939394, 31.666440208036935, 0.22641701701757366\n",
"refl:, 0.8838834764831843, 0.5850746268656717, 31.14045554291693, 0.22752429105750807\n",
"refl:, 0.8838834764831843, 0.5764705882352942, 30.6327166347442, 0.22851103000945724\n",
"refl:, 0.8838834764831843, 0.5681159420289855, 30.142232050688204, 0.2293833309292736\n",
"refl:, 0.8838834764831843, 0.56, 29.66808512880701, 0.23014665030198314\n",
"refl:, 0.8838834764831843, 0.552112676056338, 29.20942668547734, 0.2308091072410071\n",
"refl:, 0.8838834764831843, 0.5444444444444444, 28.765468598924116, 0.23137604508998047\n",
"refl:, 0.8838834764831843, 0.536986301369863, 28.33547814384704, 0.23185120425684555\n",
"refl:, 0.8838834764831843, 0.5297297297297298, 27.91877297273401, 0.23223967284122596\n",
"refl:, 0.8838834764831843, 0.5226666666666667, 27.514716656212954, 0.23254649427327514\n",
"refl:, 0.8838834764831843, 0.5157894736842105, 27.12271470851516, 0.23277497605931805\n",
"refl:, 0.8838834764831843, 0.509090909090909, 26.742211035417114, 0.2329274877105852\n",
"refl:, 0.8838834764831843, 0.5025641025641026, 26.372684751370738, 0.23300817835325607\n",
"refl:, 0.8838834764831843, 0.4962025316455696, 26.013647320299032, 0.23302096475520206\n",
"refl:, 0.8838834764831843, 0.49, 25.66463998102006, 0.23296661309174865\n",
"refl:, 0.8838834764831843, 0.4839506172839506, 25.32523142370283, 0.2328473819749458\n",
"refl:, 0.8838834764831843, 0.47804878048780486, 24.99501568834094, 0.23266777547883646\n",
"refl:, 0.8838834764831843, 0.47228915662650606, 24.673610260104642, 0.2324286704369094\n",
"refl:, 0.8838834764831843, 0.4666666666666667, 24.360654339720863, 0.23213016162250638\n",
"refl:, 0.8838834764831843, 0.4611764705882353, 24.055807269832574, 0.23177609164136181\n",
"refl:, 0.8838834764831843, 0.4558139534883721, 23.75874710068368, 0.2313686559958002\n",
"refl:, 0.8838834764831843, 0.4505747126436782, 23.46916928052956, 0.23090689658521463\n",
"refl:, 0.8838834764831843, 0.4454545454545454, 23.18678545794031, 0.23039248392782377\n",
"refl:, 0.8838834764831843, 0.44044943820224725, 22.911322384688706, 0.22982847953509086\n",
"refl:, 0.8838834764831843, 0.43555555555555553, 22.64252090923418, 0.22921468760037644\n",
"refl:, 0.8838834764831843, 0.4307692307692308, 22.380135051959574, 0.2285503145110825\n",
"refl:, 0.8838834764831843, 0.4260869565217391, 22.123931154313652, 0.22783728199610298\n",
"refl:, 0.8838834764831843, 0.421505376344086, 21.873687094881706, 0.22707701516938034\n",
"refl:, 0.8838834764831843, 0.41702127659574467, 21.629191566166806, 0.226267933168201\n",
"refl:, 0.8838834764831843, 0.4126315789473684, 21.390243406530644, 0.22540929123705422\n",
"refl:, 0.8838834764831843, 0.4083333333333333, 21.156650982328358, 0.22450324859888127\n",
"refl:, 0.8838834764831843, 0.4041237113402062, 20.928231615787418, 0.2235503997974889\n",
"refl:, 0.8838834764831843, 0.4, 20.704811054635428, 0.22254911459777174\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000109911 s\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.006423 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.18417632037527257 / 0.18417632037527257 = 1.0\n",
"field decay(t = 100.01): 1.0178427595748204e-12 / 0.18417632037527257 = 5.5264583280895835e-12\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000110865 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.0184629 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.18417631975521828 / 0.18417631975521828 = 1.0\n",
"field decay(t = 100.01): 2.8713012611847576e-11 / 0.18417631975521828 = 1.5589958931750262e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.9575555538987225, 0.8, 50.0, 0.14429067301668\n",
"refl:, 0.9575555538987225, 0.784, 48.6530933185261, 0.15241249489296654\n",
"refl:, 0.9575555538987225, 0.7686274509803922, 47.39207738436693, 0.15970237410745958\n",
"refl:, 0.9575555538987225, 0.7538461538461539, 46.207396358038395, 0.16628917742963503\n",
"refl:, 0.9575555538987225, 0.739622641509434, 45.091066324150106, 0.1722363131532337\n",
"refl:, 0.9575555538987225, 0.7259259259259259, 44.036334278275795, 0.1776288135399773\n",
