From ebc44d464e44b29f783cce092722b867a2352fc1 Mon Sep 17 00:00:00 2001 From: Dan2357 <122879023+Dan2357@users.noreply.github.com> Date: Fri, 24 Nov 2023 21:51:10 +0000 Subject: [PATCH] bfast algorithm for fixed angle broadband (#2609) * initial bfast draft * Revert changes to examples * more changes to examples * documentation * fixing bfast function * reflectance spectrum example * trying to fix 2d convergence error * 2d convergence & type error * converting mathematical documentation to markdown * improving markdown file * more improvements to markdown file * adding to documentation and deleting files * adding refractive index to documentation * Update doc/bfast/fixed_angle_broadband_simulations_in_Meep.md --------- Co-authored-by: Daniel Lloyd-Jones Co-authored-by: Steven G. Johnson --- ...xed_angle_broadband_simulations_in_Meep.md | 154 + python/examples/refl_angular_bfast.ipynb | 2602 +++++++++++++++++ python/simulation.py | 6 + src/Makefile.am | 2 +- src/cw_fields.cpp | 4 +- src/energy_and_flux.cpp | 2 + src/fields.cpp | 28 +- src/fields_dump.cpp | 6 + src/meep.hpp | 13 +- src/meep_internals.hpp | 27 + src/step_db.cpp | 18 + src/step_generic.cpp | 200 ++ 12 files changed, 3053 insertions(+), 9 deletions(-) create mode 100644 doc/bfast/fixed_angle_broadband_simulations_in_Meep.md create mode 100644 python/examples/refl_angular_bfast.ipynb diff --git a/doc/bfast/fixed_angle_broadband_simulations_in_Meep.md b/doc/bfast/fixed_angle_broadband_simulations_in_Meep.md new file mode 100644 index 000000000..c939b8418 --- /dev/null +++ b/doc/bfast/fixed_angle_broadband_simulations_in_Meep.md @@ -0,0 +1,154 @@ +--- +# Fixed Angle Broadband Simulations in Meep +--- + +Introduction +============ + +Currently in MEEP, Bloch Periodic boundary conditions are implemented, +which fix the wave vector of an incident wave [1]. As a result, the +angle of an oblique incident wave becomes frequency dependent. Following +the procedure detailed by B. Liang et al [2], all fields can be +redefined so that the boundary conditions become periodic and the angle +of the incident wave can be fixed over a broad frequency spectrum. This +requires the addition of a new field. It is assumed that the reader is +already familiar with the UPML formulation in MEEP [3], from which +the equations will be modified. B. Liang et al applied this method by +splitting the electric and magnetic fields into multiple terms. This is +different from the UPML formulation in MEEP, which allows simulation of +more complex media, and so the method of B. Liang et al has to be adapted. + +Boundary conditions +=================== + +The fields from section 3 of *Notes on the UPML implementation in MEEP* +[3] are first redefined as: +```math +\text{field}'(x,y,z) = \text{field}(x,y,z)e^{-i(k_{x}x+k_{y}y)}, \tag{1} +``` +where $k_{x}$ and $k_{y}$ are the wave vector components in the x and y +directions. This is for a structure which is periodic in these +directions. Taking the electric field $E$ as an example, the new +boundary condition can be expressed as +```math +E'(x+a,y+b,z) = E(x+a,y+b,z)e^{-i(k_{x}(x+a)+k_{y}(y+b))} \tag{2} +``` +where a is the length of the unit cell in the x direction and b in the y direction. +Substituting in the original Bloch periodic boundary conditions gives +```math +E'(x+a,y+b,z) = E(x,y,z)e^{i(k_{x}a+k_{y}b)}e^{-i(k_{x}(x+a)+k_{y}(y+b))}. \tag{3} +``` +Cancelling the $a$ and $b$ terms gives +```math +E'(x+a,y+b,z) =E(x,y,z)e^{-i(k_{x}x+k_{y}y)}=E'(x,y,z), \tag{4} +``` +and so the boundary conditions are now periodic. + +Formulation +=========== + +Equation (5) from section 3 of *Notes on the UPML implementation in +MEEP* [3] is +```math +\vec{K} = \nabla \times \vec{H}=-i\omega(1+\frac{i\sigma_{D}}{\omega})\vec{C}, \tag{5} +``` +where $\vec{H}$ is the magnetic field, $\sigma_{D}$ the conductivity and +$\vec{C}$ an auxiliary field. When the magnetic field is redefined, the +curl of a product must be carried out: +```math +\nabla\times \vec{H'} = \nabla\times (\vec{H} e^{-i(k_{x}x+k_{y}y)}) \tag{6} +``` +so, +```math +\nabla\times \vec{H'} = e^{-i(k_{x}x+k_{y}y)} \nabla\times \vec{H} + \begin{pmatrix} -ik_{x} \\-ik_{y}\\0 \end{pmatrix} \ \times \vec{H'} \tag{7} +``` +where the complex exponential in the second term has been absorbed by +$\vec{H'}$. Substituting in equation (5) gives +```math +\nabla\times \vec{H'} = \vec{K'} = -i\omega (1+\frac{i\sigma_{D}}{\omega}) \vec{C'} + \begin{pmatrix} -ik_{x} \\-ik_{y}\\0 \end{pmatrix} \ \times \vec{H'}. \tag{8} +``` +From here on in, the prime notation can be dropped since this applies to +all fields. By introducing a new field $\vec{F}$, equation +(8) can be written as +```math +\vec{K} = -i\omega(1+\frac{i\sigma_{D}}{\omega})\vec{C} - i\omega\vec{F}. \tag{9} +``` +This new field satisfies the equation: +```math +\vec{F} = \vec{\bar{k}}\times\vec{H}, \tag{10} +``` +where +```math +\vec{\bar{k}} =\frac{1}{\omega}\begin{pmatrix} k_{x} \\ k_{y}\\0 \end{pmatrix} \ = n \begin{pmatrix} \sin{\theta}\cos{\phi} \\ \sin{\theta}\sin{\phi}\\0 \end{pmatrix} \ \tag{11} +``` +and so $\vec{\bar{k}}$ is the wave vector with its frequency dependence +removed. $\theta$ and $\phi$ are the propagating direction angles, $n$ is the refractive index of the source medium and c, +the speed of light is taken to be 1. Therefore by defining $\vec{F}$, +the angle of the incident wave is fixed. Equation +(10) can be discretized as: +```math +\vec{F}^{n+1}=2\bar{\vec{k}}\times\vec{H}^{n+0.5} -\vec{F}^{n} . \tag{12} +``` +Transforming equation (9) +to the time domain gives: +```math +\vec{K} = \frac{\partial \vec{C}}{\partial t}+\sigma_{D}\vec{C}+\frac{\partial \vec{F}}{\partial t} . \tag{13} +``` +This can be discretized as: +```math +\vec{K}^{n+0.5}=\frac{\vec{C}^{n+1}-\vec{C}^n}{\Delta t}+\sigma_{D}\frac{\vec{C}^{n+1}+\vec{C}^n}{2} + \frac{\vec{F}^{n+1}-\vec{F}^{n}}{\Delta t} \tag{14} +``` +and then solved to update the value of $\vec{C}$ using: +```math +\vec{C}^{n+1}=(1+\frac{\sigma_{D} \Delta t}{2})^{-1} [(1-\frac{\sigma_D \Delta t}{2}) \vec{C}^n+\Delta t\vec{K}^{n+0.5}+\vec{F}^{n}-\vec{F}^{n+1}] . \tag{15} +``` +All other equations are unaffected by these changes. + +A new field must be introduced because $\vec{H}$ is defined at +$n+\frac{1}{2}$ timesteps whereas $\vec{C}$ is defined at $n$ timesteps, +where $n$ is an integer. As a result, if the derivative in $\vec{F}$ in +equation (14) was replaced with +```math +\vec{\bar{k}}\times(\frac{\vec{H}^{n+0.5}-\vec{H}^{n-0.5}}{\Delta t}), \tag{16} +``` +only first order accuracy would be achieved, since this is a backward +difference scheme. To achieve second order accuracy would require +$\vec{H}^{n+1.5}$ to be known. + +Application to the source code +========= + +$\vec{C}$ is first time-stepped using the original function in the MEEP source code, i.e. using +```math +\vec{C}^{n+1}=(1+\frac{\sigma_{D} \Delta t}{2})^{-1} [(1-\frac{\sigma_D \Delta t}{2}) \vec{C}^n+\Delta t\vec{K}^{n+0.5}]. \tag{17} +``` +When fixed angle broadband simulations are required, a new function is called which recovers equation (15) using +```math +\vec{C'}^{n+1} = (1+\frac{\sigma_{D} \Delta t}{2})^{-1} (\vec{F}^{n}-\vec{F}^{n+1}) + \vec{C}^{n+1}. \tag{18} +``` +Similarly, all other fields which depend on the value of $\vec{C}$ have new terms added to them, multiplied by the relevant conductivity. Therefore the original functions in MEEP remain unchanged. + +Stability +========= + +As the incident angle increases, the maximum possible $\Delta t$ value +decreases, following the formula: +```math +\frac{c\Delta t}{\Delta x} \leq \frac{(1-\sin(\theta))}{\sqrt{D}} \tag{17} +``` +where D is the number of dimensions [2]. + +References +========= + +[1] Taflove A., Oskooi A., Johnson S.. *Advances in FDTD Computational +Electrodynamics: Photonics and Nanotechnology*. Artech House, Inc.; 2013 + +[2] Liang B., Bai M., Ma H., Ou N., Miao J.. Wideband Analysis of Periodic +Structures at Oblique Incidence by Material Independent FDTD Algorithm. +*IEEE Transactions on Antennas and Propagation*, vol. 62, no. 1, pp. +354-360, Jan. 2014, doi: 10.1109/TAP.2013.2287896. + +[3] Johnson S. *Notes on the UPML implementation in