{
"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",
"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 = [mp.Source(mp.GaussianSource(fcen,fwidth=df), component=mp.Ex, center=mp.Vector3(z=-0.5*sz+dpml))]\n",
"\n",
" sim = mp.Simulation(cell_size=cell_size,\n",
" boundary_layers=pml_layers,\n",
" sources=sources,\n",
" k_point=k,\n",
" dimensions=dimensions,\n",
" resolution=resolution)\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(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ex, mp.Vector3(z=-0.5*sz+dpml), 1e-9))\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 = [mp.Block(mp.Vector3(mp.inf,mp.inf,0.5*sz), center=mp.Vector3(z=0.25*sz), material=mp.Medium(index=3.5))]\n",
"\n",
" sim = mp.Simulation(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",
" refl = sim.add_flux(fcen, df, nfreq, refl_fr)\n",
" sim.load_minus_flux_data(refl, empty_data)\n",
"\n",
" sim.run(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ex, mp.Vector3(z=-0.5*sz+dpml), 1e-9))\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 = 0.000254154 s\n",
"Working in 1D dimensions.\n",
"Computational cell is 0 x 0 x 12 with resolution 50\n",
"time for set_epsilon = 0.000342131 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): 6.806395978139867e-16 / 0.25332329653323415 = 2.6868417043700194e-15\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 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 = 0.000371933 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, 0.29476330384323207\n",
"refl:, 0.0, 0.784, 0.0, 0.29416578611798405\n",
"refl:, 0.0, 0.7686274509803922, 0.0, 0.2935560666132851\n",
"refl:, 0.0, 0.7538461538461539, 0.0, 0.29293290546540196\n",
"refl:, 0.0, 0.739622641509434, 0.0, 0.2922951429790378\n",
"refl:, 0.0, 0.7259259259259259, 0.0, 0.29164324229177097\n",
"refl:, 0.0, 0.7127272727272727, 0.0, 0.29097731021514417\n",
"refl:, 0.0, 0.7, 0.0, 0.29029575759541565\n",
"refl:, 0.0, 0.6877192982456141, 0.0, 0.2895975033066778\n",
"refl:, 0.0, 0.6758620689655173, 0.0, 0.2888834125810835\n",
"refl:, 0.0, 0.664406779661017, 0.0, 0.2881539488987047\n",
"refl:, 0.0, 0.6533333333333333, 0.0, 0.2874077841401458\n",
"refl:, 0.0, 0.6426229508196721, 0.0, 0.2866443691325259\n",
"refl:, 0.0, 0.632258064516129, 0.0, 0.2858651486082286\n",
"refl:, 0.0, 0.6222222222222222, 0.0, 0.28507064287177303\n",
"refl:, 0.0, 0.6124999999999999, 0.0, 0.2842593661161744\n",
"refl:, 0.0, 0.6030769230769231, 0.0, 0.28343094611850356\n",
"refl:, 0.0, 0.593939393939394, 0.0, 0.28258688014584116\n",
"refl:, 0.0, 0.5850746268656717, 0.0, 0.2817272035905085\n",
"refl:, 0.0, 0.5764705882352942, 0.0, 0.2808500622387931\n",
"refl:, 0.0, 0.5681159420289855, 0.0, 0.27995515394321197\n",
"refl:, 0.0, 0.56, 0.0, 0.27904384994339343\n",
"refl:, 0.0, 0.552112676056338, 0.0, 0.27811574176551984\n",
"refl:, 0.0, 0.5444444444444444, 0.0, 0.2771688207349352\n",
"refl:, 0.0, 0.536986301369863, 0.0, 0.2762029589907331\n",
"refl:, 0.0, 0.5297297297297298, 0.0, 0.2752195125027274\n",
"refl:, 0.0, 0.5226666666666667, 0.0, 0.2742178237240486\n",
"refl:, 0.0, 0.5157894736842105, 0.0, 0.27319583895650085\n",
"refl:, 0.0, 0.509090909090909, 0.0, 0.27215367552975717\n",
"refl:, 0.0, 0.5025641025641026, 0.0, 0.27109276268116617\n",
"refl:, 0.0, 0.4962025316455696, 0.0, 0.2700121717612113\n",
"refl:, 0.0, 0.49, 0.0, 0.26890977948431494\n",
"refl:, 0.0, 0.4839506172839506, 0.0, 0.26778602305927346\n",
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"refl:, 0.0, 0.4666666666666667, 0.0, 0.2642890605183494\n",
"refl:, 0.0, 0.4611764705882353, 0.0, 0.26307815170848525\n",
"refl:, 0.0, 0.4558139534883721, 0.0, 0.2618459695575972\n",
"refl:, 0.0, 0.4505747126436782, 0.0, 0.2605907641320623\n",
"refl:, 0.0, 0.4454545454545454, 0.0, 0.25931062280334477\n",
"refl:, 0.0, 0.44044943820224725, 0.0, 0.25800677969709146\n",
"refl:, 0.0, 0.43555555555555553, 0.0, 0.2566804027177118\n",
"refl:, 0.0, 0.4307692307692308, 0.0, 0.25532959438320507\n",
"refl:, 0.0, 0.4260869565217391, 0.0, 0.2539529088676918\n",
"refl:, 0.0, 0.421505376344086, 0.0, 0.2525520862693137\n",
"refl:, 0.0, 0.41702127659574467, 0.0, 0.2511282531123407\n",