"refl:, 0.9575555538987225, 0.7127272727272727, 43.037427456538545, 0.1825236470768417\n",
"refl:, 0.9575555538987225, 0.7, 42.089365210987516, 0.1869718164862598\n",
"refl:, 0.9575555538987225, 0.6877192982456141, 41.18781524255363, 0.19102552097133876\n",
"refl:, 0.9575555538987225, 0.6758620689655173, 40.32898196453324, 0.19471651743120957\n",
"refl:, 0.9575555538987225, 0.664406779661017, 39.50951857909891, 0.1980846376246996\n",
"refl:, 0.9575555538987225, 0.6533333333333333, 38.726456948394606, 0.20115681830261414\n",
"refl:, 0.9575555538987225, 0.6426229508196721, 37.97715101972185, 0.20395988101926588\n",
"refl:, 0.9575555538987225, 0.632258064516129, 37.25923071465613, 0.20651807398114963\n",
"refl:, 0.9575555538987225, 0.6222222222222222, 36.57056399547784, 0.20884957043569513\n",
"refl:, 0.9575555538987225, 0.6124999999999999, 35.909225393217994, 0.21097550520798009\n",
"refl:, 0.9575555538987225, 0.6030769230769231, 35.273469693564564, 0.21290924565401623\n",
"refl:, 0.9575555538987225, 0.593939393939394, 34.6617097783444, 0.214665416754943\n",
"refl:, 0.9575555538987225, 0.5850746268656717, 34.07249784378941, 0.2162593463941121\n",
"refl:, 0.9575555538987225, 0.5764705882352942, 33.504509384470694, 0.21769885837479563\n",
"refl:, 0.9575555538987225, 0.5681159420289855, 32.95652945897567, 0.2189956192414337\n",
"refl:, 0.9575555538987225, 0.56, 32.42744085087325, 0.22016058268759847\n",
"refl:, 0.9575555538987225, 0.552112676056338, 31.91621381391884, 0.22119898455404\n",
"refl:, 0.9575555538987225, 0.5444444444444444, 31.42189714930561, 0.22211935917204448\n",
"refl:, 0.9575555538987225, 0.536986301369863, 30.943610409083956, 0.2229298821236265\n",
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"refl:, 0.9575555538987225, 0.5157894736842105, 29.597048491686717, 0.22475115535497284\n",
"refl:, 0.9575555538987225, 0.509090909090909, 29.17526896927061, 0.2251729335780506\n",
"refl:, 0.9575555538987225, 0.5025641025641026, 28.76596530209651, 0.22550858491249842\n",
"refl:, 0.9575555538987225, 0.4962025316455696, 28.36856282886028, 0.22576196217784258\n",
"refl:, 0.9575555538987225, 0.49, 27.982523455399697, 0.22593807040959396\n",
"refl:, 0.9575555538987225, 0.4839506172839506, 27.60734265386835, 0.22603917633476883\n",
"refl:, 0.9575555538987225, 0.47804878048780486, 27.24254676502359, 0.22606684493527063\n",
"refl:, 0.9575555538987225, 0.47228915662650606, 26.88769056722596, 0.22602594884033364\n",
"refl:, 0.9575555538987225, 0.4666666666666667, 26.54235508080712, 0.22591913511748662\n",
"refl:, 0.9575555538987225, 0.4611764705882353, 26.206145580726076, 0.2257461894573964\n",
"refl:, 0.9575555538987225, 0.4558139534883721, 25.878689794039474, 0.2255106337747593\n",
"refl:, 0.9575555538987225, 0.4505747126436782, 25.55963626177365, 0.22521611643853037\n",
"refl:, 0.9575555538987225, 0.4454545454545454, 25.248652847395146, 0.2248621048576318\n",
"refl:, 0.9575555538987225, 0.44044943820224725, 24.945425376307522, 0.2244497571914091\n",
"refl:, 0.9575555538987225, 0.43555555555555553, 24.64965639271632, 0.22398274531115286\n",
"refl:, 0.9575555538987225, 0.4307692307692308, 24.361064021851533, 0.22346171326862457\n",
"refl:, 0.9575555538987225, 0.4260869565217391, 24.079380926958596, 0.22288585592315466\n",
"refl:, 0.9575555538987225, 0.421505376344086, 23.804353351700417, 0.22225690920257898\n",
"refl:, 0.9575555538987225, 0.41702127659574467, 23.535740239681235, 0.22157652716566317\n",
"refl:, 0.9575555538987225, 0.4126315789473684, 23.27331242373393, 0.22084351574148542\n",
"refl:, 0.9575555538987225, 0.4083333333333333, 23.016851878423925, 0.220057130518136\n",
"refl:, 0.9575555538987225, 0.4041237113402062, 22.76615102993319, 0.21921919579654955\n",
"refl:, 0.9575555538987225, 0.4, 22.521012118111, 0.21832995493951468\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000108004 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00824594 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.17431196343224772 / 0.17431196343224772 = 1.0\n",
"field decay(t = 100.01): 1.226599619152291e-12 / 0.17431196343224772 = 7.0368068547919865e-12\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000108957 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.0162461 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.17431196264184795 / 0.17431196264184795 = 1.0\n",
"field decay(t = 100.01): 2.9177363356244976e-11 / 0.17431196264184795 = 1.6738589201817764e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 1.0239400553612397, 0.8, 54.99999999999999, 0.11015750327021501\n",
"refl:, 1.0239400553612397, 0.784, 53.39534223243568, 0.12100519786278613\n",
"refl:, 1.0239400553612397, 0.7686274509803922, 51.90867481651075, 0.13067356321855755\n",
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"refl:, 1.0239400553612397, 0.7259259259259259, 48.013685667151286, 0.15425442212255983\n",
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"refl:, 1.0239400553612397, 0.5025641025641026, 30.97042247873359, 0.2179480717640861\n",
"refl:, 1.0239400553612397, 0.4962025316455696, 30.536133536635912, 0.21845549976557374\n",
"refl:, 1.0239400553612397, 0.49, 30.114563572550164, 0.21887075023784372\n",
"refl:, 1.0239400553612397, 0.4839506172839506, 29.70512882224086, 0.21919941164026552\n",
"refl:, 1.0239400553612397, 0.47804878048780486, 29.307282750744406, 0.21944546389616373\n",
"refl:, 1.0239400553612397, 0.47228915662650606, 28.920512975908146, 0.21961022544356806\n",
"refl:, 1.0239400553612397, 0.4666666666666667, 28.544338505905493, 0.2196984674330614\n",
"refl:, 1.0239400553612397, 0.4611764705882353, 28.178307252549438, 0.21971428386147993\n",
"refl:, 1.0239400553612397, 0.4558139534883721, 27.821993787605123, 0.21965764862748693\n",
"refl:, 1.0239400553612397, 0.4505747126436782, 27.474997313821564, 0.21953193965864698\n",
"refl:, 1.0239400553612397, 0.4454545454545454, 27.13693982621647, 0.21934178652625613\n",
"refl:, 1.0239400553612397, 0.44044943820224725, 26.80746444237855, 0.21908700093353123\n",
"refl:, 1.0239400553612397, 0.43555555555555553, 26.486233883298294, 0.21876853077786598\n",
"refl:, 1.0239400553612397, 0.4307692307692308, 26.172929088582443, 0.2183905958409472\n",
"refl:, 1.0239400553612397, 0.4260869565217391, 25.867247951913267, 0.21795488284012238\n",
"refl:, 1.0239400553612397, 0.421505376344086, 25.56890416433822, 0.21746063743615796\n",
"refl:, 1.0239400553612397, 0.41702127659574467, 25.277626154460066, 0.21690850348145124\n",
"refl:, 1.0239400553612397, 0.4126315789473684, 24.993156115881433, 0.21630059246127992\n",
"refl:, 1.0239400553612397, 0.4083333333333333, 24.715249113370163, 0.21563737630418256\n",
"refl:, 1.0239400553612397, 0.4041237113402062, 24.443672260178424, 0.2149184652144797\n",
"refl:, 1.0239400553612397, 0.4, 24.178203959791162, 0.2141434469115452\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000112057 s\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.0063448 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.16505586379118362 / 0.16505586379118362 = 1.0\n",
"field decay(t = 100.01): 1.6796657955389861e-12 / 0.16505586379118362 = 1.0176347310289891e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000111818 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.020278 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.16505586311279807 / 0.16505586311279807 = 1.0\n",
"field decay(t = 100.01): 3.3223715038456985e-11 / 0.16505586311279807 = 2.0128769988468766e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 1.0825317547305482, 0.8, 59.99999999999999, 0.07360773441443474\n",
"refl:, 1.0825317547305482, 0.784, 58.07108488083593, 0.08756183349395384\n",
"refl:, 1.0825317547305482, 0.7686274509803922, 56.311309260669624, 0.09993186958234106\n",
"refl:, 1.0825317547305482, 0.7538461538461539, 54.69254540505164, 0.11102792920544496\n",
"refl:, 1.0825317547305482, 0.739622641509434, 53.19365179333026, 0.12095671757064261\n",
"refl:, 1.0825317547305482, 0.7259259259259259, 51.798237196004614, 0.12989111490169047\n",
"refl:, 1.0825317547305482, 0.7127272727272727, 50.49327371888257, 0.13795385843502186\n",
"refl:, 1.0825317547305482, 0.7, 49.268194122622916, 0.14525656081749277\n",
"refl:, 1.0825317547305482, 0.6877192982456141, 48.11428082873218, 0.15187584382721003\n",