"refl:, 0.0, 0.4126315789473684, 0.0, 0.24967934554669954\n",
"refl:, 0.0, 0.4083333333333333, 0.0, 0.24820404444956207\n",
"refl:, 0.0, 0.4041237113402062, 0.0, 0.24670386250022297\n",
"refl:, 0.0, 0.4, 0.0, 0.24517862401765392\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 = 0.00770998 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.25242167342001043 / 0.25242167342001043 = 1.0\n",
"field decay(t = 100.01): 1.8867425254108467e-14 / 0.25242167342001043 = 7.474566267815881e-14\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 = 0.026345 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): 2.0310851043564926e-11 / 0.2524216734361254 = 8.046397429777174e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.1089446784345727, 0.8, 5.0, 0.2934227118859898\n",
"refl:, 0.1089446784345727, 0.784, 4.899752997934953, 0.29287850682357097\n",
"refl:, 0.1089446784345727, 0.7686274509803922, 4.803451415694315, 0.2923194417293526\n",
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"refl:, 0.1089446784345727, 0.47228915662650606, 2.9493644663270095, 0.2650190380989821\n",
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"refl:, 0.1089446784345727, 0.41702127659574467, 2.603972444256211, 0.25077428012312447\n",
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"refl:, 0.1089446784345727, 0.4041237113402062, 2.5233842703240543, 0.24637235281997996\n",
"refl:, 0.1089446784345727, 0.4, 2.4976190449198983, 0.2448541987123429\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.00011611 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 = 0.00750589 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.24974540035413878 / 0.24974540035413878 = 1.0\n",
"field decay(t = 100.01): 6.006906595531682e-14 / 0.24974540035413878 = 2.40521210281106e-13\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 = 0.0191441 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.24974540044608928 / 0.24974540044608928 = 1.0\n",
"field decay(t = 100.01): 2.1519308385946042e-11 / 0.24974540044608928 = 8.61649838095467e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.2170602220836629, 0.8, 10.0, 0.2893781746253207\n",
"refl:, 0.2170602220836629, 0.784, 9.798006528153513, 0.288998732433702\n",
"refl:, 0.2170602220836629, 0.7686274509803922, 9.604050171837292, 0.2885938951899122\n",
"refl:, 0.2170602220836629, 0.7538461538461539, 9.417658416993296, 0.28816419107846264\n",
"refl:, 0.2170602220836629, 0.739622641509434, 9.238395240840497, 0.28770900366948954\n",
"refl:, 0.2170602220836629, 0.7259259259259259, 9.06585764090149, 0.28722834374816003\n",
"refl:, 0.2170602220836629, 0.7127272727272727, 8.899672554443574, 0.2867235913729682\n",
"refl:, 0.2170602220836629, 0.7, 8.739494117841588, 0.28619525258422535\n",
"refl:, 0.2170602220836629, 0.6877192982456141, 8.585001222725978, 0.28564218452120266\n",
"refl:, 0.2170602220836629, 0.6758620689655173, 8.435895331947279, 0.2850647891546287\n",
"refl:, 0.2170602220836629, 0.664406779661017, 8.291898523577625, 0.2844650049217599\n",
"refl:, 0.2170602220836629, 0.6533333333333333, 8.152751735551202, 0.2838430637467787\n",
"refl:, 0.2170602220836629, 0.6426229508196721, 8.018213187256704, 0.28319797552226944\n",
"refl:, 0.2170602220836629, 0.632258064516129, 7.88805695754783, 0.2825306580041294\n",
"refl:, 0.2170602220836629, 0.6222222222222222, 7.762071701325296, 0.2818429693994039\n",
"refl:, 0.2170602220836629, 0.6124999999999999, 7.640059489140416, 0.2811345740291295\n",
"refl:, 0.2170602220836629, 0.6030769230769231, 7.521834756238996, 0.28040433725297315\n",
"refl:, 0.2170602220836629, 0.593939393939394, 7.407223349155971, 0.27965322172446067\n",
"refl:, 0.2170602220836629, 0.5850746268656717, 7.296061659428915, 0.2788825653708164\n",
"refl:, 0.2170602220836629, 0.5764705882352942, 7.188195835257705, 0.27809144849085615\n",
"refl:, 0.2170602220836629, 0.5681159420289855, 7.083481063027822, 0.2772785981174172\n",
"refl:, 0.2170602220836629, 0.56, 6.981780911561047, 0.2764449243213644\n",
"refl:, 0.2170602220836629, 0.552112676056338, 6.882966732780441, 0.2755914805667849\n",