"refl:, 1.0825317547305482, 0.6758620689655173, 47.024238635081495, 0.15790192109849083\n",
"refl:, 1.0825317547305482, 0.664406779661017, 45.99188753936469, 0.16337692994168027\n",
"refl:, 1.0825317547305482, 0.6533333333333333, 45.01193662107726, 0.16837576220748254\n",
"refl:, 1.0825317547305482, 0.6426229508196721, 44.07981414374115, 0.1729308563822558\n",
"refl:, 1.0825317547305482, 0.632258064516129, 43.191537588393835, 0.17709787538099556\n",
"refl:, 1.0825317547305482, 0.6222222222222222, 42.34361264736431, 0.18090702518494378\n",
"refl:, 1.0825317547305482, 0.6124999999999999, 41.53295361356457, 0.18439374819992094\n",
"refl:, 1.0825317547305482, 0.6030769230769231, 40.756819839298586, 0.1875864032458676\n",
"refl:, 1.0825317547305482, 0.593939393939394, 40.01276444425686, 0.1905057507798468\n",
"refl:, 1.0825317547305482, 0.5850746268656717, 39.298592486049785, 0.19318030905511865\n",
"refl:, 1.0825317547305482, 0.5764705882352942, 38.61232652957572, 0.1956239605857035\n",
"refl:, 1.0825317547305482, 0.5681159420289855, 37.9521780657052, 0.19785784772625742\n",
"refl:, 1.0825317547305482, 0.56, 37.31652360111115, 0.19989839276598212\n",
"refl:, 1.0825317547305482, 0.552112676056338, 36.70388451304266, 0.2017547526768604\n",
"refl:, 1.0825317547305482, 0.5444444444444444, 36.112909964600526, 0.20344360330889855\n",
"refl:, 1.0825317547305482, 0.536986301369863, 35.54236232752769, 0.20497480625666326\n",
"refl:, 1.0825317547305482, 0.5297297297297298, 34.991104674473426, 0.20635699484209216\n",
"refl:, 1.0825317547305482, 0.5226666666666667, 34.4580899908132, 0.20760151265764157\n",
"refl:, 1.0825317547305482, 0.5157894736842105, 33.94235182430718, 0.20871528450622134\n",
"refl:, 1.0825317547305482, 0.509090909090909, 33.442996144127704, 0.20970524738496094\n",
"refl:, 1.0825317547305482, 0.5025641025641026, 32.95919422270091, 0.2105783514069682\n",
"refl:, 1.0825317547305482, 0.4962025316455696, 32.4901763870572, 0.2113414215404359\n",
"refl:, 1.0825317547305482, 0.49, 32.035226512949734, 0.21200027362523924\n",
"refl:, 1.0825317547305482, 0.4839506172839506, 31.593677156370052, 0.21255807961996584\n",
"refl:, 1.0825317547305482, 0.47804878048780486, 31.164905234389202, 0.21302071809138926\n",
"refl:, 1.0825317547305482, 0.47228915662650606, 30.748328181342448, 0.21339356617448996\n",
"refl:, 1.0825317547305482, 0.4666666666666667, 30.343400517915825, 0.2136782430141135\n",
"refl:, 1.0825317547305482, 0.4611764705882353, 29.949610780196405, 0.21387969509149066\n",
"refl:, 1.0825317547305482, 0.4558139534883721, 29.566478763613983, 0.2140025648813409\n",
"refl:, 1.0825317547305482, 0.4505747126436782, 29.193553043244272, 0.21404664550288702\n",
"refl:, 1.0825317547305482, 0.4454545454545454, 28.830408737409662, 0.2140158741099825\n",
"refl:, 1.0825317547305482, 0.44044943820224725, 28.47664548610104, 0.2139163515040305\n",
"refl:, 1.0825317547305482, 0.43555555555555553, 28.131885619609587, 0.213747755347228\n",
"refl:, 1.0825317547305482, 0.4307692307692308, 27.79577249602797, 0.2135103221579689\n",
"refl:, 1.0825317547305482, 0.4260869565217391, 27.46796898905743, 0.21320790783224955\n",
"refl:, 1.0825317547305482, 0.421505376344086, 27.14815610992485, 0.2128440342182022\n",
"refl:, 1.0825317547305482, 0.41702127659574467, 26.836031749237822, 0.21242171734687695\n",
"refl:, 1.0825317547305482, 0.4126315789473684, 26.531309526343414, 0.21193780892543815\n",
"refl:, 1.0825317547305482, 0.4083333333333333, 26.23371773525153, 0.21138950860192895\n",
"refl:, 1.0825317547305482, 0.4041237113402062, 25.94299837747481, 0.21078013578978685\n",
"refl:, 1.0825317547305482, 0.4, 25.65890627325528, 0.2101171783272214\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000109911 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00752401 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.15668265201002152 / 0.15668265201002152 = 1.0\n",
"field decay(t = 100.01): 2.2446823295144107e-12 / 0.15668265201002152 = 1.4326297779098349e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000112057 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.0143809 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.1566826516265948 / 0.1566826516265948 = 1.0\n",
"field decay(t = 100.01): 3.452976998428892e-11 / 0.1566826516265948 = 2.2038030136597423e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 1.1328847337958123, 0.8, 64.99999999999999, 0.037170886043112084\n",
"refl:, 1.1328847337958123, 0.784, 62.645633431180784, 0.05362783985573467\n",
"refl:, 1.1328847337958123, 0.7686274509803922, 60.547811567584965, 0.06875709351287543\n",
"refl:, 1.1328847337958123, 0.7538461538461539, 58.65172469781183, 0.082354616478198\n",
"refl:, 1.1328847337958123, 0.739622641509434, 56.919780417243786, 0.09462755396270182\n",
"refl:, 1.1328847337958123, 0.7259259259259259, 55.32480276439999, 0.10557645638030469\n",
"refl:, 1.1328847337958123, 0.7127272727272727, 53.84635215217889, 0.11544950273548941\n",
"refl:, 1.1328847337958123, 0.7, 52.468573108244414, 0.1243168343725702\n",
"refl:, 1.1328847337958123, 0.6877192982456141, 51.17885777022349, 0.13235703881433808\n",
"refl:, 1.1328847337958123, 0.6758620689655173, 49.96697533403755, 0.139626360552005\n",
"refl:, 1.1328847337958123, 0.664406779661017, 48.82448244349733, 0.14625471025031767\n",
"refl:, 1.1328847337958123, 0.6533333333333333, 47.744310665402864, 0.1522788790416092\n",
"refl:, 1.1328847337958123, 0.6426229508196721, 46.720469815981424, 0.1577852862490647\n",
"refl:, 1.1328847337958123, 0.632258064516129, 45.7478295128327, 0.16280555175366354\n",
"refl:, 1.1328847337958123, 0.6222222222222222, 44.82195500406973, 0.167398621072885\n",
"refl:, 1.1328847337958123, 0.6124999999999999, 43.93898156096055, 0.17159777718924688\n",
"refl:, 1.1328847337958123, 0.6030769230769231, 43.09551684594588, 0.17544391308281032\n",
"refl:, 1.1328847337958123, 0.593939393939394, 42.288563952640665, 0.1789701508099767\n",
"refl:, 1.1328847337958123, 0.5850746268656717, 41.51545997434592, 0.18219866439447\n",
"refl:, 1.1328847337958123, 0.5764705882352942, 40.77382641078957, 0.185160771243366\n",
"refl:, 1.1328847337958123, 0.5681159420289855, 40.06152872079658, 0.18786997681737858\n",
"refl:, 1.1328847337958123, 0.56, 39.37664302675111, 0.19035022781311492\n",
"refl:, 1.1328847337958123, 0.552112676056338, 38.717428473384835, 0.19261993394590182\n",
"refl:, 1.1328847337958123, 0.5444444444444444, 38.08230410219336, 0.19469110743273724\n",
"refl:, 1.1328847337958123, 0.536986301369863, 37.4698293655767, 0.1965812755931606\n",
"refl:, 1.1328847337958123, 0.5297297297297298, 36.87868759977799, 0.19830004161335185\n",
"refl:, 1.1328847337958123, 0.5226666666666667, 36.307671922074825, 0.19985824848269654\n",
"refl:, 1.1328847337958123, 0.5157894736842105, 35.75567312877807, 0.20126711563403166\n",
"refl:, 1.1328847337958123, 0.509090909090909, 35.22166925577522, 0.20253568251243403\n",
"refl:, 1.1328847337958123, 0.5025641025641026, 34.70471652928195, 0.2036726801968963\n",
"refl:, 1.1328847337958123, 0.4962025316455696, 34.203941485939055, 0.20468320295652365\n",
"refl:, 1.1328847337958123, 0.49, 33.7185340819115, 0.20557517176695547\n",
"refl:, 1.1328847337958123, 0.4839506172839506, 33.247741642788455, 0.20635542059630924\n",
"refl:, 1.1328847337958123, 0.47804878048780486, 32.790863531764046, 0.2070277254966668\n",
"refl:, 1.1328847337958123, 0.47228915662650606, 32.347246434236666, 0.20759964094140226\n",
"refl:, 1.1328847337958123, 0.4666666666666667, 31.91628017368787, 0.20807496149136276\n",
"refl:, 1.1328847337958123, 0.4611764705882353, 31.497393987322308, 0.20845469225613245\n",
"refl:, 1.1328847337958123, 0.4558139534883721, 31.090053201105746, 0.20874562394291427\n",
"refl:, 1.1328847337958123, 0.4505747126436782, 30.693756253024553, 0.20895386380475825\n",
"refl:, 1.1328847337958123, 0.4454545454545454, 30.308032020994055, 0.20908023176898172\n",
"refl:, 1.1328847337958123, 0.44044943820224725, 29.9324374181665, 0.209125738596599\n",
"refl:, 1.1328847337958123, 0.43555555555555553, 29.5665552236732, 0.20909456295065154\n",
"refl:, 1.1328847337958123, 0.4307692307692308, 29.209992121269647, 0.20899049887482632\n",
"refl:, 1.1328847337958123, 0.4260869565217391, 28.86237692208816, 0.2088190433084917\n",
"refl:, 1.1328847337958123, 0.421505376344086, 28.523358950864424, 0.2085833129971406\n",