"refl:, 0.2170602220836629, 0.5444444444444444, 6.786917113194022, 0.27471697321444166\n",
"refl:, 0.2170602220836629, 0.536986301369863, 6.693517371228444, 0.27382008373306266\n",
"refl:, 0.2170602220836629, 0.5297297297297298, 6.602659095992853, 0.2729019522035499\n",
"refl:, 0.2170602220836629, 0.5226666666666667, 6.514239723534344, 0.27196350015165877\n",
"refl:, 0.2170602220836629, 0.5157894736842105, 6.428162147069652, 0.27100303851505764\n",
"refl:, 0.2170602220836629, 0.509090909090909, 6.3443343580501015, 0.27001939086671356\n",
"refl:, 0.2170602220836629, 0.5025641025641026, 6.262669115245526, 0.26901406912439724\n",
"refl:, 0.2170602220836629, 0.4962025316455696, 6.1830836393232005, 0.2679876733928022\n",
"refl:, 0.2170602220836629, 0.49, 6.105499330654852, 0.2669381026643071\n",
"refl:, 0.2170602220836629, 0.4839506172839506, 6.029841508312739, 0.265864537999668\n",
"refl:, 0.2170602220836629, 0.47804878048780486, 5.956039168418179, 0.26476870360049726\n",
"refl:, 0.2170602220836629, 0.47228915662650606, 5.884024760185935, 0.26365066570667506\n",
"refl:, 0.2170602220836629, 0.4666666666666667, 5.813733978168244, 0.26250810411848724\n",
"refl:, 0.2170602220836629, 0.4611764705882353, 5.745105569345401, 0.26134058873292715\n",
"refl:, 0.2170602220836629, 0.4558139534883721, 5.678081153837623, 0.26014984735445634\n",
"refl:, 0.2170602220836629, 0.4505747126436782, 5.612605058127373, 0.25893548643505515\n",
"refl:, 0.2170602220836629, 0.4454545454545454, 5.5486241597837695, 0.2576951510120501\n",
"refl:, 0.2170602220836629, 0.44044943820224725, 5.486087742772728, 0.2564288095400968\n",
"refl:, 0.2170602220836629, 0.43555555555555553, 5.424947362519055, 0.2551382775804875\n",
"refl:, 0.2170602220836629, 0.4307692307692308, 5.365156719961124, 0.25382296989852066\n",
"refl:, 0.2170602220836629, 0.4260869565217391, 5.306671543905553, 0.25248068938520546\n",
"refl:, 0.2170602220836629, 0.421505376344086, 5.249449481049872, 0.2511120329000034\n",
"refl:, 0.2170602220836629, 0.41702127659574467, 5.19344999309547, 0.2497191778959394\n",
"refl:, 0.2170602220836629, 0.4126315789473684, 5.138634260422533, 0.2483012320567707\n",
"refl:, 0.2170602220836629, 0.4083333333333333, 5.08496509184317, 0.2468560224651321\n",
"refl:, 0.2170602220836629, 0.4041237113402062, 5.032406839989342, 0.24538435149961998\n",
"refl:, 0.2170602220836629, 0.4, 4.980925321928872, 0.2438873823711191\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 = 0.00942492 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.24537918139687384 / 0.24537918139687384 = 1.0\n",
"field decay(t = 100.01): 1.2755953357084837e-13 / 0.24537918139687384 = 5.198466016745522e-13\n",
"run 0 finished at t = 100.01 (10001 timesteps)\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",
" 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 = 0.015625 s\n",
"-----------\n",
"Meep: using complex fields.\n",
"field decay(t = 50.01): 0.24537918161848085 / 0.24537918161848085 = 1.0\n",
"field decay(t = 100.01): 2.2796495621609012e-11 / 0.24537918161848085 = 9.290313657111033e-11\n",
"run 0 finished at t = 100.01 (10001 timesteps)\n",
"refl:, 0.3235238063781509, 0.8, 14.999999999999998, 0.28256373042287475\n",
"refl:, 0.3235238063781509, 0.784, 14.693171512000124, 0.28247093802487827\n",
"refl:, 0.3235238063781509, 0.7686274509803922, 14.398780921441814, 0.28233355058613946\n",
"refl:, 0.3235238063781509, 0.7538461538461539, 14.116078899389818, 0.2821545309608155\n",
"refl:, 0.3235238063781509, 0.739622641509434, 13.844375746673084, 0.2819358770069733\n",
"refl:, 0.3235238063781509, 0.7259259259259259, 13.583035518835887, 0.2816776835689441\n",
"refl:, 0.3235238063781509, 0.7127272727272727, 13.331470838933798, 0.28138133257604653\n",
"refl:, 0.3235238063781509, 0.7, 13.089138305160036, 0.281049646363028\n",
"refl:, 0.3235238063781509, 0.6877192982456141, 12.855534414514684, 0.28068351331308133\n",
"refl:, 0.3235238063781509, 0.6758620689655173, 12.630191935533823, 0.28028281405469785\n",
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"refl:, 0.3235238063781509, 0.6533333333333333, 12.202584575236058, 0.27938611173524625\n",