"refl:, 1.1328847337958123, 0.41702127659574467, 28.192606577687982, 0.2082742041204916\n",
"refl:, 1.1328847337958123, 0.4126315789473684, 27.86980587961545, 0.2078930131964556\n",
"refl:, 1.1328847337958123, 0.4083333333333333, 27.554659418441407, 0.20745662776433935\n",
"refl:, 1.1328847337958123, 0.4041237113402062, 27.246885122601544, 0.20697561960434535\n",
"refl:, 1.1328847337958123, 0.4, 26.946215262627685, 0.20643519600186538\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000110865 s\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00959396 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.14944315649486126 / 0.14944315649486126 = 1.0\n",
"field decay(t = 100.01): 4.987937476864823e-12 / 0.14944315649486126 = 3.3376820952228335e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000108957 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.0218339 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.14944315644072245 / 0.14944315644072245 = 1.0\n",
"field decay(t = 100.01): 3.807851695141726e-11 / 0.14944315644072245 = 2.548026812222836e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 1.1746157759823854, 0.8, 70.0, 0.008715934286147569\n",
"refl:, 1.1746157759823854, 0.784, 67.05783140972835, 0.024210799209089452\n",
"refl:, 1.1746157759823854, 0.7686274509803922, 64.53417775149677, 0.04029873111181387\n",
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"refl:, 1.1746157759823854, 0.5226666666666667, 37.87439561623927, 0.19292625454975332\n",
"refl:, 1.1746157759823854, 0.5157894736842105, 37.29035275442276, 0.19460884663783543\n",
"refl:, 1.1746157759823854, 0.509090909090909, 36.72580652885898, 0.1961345571897698\n",
"refl:, 1.1746157759823854, 0.5025641025641026, 36.179700019842116, 0.1975122933988443\n",
"refl:, 1.1746157759823854, 0.4962025316455696, 35.651058294458764, 0.19875051751344916\n",
"refl:, 1.1746157759823854, 0.49, 35.138980002927255, 0.19985541870413245\n",
"refl:, 1.1746157759823854, 0.4839506172839506, 34.64263004924646, 0.20083789883449643\n",
"refl:, 1.1746157759823854, 0.47804878048780486, 34.161233172132036, 0.2017049645889793\n",
"refl:, 1.1746157759823854, 0.47228915662650606, 33.69406830116886, 0.20245751259203246\n",
"refl:, 1.1746157759823854, 0.4666666666666667, 33.24046357629389, 0.20310354230391978\n",
"refl:, 1.1746157759823854, 0.4611764705882353, 32.79979193741594, 0.2036476720462249\n",
"refl:, 1.1746157759823854, 0.4558139534883721, 32.37146720614281, 0.20409307625590972\n",
"refl:, 1.1746157759823854, 0.4505747126436782, 31.954940593960732, 0.20445096223605416\n",
"refl:, 1.1746157759823854, 0.4454545454545454, 31.549697581364857, 0.20471845410715214\n",
"refl:, 1.1746157759823854, 0.44044943820224725, 31.155255120816925, 0.20489444063169535\n",
"refl:, 1.1746157759823854, 0.43555555555555553, 30.771159123350074, 0.2049889592193817\n",
"refl:, 1.1746157759823854, 0.4307692307692308, 30.396982194426784, 0.20500542736591415\n",
"refl:, 1.1746157759823854, 0.4260869565217391, 30.032321589495837, 0.20495768982428397\n",
"refl:, 1.1746157759823854, 0.421505376344086, 29.67679736376329, 0.20483056853588974\n",
"refl:, 1.1746157759823854, 0.41702127659574467, 29.33005069412437, 0.20461216911883964\n",
"refl:, 1.1746157759823854, 0.4126315789473684, 28.991742354111988, 0.2043374679527374\n",
"refl:, 1.1746157759823854, 0.4083333333333333, 28.66155132518973, 0.20400220026620766\n",
"refl:, 1.1746157759823854, 0.4041237113402062, 28.339173529827534, 0.2036399273981529\n",
"refl:, 1.1746157759823854, 0.4, 28.024320673604695, 0.20318419566870832\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000108957 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00775695 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.14355855111904026 / 0.14355855111904026 = 1.0\n",
"field decay(t = 100.01): 9.667874474337293e-12 / 0.14355855111904026 = 6.734446954901761e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000108957 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.017272 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.1435585513271557 / 0.1435585513271557 = 1.0\n",