"refl:, 0.3235238063781509, 0.6426229508196721, 11.999539143408532, 0.2788927304404999\n",
"refl:, 0.3235238063781509, 0.632258064516129, 11.803189104258525, 0.27836932361278227\n",
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"refl:, 0.3235238063781509, 0.552112676056338, 10.289481874787974, 0.2724582796019277\n",
"refl:, 0.3235238063781509, 0.5444444444444444, 10.145048899510067, 0.27167450266463894\n",
"refl:, 0.3235238063781509, 0.536986301369863, 10.004635469795673, 0.2708649570485523\n",
"refl:, 0.3235238063781509, 0.5297297297297298, 9.868075245978739, 0.27002944005333146\n",
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"refl:, 0.3235238063781509, 0.5157894736842105, 9.60589393375409, 0.26828628327229254\n",
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"refl:, 0.3235238063781509, 0.5025641025641026, 9.3573454604044, 0.266441343276572\n",
"refl:, 0.3235238063781509, 0.4962025316455696, 9.237854049896542, 0.2654822435375998\n",
"refl:, 0.3235238063781509, 0.49, 9.121388939570695, 0.26449858196569564\n",
"refl:, 0.3235238063781509, 0.4839506172839506, 9.00783611704105, 0.2634884799544352\n",
"refl:, 0.3235238063781509, 0.47804878048780486, 8.897087249467761, 0.26245270185974406\n",
"refl:, 0.3235238063781509, 0.47228915662650606, 8.789039332825531, 0.26139274110511584\n",
"refl:, 0.3235238063781509, 0.4666666666666667, 8.683594366947904, 0.26030735036150837\n",
"refl:, 0.3235238063781509, 0.4611764705882353, 8.5806590541555, 0.2591947457863499\n",
"refl:, 0.3235238063781509, 0.4558139534883721, 8.480144519487721, 0.25805589551088276\n",
"refl:, 0.3235238063781509, 0.4505747126436782, 8.381966050745921, 0.256892047194308\n",
"refl:, 0.3235238063781509, 0.4454545454545454, 8.286042856724524, 0.2557015480946698\n",
"refl:, 0.3235238063781509, 0.44044943820224725, 8.192297842157469, 0.2544827165503608\n",
"refl:, 0.3235238063781509, 0.43555555555555553, 8.100657398042404, 0.25323697315876975\n",
"refl:, 0.3235238063781509, 0.4307692307692308, 8.011051206126568, 0.25196549708688976\n",
"refl:, 0.3235238063781509, 0.4260869565217391, 7.923412056447124, 0.2506663282693837\n",
"refl:, 0.3235238063781509, 0.421505376344086, 7.837675676917115, 0.2493383700330171\n",
"refl:, 0.3235238063781509, 0.41702127659574467, 7.753780574036344, 0.24798388324916928\n",
"refl:, 0.3235238063781509, 0.4126315789473684, 7.671667883886533, 0.24660386238549814\n",
"refl:, 0.3235238063781509, 0.4083333333333333, 7.591281232641979, 0.2451961050843521\n",
"refl:, 0.3235238063781509, 0.4041237113402062, 7.512566605892175, 0.2437600099079589\n",
"refl:, 0.3235238063781509, 0.4, 7.435472226131853, 0.24229747168145319\n",
"-----------\n",
"Initializing structure...\n",
"time for choose_chunkdivision = 0.000112772 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 = 0.007622 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",
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"refl:, 0.4275251791570859, 0.4307692307692308, 10.61243605852877, 0.249413825082604\n",
"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",
"refl:, 0.5282728271758743, 0.7259259259259259, 22.54983979533518, 0.2636926798419164\n",
"refl:, 0.5282728271758743, 0.7127272727272727, 22.117946146436154, 0.2641189902441729\n",
"refl:, 0.5282728271758743, 0.7, 21.70272699899909, 0.2644658127354963\n",
"refl:, 0.5282728271758743, 0.6877192982456141, 21.303209386217617, 0.26473707694833154\n",
"refl:, 0.5282728271758743, 0.6758620689655173, 20.91849655102253, 0.26493869102120726\n",
"refl:, 0.5282728271758743, 0.664406779661017, 20.54776044367494, 0.26507564513451415\n",
"refl:, 0.5282728271758743, 0.6533333333333333, 20.19023510896709, 0.2651500052068409\n",
"refl:, 0.5282728271758743, 0.6426229508196721, 19.84521083974841, 0.26516501686911953\n",
"refl:, 0.5282728271758743, 0.632258064516129, 19.51202899301187, 0.26512536746580095\n",
"refl:, 0.5282728271758743, 0.6222222222222222, 19.190077380825585, 0.26503310672375896\n",
"refl:, 0.5282728271758743, 0.6124999999999999, 18.878786161658894, 0.26488908132632305\n",
"refl:, 0.5282728271758743, 0.6030769230769231, 18.577624168665142, 0.26469630209606193\n",
"refl:, 0.5282728271758743, 0.593939393939394, 18.28609562066815, 0.26445767784614754\n",
"refl:, 0.5282728271758743, 0.5850746268656717, 18.003737169291743, 0.26417370471931184\n",
"refl:, 0.5282728271758743, 0.5764705882352942, 17.730115242139682, 0.26384505077481407\n",
"refl:, 0.5282728271758743, 0.5681159420289855, 17.46482364739322, 0.26347427561024556\n",
"refl:, 0.5282728271758743, 0.56, 17.207481409818527, 0.26306325708398504\n",
"refl:, 0.5282728271758743, 0.552112676056338, 16.957730812108316, 0.262611771262809\n",
"refl:, 0.5282728271758743, 0.5444444444444444, 16.715235618835717, 0.2621203557572436\n",
"refl:, 0.5282728271758743, 0.536986301369863, 16.479679463167955, 0.2615915488530281\n",
"refl:, 0.5282728271758743, 0.5297297297297298, 16.250764378950514, 0.26102646172552363\n",
"refl:, 0.5282728271758743, 0.5226666666666667, 16.028209462892256, 0.26042407309811766\n",
"refl:, 0.5282728271758743, 0.5157894736842105, 15.811749653412038, 0.25978529806673434\n",
"refl:, 0.5282728271758743, 0.509090909090909, 15.60113461429131, 0.2591127130188696\n",
"refl:, 0.5282728271758743, 0.5025641025641026, 15.396127712651408, 0.25840617419006323\n",
"refl:, 0.5282728271758743, 0.4962025316455696, 15.196505081970068, 0.2576643632602327\n",
"refl:, 0.5282728271758743, 0.49, 15.002054761894165, 0.2568889467859571\n",
"refl:, 0.5282728271758743, 0.4839506172839506, 14.81257590751694, 0.2560818324629057\n",
"refl:, 0.5282728271758743, 0.47804878048780486, 14.627878061586326, 0.2552417285733339\n",
"refl:, 0.5282728271758743, 0.47228915662650606, 14.44778048381156, 0.25436772779199046\n",
"refl:, 0.5282728271758743, 0.4666666666666667, 14.272111532051735, 0.2534618054882236\n",
"refl:, 0.5282728271758743, 0.4611764705882353, 14.100708090713411, 0.2525248442883521\n",
"refl:, 0.5282728271758743, 0.4558139534883721, 13.933415042164041, 0.25155500702726324\n",
"refl:, 0.5282728271758743, 0.4505747126436782, 13.770084777392734, 0.25055182001671567\n",
"refl:, 0.5282728271758743, 0.4454545454545454, 13.610576742526133, 0.24951717022490025\n",
"refl:, 0.5282728271758743, 0.44044943820224725, 13.454757018141454, 0.24845117408859577\n",
"refl:, 0.5282728271758743, 0.43555555555555553, 13.30249792861589, 0.24735169966979012\n",
"refl:, 0.5282728271758743, 0.4307692307692308, 13.153677679016674, 0.2462187296769865\n",
"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, 0.4260869565217391, 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",
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"refl:, 0.7169705454388076, 0.47228915662650606, 19.79266184720379, 0.24443328421700983\n",
"refl:, 0.7169705454388076, 0.4666666666666667, 19.54738026749198, 0.24379556106465222\n",
"refl:, 0.7169705454388076, 0.4611764705882353, 19.308229285168313, 0.24311440973651832\n",
"refl:, 0.7169705454388076, 0.4558139534883721, 19.07497712952083, 0.2423917032614313\n",
"refl:, 0.7169705454388076, 0.4505747126436782, 18.847403806983923, 0.24162921270758458\n",
"refl:, 0.7169705454388076, 0.4454545454545454, 18.62530034751981, 0.24082577322829152\n",
"refl:, 0.7169705454388076, 0.44044943820224725, 18.408468109247096, 0.23998068018388435\n",
"refl:, 0.7169705454388076, 0.43555555555555553, 18.196718136035763, 0.23909605307915388\n",
"refl:, 0.7169705454388076, 0.4307692307692308, 17.98987056333767, 0.23817255818097147\n",
"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",
"refl:, 0.8034845121081741, 0.784, 39.04509528455022, 0.2059250719323383\n",
"refl:, 0.8034845121081741, 0.7686274509803922, 38.139646206191365, 0.20966397204966036\n",
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"refl:, 0.8034845121081741, 0.6222222222222222, 29.996422070856152, 0.2348212532271984\n",
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"refl:, 0.8034845121081741, 0.593939393939394, 28.504064681021994, 0.2374874618810027\n",
"refl:, 0.8034845121081741, 0.5850746268656717, 28.0406841528977, 0.23816414677923553\n",
"refl:, 0.8034845121081741, 0.5764705882352942, 27.592833714170844, 0.2387438174110003\n",
"refl:, 0.8034845121081741, 0.5681159420289855, 27.159708577552564, 0.239232508084756\n",