"field decay(t = 100.01): 5.780725980413138e-11 / 0.1435585513271557 = 4.0267374719040156e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 1.2074072828613354, 0.8, 75.0, 0.002279010064127535\n",
"refl:, 1.2074072828613354, 0.784, 71.19254305121969, 0.004052585814133056\n",
"refl:, 1.2074072828613354, 0.7686274509803922, 68.13230108184366, 0.017669454881364767\n",
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"refl:, 1.2074072828613354, 0.7127272727272727, 59.378629248099124, 0.07576309243511313\n",
"refl:, 1.2074072828613354, 0.7, 57.691773022139905, 0.08758135787027703\n",
"refl:, 1.2074072828613354, 0.6877192982456141, 56.13545775731428, 0.098248929360899\n",
"refl:, 1.2074072828613354, 0.6758620689655173, 54.69040263962552, 0.10794664183105998\n",
"refl:, 1.2074072828613354, 0.664406779661017, 53.3416232015308, 0.11670121483117171\n",
"refl:, 1.2074072828613354, 0.6533333333333333, 52.0771858356392, 0.12465585169755833\n",
"refl:, 1.2074072828613354, 0.6426229508196721, 50.88739414232009, 0.13187389976516842\n",
"refl:, 1.2074072828613354, 0.632258064516129, 49.76423655717566, 0.13846172295217293\n",
"refl:, 1.2074072828613354, 0.6222222222222222, 48.70099913863975, 0.14446173011718028\n",
"refl:, 1.2074072828613354, 0.6124999999999999, 47.69198665804526, 0.14995965765204525\n",
"refl:, 1.2074072828613354, 0.6030769230769231, 46.73231696062462, 0.1549825384470223\n",
"refl:, 1.2074072828613354, 0.593939393939394, 45.817766249324485, 0.15958402411708034\n",
"refl:, 1.2074072828613354, 0.5850746268656717, 44.94465059915575, 0.16380217089082738\n",
"refl:, 1.2074072828613354, 0.5764705882352942, 44.109733785683, 0.1676654538139623\n",
"refl:, 1.2074072828613354, 0.5681159420289855, 43.31015457776125, 0.17121662693717593\n",
"refl:, 1.2074072828613354, 0.56, 42.543368664412704, 0.1744741445938872\n",
"refl:, 1.2074072828613354, 0.552112676056338, 41.80710174663229, 0.17746630440999525\n",
"refl:, 1.2074072828613354, 0.5444444444444444, 41.099311260706344, 0.1802095438402015\n",
"refl:, 1.2074072828613354, 0.536986301369863, 40.418154855029364, 0.18272173169827843\n",
"refl:, 1.2074072828613354, 0.5297297297297298, 39.76196420912173, 0.18502119081455226\n",
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"refl:, 1.2074072828613354, 0.5025641025641026, 37.35844816099257, 0.192373003931677\n",
"refl:, 1.2074072828613354, 0.4962025316455696, 36.806794523773725, 0.19380521484150348\n",
"refl:, 1.2074072828613354, 0.49, 36.272732803336254, 0.19509368153538312\n",
"refl:, 1.2074072828613354, 0.4839506172839506, 35.755353950220794, 0.19624859910356954\n",
"refl:, 1.2074072828613354, 0.47804878048780486, 35.253816041990945, 0.19727952544337504\n",
"refl:, 1.2074072828613354, 0.47228915662650606, 34.76733773550362, 0.19818701041137332\n",
"refl:, 1.2074072828613354, 0.4666666666666667, 34.295192516152845, 0.19897646054575882\n",
"refl:, 1.2074072828613354, 0.4611764705882353, 33.83670362811667, 0.19965889435875267\n",
"refl:, 1.2074072828613354, 0.4558139534883721, 33.391239589169516, 0.20023796589376308\n",
"refl:, 1.2074072828613354, 0.4505747126436782, 32.95821020943854, 0.20072106469864034\n",
"refl:, 1.2074072828613354, 0.4454545454545454, 32.537063046367535, 0.2011073384968122\n",
"refl:, 1.2074072828613354, 0.44044943820224725, 32.12728023870626, 0.2013932866552523\n",
"refl:, 1.2074072828613354, 0.43555555555555553, 31.728375671037586, 0.20159478768644698\n",
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"refl:, 1.2074072828613354, 0.4260869565217391, 30.96140049976025, 0.20176796051792995\n",
"refl:, 1.2074072828613354, 0.421505376344086, 30.592494717856905, 0.20173546160628877\n",
"refl:, 1.2074072828613354, 0.41702127659574467, 30.23279287960783, 0.2015919333831556\n",
"refl:, 1.2074072828613354, 0.4126315789473684, 29.88193405422147, 0.20140043913698885\n",
"refl:, 1.2074072828613354, 0.4083333333333333, 29.539577041619506, 0.20116952947891878\n",
"refl:, 1.2074072828613354, 0.4041237113402062, 29.2053989700849, 0.2008832766544487\n",
"refl:, 1.2074072828613354, 0.4, 28.879094017427605, 0.200502480384686\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000110865 s\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