"refl:, 0.8034845121081741, 0.56, 26.740561170354134, 0.23963612123153596\n",
"refl:, 0.8034845121081741, 0.552112676056338, 26.33469592188663, 0.23995828312103898\n",
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"refl:, 0.8034845121081741, 0.536986301369863, 25.560262345758233, 0.24037244343095185\n",
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"refl:, 0.8034845121081741, 0.5025641025641026, 23.816105667237974, 0.24022489861203003\n",
"refl:, 0.8034845121081741, 0.4962025316455696, 23.496375102814216, 0.24001212440412875\n",
"refl:, 0.8034845121081741, 0.49, 23.185382948015043, 0.2397434129524054\n",
"refl:, 0.8034845121081741, 0.4839506172839506, 22.882764536632674, 0.2394219863711472\n",
"refl:, 0.8034845121081741, 0.47804878048780486, 22.58817584322306, 0.23904730465890137\n",
"refl:, 0.8034845121081741, 0.47228915662650606, 22.301291999661412, 0.23862033792003395\n",
"refl:, 0.8034845121081741, 0.4666666666666667, 22.021805941382443, 0.23814466238694304\n",
"refl:, 0.8034845121081741, 0.4611764705882353, 21.749427169932794, 0.23762099874005177\n",
"refl:, 0.8034845121081741, 0.4558139534883721, 21.483880620051718, 0.23704845905896132\n",
"refl:, 0.8034845121081741, 0.4505747126436782, 21.224905620871482, 0.2364290006894749\n",
"refl:, 0.8034845121081741, 0.4454545454545454, 20.972254942022712, 0.23576489053070165\n",
"refl:, 0.8034845121081741, 0.44044943820224725, 20.725693916468796, 0.23505540516189377\n",
"refl:, 0.8034845121081741, 0.43555555555555553, 20.48499963280006, 0.23429986728741037\n",
"refl:, 0.8034845121081741, 0.4307692307692308, 20.249960190511292, 0.23350021386178307\n",
"refl:, 0.8034845121081741, 0.4260869565217391, 20.020374012481035, 0.23265749904183425\n",
"refl:, 0.8034845121081741, 0.421505376344086, 19.79604920948226, 0.23176986721335244\n",
"refl:, 0.8034845121081741, 0.41702127659574467, 19.576802992091316, 0.23083693098169072\n",
"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",
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"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",
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"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",
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"refl:, 0.8838834764831843, 0.4611764705882353, 24.055807269832574, 0.23177609164136181\n",
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"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",
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"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",
"refl:, 0.9575555538987225, 0.5297297297297298, 30.480537056602333, 0.22363493657078803\n",
"refl:, 0.9575555538987225, 0.5226666666666667, 30.031918444163345, 0.2242400133418431\n",
"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",
"refl:, 1.0239400553612397, 0.7538461538461539, 50.524208813748004, 0.1393743175816963\n",
"refl:, 1.0239400553612397, 0.739622641509434, 49.22931269112476, 0.14718461760941978\n",
"refl:, 1.0239400553612397, 0.7259259259259259, 48.013685667151286, 0.15425442212255983\n",
"refl:, 1.0239400553612397, 0.7127272727272727, 46.86879216202182, 0.16064116852684127\n",
"refl:, 1.0239400553612397, 0.7, 45.787462696319906, 0.1664466525245801\n",
"refl:, 1.0239400553612397, 0.6877192982456141, 44.7636047370949, 0.17171830451504444\n",
"refl:, 1.0239400553612397, 0.6758620689655173, 43.79198840588911, 0.17651889499651638\n",
"refl:, 1.0239400553612397, 0.664406779661017, 42.868084512177944, 0.1808955749197593\n",
"refl:, 1.0239400553612397, 0.6533333333333333, 41.98794000564178, 0.18488590864155194\n",
"refl:, 1.0239400553612397, 0.6426229508196721, 41.148080731197126, 0.1885334768453189\n",
"refl:, 1.0239400553612397, 0.632258064516129, 40.345434464399176, 0.19186399028554912\n",
"refl:, 1.0239400553612397, 0.6222222222222222, 39.57726925315509, 0.1949105801621511\n",
"refl:, 1.0239400553612397, 0.6124999999999999, 38.841143478370526, 0.19769436000574783\n",
"refl:, 1.0239400553612397, 0.6030769230769231, 38.13486500383326, 0.20023789123980396\n",
"refl:, 1.0239400553612397, 0.593939393939394, 37.45645745905701, 0.2025624060128163\n",
"refl:, 1.0239400553612397, 0.5850746268656717, 36.80413218014341, 0.204680856177325\n",
"refl:, 1.0239400553612397, 0.5764705882352942, 36.176264682924305, 0.2066128346051995\n",
"refl:, 1.0239400553612397, 0.5681159420289855, 35.57137479946729, 0.20837010840175924\n",
"refl:, 1.0239400553612397, 0.56, 34.98810980028866, 0.2099625172331732\n",
"refl:, 1.0239400553612397, 0.552112676056338, 34.42522996870841, 0.21140487263605512\n",
"refl:, 1.0239400553612397, 0.5444444444444444, 33.881596203503065, 0.2127045522560479\n",
"refl:, 1.0239400553612397, 0.536986301369863, 33.35615931039313, 0.21386953098052403\n",
"refl:, 1.0239400553612397, 0.5297297297297298, 32.847950708397136, 0.21491013773280657\n",
"refl:, 1.0239400553612397, 0.5226666666666667, 32.3560743283589, 0.21583212552616557\n",
"refl:, 1.0239400553612397, 0.5157894736842105, 31.87969952142079, 0.2166414381263308\n",
"refl:, 1.0239400553612397, 0.509090909090909, 31.41805482739263, 0.21734485598596862\n",
"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",
"refl:, 1.1746157759823854, 0.7538461538461539, 62.31059707934406, 0.0555678814867085\n",
"refl:, 1.1746157759823854, 0.739622641509434, 60.31629899672389, 0.06970125775811391\n",
"refl:, 1.1746157759823854, 0.7259259259259259, 58.50481213939229, 0.08255524971343331\n",
"refl:, 1.1746157759823854, 0.7127272727272727, 56.843594941553754, 0.09413263635827869\n",
"refl:, 1.1746157759823854, 0.7, 55.30875739675561, 0.10463698983404623\n",
"refl:, 1.1746157759823854, 0.6877192982456141, 53.88211612099151, 0.11407493400247079\n",
"refl:, 1.1746157759823854, 0.6758620689655173, 52.54943143507829, 0.1226472707657511\n",
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"refl:, 1.1746157759823854, 0.6533333333333333, 50.122379445158494, 0.13744242808130103\n",
"refl:, 1.1746157759823854, 0.6426229508196721, 49.010959419193355, 0.1438468426182844\n",
"refl:, 1.1746157759823854, 0.632258064516129, 47.958527855818005, 0.14968921112177416\n",
"refl:, 1.1746157759823854, 0.6222222222222222, 46.9595500055931, 0.1550186900782557\n",
"refl:, 1.1746157759823854, 0.6124999999999999, 46.00926848902442, 0.15990623687364083\n",
"refl:, 1.1746157759823854, 0.6030769230769231, 45.103557823882895, 0.1643748532843572\n",
"refl:, 1.1746157759823854, 0.593939393939394, 44.23881248012816, 0.16847752780425043\n",
"refl:, 1.1746157759823854, 0.5850746268656717, 43.41185942214757, 0.1722356163059057\n",
"refl:, 1.1746157759823854, 0.5764705882352942, 42.619888854495166, 0.17567897390885354\n",
"refl:, 1.1746157759823854, 0.5681159420289855, 41.860398715356425, 0.17883996497200733\n",
"refl:, 1.1746157759823854, 0.56, 41.131149701242414, 0.18173480153232927\n",
"refl:, 1.1746157759823854, 0.552112676056338, 40.430128463310105, 0.18439121641848574\n",
"refl:, 1.1746157759823854, 0.5444444444444444, 39.75551721886283, 0.18682378756973045\n",
"refl:, 1.1746157759823854, 0.536986301369863, 39.10566845306894, 0.18904674104030247\n",
"refl:, 1.1746157759823854, 0.5297297297297298, 38.479083699202135, 0.19107686788902303\n",
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"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",
"refl:, 1.2074072828613354, 0.7538461538461539, 65.5329128763873, 0.03336169435169541\n",
"refl:, 1.2074072828613354, 0.739622641509434, 63.25596068464814, 0.048654509225169895\n",
"refl:, 1.2074072828613354, 0.7259259259259259, 61.22160180379117, 0.06275216167717797\n",
"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",
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"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",
"refl:, 1.2074072828613354, 0.5226666666666667, 39.12922312098109, 0.1871223337651491\n",
"refl:, 1.2074072828613354, 0.5157894736842105, 38.51854903626071, 0.18904214560856375\n",
"refl:, 1.2074072828613354, 0.509090909090909, 37.928677376424204, 0.190789263829168\n",
"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",
"refl:, 1.2074072828613354, 0.4307692307692308, 31.33989242755132, 0.20171671281423958\n",
"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",