"time for set_epsilon = 0.00754905 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.1392134275610875 / 0.1392134275610875 = 1.0\n",
"field decay(t = 100.01): 1.3144200424788948e-11 / 0.1392134275610875 = 9.441761944278838e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000108957 s\n",
"Working in 3D dimensions.\n",
"Computational cell is 0.02 x 0.02 x 12 with resolution 50\n",
" block, center = (0,0,3)\n",
" size (1e+20,1e+20,6)\n",
" axes (1,0,0), (0,1,0), (0,0,1)\n",
" dielectric constant epsilon diagonal = (12.25,12.25,12.25)\n",
"time for set_epsilon = 0.019413 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.13921342793500532 / 0.13921342793500532 = 1.0\n",
"field decay(t = 100.01): 9.871965144118156e-11 / 0.13921342793500532 = 7.091244925544889e-10\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 1.23100969126526, 0.8, 79.99999999999994, 0.028667884842985224\n",
"refl:, 1.23100969126526, 0.784, 74.82079670263325, 0.0021347453734021486\n",
"refl:, 1.23100969126526, 0.7686274509803922, 71.11813585396203, 0.0041164349187047915\n",
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"refl:, 1.23100969126526, 0.41702127659574467, 30.887713235292672, 0.1993498431053417\n",
"refl:, 1.23100969126526, 0.4126315789473684, 30.527607477190394, 0.19917542826890433\n",
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"refl:, 1.23100969126526, 0.4041237113402062, 29.83343126780691, 0.19890224385206828\n",
"refl:, 1.23100969126526, 0.4, 29.498704231103652, 0.1984945592268268\n"
]
}
],
"source": [
"theta_in = np.arange(0, 85, 5)\n",
"wvl = np.empty(nfreq)\n",
"kxs = np.empty((nfreq, theta_in.size))\n",
"thetas = np.empty((nfreq, theta_in.size))\n",
"Rmeep = np.empty((nfreq, theta_in.size))\n",
"\n",
"for j in range(theta_in.size):\n",
" kxs[:, j], wvl, thetas[:, j], Rmeep[:, j] = planar_reflectance(theta_in[j])\n",
"\n",
"# create a 2d matrix for the wavelength by repeating the column vector for each angle\n",
"wvls = np.transpose(np.matlib.repmat(wvl, theta_in.size, 1))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Two-dimensional plots of the angular reflectance spectrum based on the simulated data and the analytic [Fresnel equations](https://en.wikipedia.org/wiki/Fresnel_equations) are generated using the script below. The plots are shown in the accompanying figure with four insets. The top left inset shows the simulated and analytic reflectance spectra at a wavelength of 0.6 μm. The top right inset shows the simulated reflectance spectrum as a function of the source wavelength λ and Bloch-periodic wavevector $k_x$: $R(\\lambda, k_x)$. The lower left inset is a transformation of $R(\\lambda, k_x)$ into $R(\\lambda, \\theta)$. Note how the range of angles depends on the wavelength. For a particular angle, the reflectance is a constant for all wavelengths due to the dispersionless dielectric. The lower right inset is the analytic reflectance spectrum computed using the Fresnel equations. There is agreement between the simulated and analytic results. The [Brewster's angle](https://en.wikipedia.org/wiki/Brewster%27s_angle), where the transmittance is 1 and the reflectance is 0, is tan-1(3.5/1)=74.1°. This is also verified by the simulated results.\n",
"\n",
"In order to generate results for the missing portion of the reflectance spectrum (i.e., the white region), we will need to rerun the simulations for different wavelength spectra.\n",
"\n",
"![](https://meep.readthedocs.io/en/latest/images/reflectance_angular_spectrum.png)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/gcrouch/anaconda3/envs/mp/lib/python3.11/site-packages/numpy/core/getlimits.py:500: UserWarning: The value of the smallest subnormal for type is zero.\n",
" setattr(self, word, getattr(machar, word).flat[0])\n",
"/home/gcrouch/anaconda3/envs/mp/lib/python3.11/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero.\n",
" return self._float_to_str(self.smallest_subnormal)\n"
]
},
{
"data": {
"image/png": 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",
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