"refl:, 1.23100969126526, 0.7538461538461539, 68.12392493650243, 0.017504855468406976\n",
"refl:, 1.23100969126526, 0.739622641509434, 65.57213417097068, 0.03282494395652445\n",
"refl:, 1.23100969126526, 0.7259259259259259, 63.331955818023665, 0.04792423816150501\n",
"refl:, 1.23100969126526, 0.7127272727272727, 61.32721657609733, 0.06193140028783135\n",
"refl:, 1.23100969126526, 0.7, 59.508764013939604, 0.07458578833476998\n",
"refl:, 1.23100969126526, 0.6877192982456141, 57.84259890532987, 0.08617897772571746\n",
"refl:, 1.23100969126526, 0.6758620689655173, 56.30398980710504, 0.0966374263474978\n",
"refl:, 1.23100969126526, 0.664406779661017, 54.87424701948212, 0.10612404031633497\n",
"refl:, 1.23100969126526, 0.6533333333333333, 53.53881754577338, 0.1147736073308378\n",
"refl:, 1.23100969126526, 0.6426229508196721, 52.2860932123638, 0.12261878935484406\n",
"refl:, 1.23100969126526, 0.632258064516129, 51.10662968356778, 0.1297955968814688\n",
"refl:, 1.23100969126526, 0.6222222222222222, 49.992614952243095, 0.1363423963503902\n",
"refl:, 1.23100969126526, 0.6124999999999999, 48.937495982303304, 0.14232561295216176\n",
"refl:, 1.23100969126526, 0.6030769230769231, 47.93570930843333, 0.1477973393651342\n",
"refl:, 1.23100969126526, 0.593939393939394, 46.98248211140486, 0.1527979150330299\n",
"refl:, 1.23100969126526, 0.5850746268656717, 46.07368235996428, 0.15737616810594365\n",
"refl:, 1.23100969126526, 0.5764705882352942, 45.205703916101704, 0.16157175886307418\n",
"refl:, 1.23100969126526, 0.5681159420289855, 44.37537706820699, 0.16542702710683707\n",
"refl:, 1.23100969126526, 0.56, 43.57989789517631, 0.16896483740231436\n",
"refl:, 1.23100969126526, 0.552112676056338, 42.81677180338089, 0.17222042834178233\n",
"refl:, 1.23100969126526, 0.5444444444444444, 42.083767886770914, 0.17520079945615433\n",
"refl:, 1.23100969126526, 0.536986301369863, 41.378881661291835, 0.1779352569426369\n",
"refl:, 1.23100969126526, 0.5297297297297298, 40.70030435652892, 0.18044129732794095\n",
"refl:, 1.23100969126526, 0.5226666666666667, 40.046397397863686, 0.182734107792854\n",
"refl:, 1.23100969126526, 0.5157894736842105, 39.41567103836258, 0.18483861166276766\n",
"refl:, 1.23100969126526, 0.509090909090909, 38.806766338771496, 0.18675601688212784\n",
"refl:, 1.23100969126526, 0.5025641025641026, 38.218439871701385, 0.1884996414001091\n",
"refl:, 1.23100969126526, 0.4962025316455696, 37.64955065969264, 0.19008080645459632\n",
"refl:, 1.23100969126526, 0.49, 37.099048958377544, 0.1915079168724047\n",
"refl:, 1.23100969126526, 0.4839506172839506, 36.56596657389412, 0.19279885897563126\n",
"refl:, 1.23100969126526, 0.47804878048780486, 36.049408464086156, 0.19395530230339666\n",
"refl:, 1.23100969126526, 0.47228915662650606, 35.54854542021205, 0.19498186511670068\n",
"refl:, 1.23100969126526, 0.4666666666666667, 35.062607663064846, 0.19588322966927102\n",
"refl:, 1.23100969126526, 0.4611764705882353, 34.59087921692149, 0.19666472127374038\n",
"refl:, 1.23100969126526, 0.4558139534883721, 34.13269294834013, 0.19734835806450404\n",
"refl:, 1.23100969126526, 0.4505747126436782, 33.6874261758209, 0.197930496667696\n",
"refl:, 1.23100969126526, 0.4454545454545454, 33.25449677173539, 0.19840503576945626\n",
"refl:, 1.23100969126526, 0.44044943820224725, 32.83335969046958, 0.19877805012361263\n",
"refl:, 1.23100969126526, 0.43555555555555553, 32.42350386700291, 0.19904737688450852\n",
"refl:, 1.23100969126526, 0.4307692307692308, 32.0244494386133, 0.19925404758581897\n",
"refl:, 1.23100969126526, 0.4260869565217391, 31.63574524940934, 0.1993954429097289\n",
"refl:, 1.23100969126526, 0.421505376344086, 31.2569666032255, 0.19942422718572894\n",
"refl:, 1.23100969126526, 0.41702127659574467, 30.887713235292672, 0.1993498431053417\n",
"refl:, 1.23100969126526, 0.4126315789473684, 30.527607477190394, 0.19917542826890433\n",
"refl:, 1.23100969126526, 0.4083333333333333, 30.176292593038497, 0.19903411145233238\n",
"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": [
{
"data": {
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\n",
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