Meep*. Massachusetts +Institute of Technology. Posted August 17, 2009; updated March 10, 2010. +http://ab-initio.mit.edu/meep/pml-meep.pdf diff --git a/python/examples/refl_angular_bfast.ipynb b/python/examples/refl_angular_bfast.ipynb new file mode 100644 index 000000000..483f6df17 --- /dev/null +++ b/python/examples/refl_angular_bfast.ipynb @@ -0,0 +1,2602 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Angular Reflectance Spectrum of a Planar Interface with Bfast " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This provides an example of how to use the bfast feature. The reflectance spectrum of a planar interface is obtained first using bfast and then by using Bloch periodic boundary conditions to allow a comparison. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Below is the function to calculate the spectrum using bfast." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "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(thickness=dpml,direction=mp.Z)]\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", + "\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", + " if theta > 40: #needs to be lower for stability\n", + " Courant = 0.05\n", + " else:\n", + " Courant = 0.1\n", + "\n", + " sim = mp.Simulation(\n", + " cell_size=cell_size,\n", + " boundary_layers=pml_layers,\n", + " sources=sources,\n", + " k_point=mp.Vector3(),\n", + " dimensions=dimensions,\n", + " resolution=resolution,\n", + " need_bfast = True,\n", + " bfast_k_bar = (np.sin(theta_r),0,0), #sets the angle of the incident wave\n", + " Courant = Courant \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=mp.Vector3(),\n", + " dimensions=dimensions,\n", + " resolution=resolution,\n", + " need_bfast = True,\n", + " bfast_k_bar = (np.sin(theta_r),0,0),\n", + " Courant = Courant \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", + " R = np.empty(nfreq)\n", + " for i in range(nfreq):\n", + " wvls[i] = 1 / freqs[i]\n", + " R[i] = -refl_flux[i] / empty_flux[i]\n", + " print(\"refl:, {}, {}, {}\".format(wvls[i], theta, R[i]))\n", + " \n", + " return wvls, theta, R" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This is the same function but using Bloch periodic boundaries." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "def planar_reflectance_original(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", + " 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", + " 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\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The reflectance spectrum is then calculated for a range of angles between 0 and 50 degrees." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000143223 s\n", + "Working in 1D dimensions.\n", + "Computational cell is 0 x 0 x 12 with resolution 50\n", + "time for set_epsilon = 0.000574305 s\n", + "-----------\n", + "field decay(t = 50.002): 0.2535922222197771 / 0.2535922222197771 = 1.0\n", + "field decay(t = 100.004): 3.242069433496442e-17 / 0.2535922222197771 = 1.2784577559664604e-16\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000176516 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 = 0.000425481 s\n", + "-----------\n", + "field decay(t = 50.002): 0.25359222221929495 / 0.25359222221929495 = 1.0\n", + "field decay(t = 100.004): 1.7974784816283913e-11 / 0.25359222221929495 = 7.088066289643592e-11\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "refl:, 0.8, 0, 0.29478548225481105\n", + "refl:, 0.784, 0, 0.29418950277735434\n", + "refl:, 0.7686274509803922, 0, 0.29357486395416005\n", + "refl:, 0.7538461538461539, 0, 0.2929420807997511\n", + "refl:, 0.739622641509434, 0, 0.2922935655705215\n", + "refl:, 0.7259259259259259, 0, 0.29163159706426195\n", + "refl:, 0.7127272727272727, 0, 0.2909614611019373\n", + "refl:, 0.7, 0, 0.29027935535339117\n", + "refl:, 0.6877192982456141, 0, 0.2895815443425243\n", + "refl:, 0.6758620689655173, 0, 0.2888680662876321\n", + "refl:, 0.664406779661017, 0, 0.2881388355970032\n", + "refl:, 0.6533333333333333, 0, 0.28739275910329115\n", + "refl:, 0.6426229508196721, 0, 0.286628856608785\n", + "refl:, 0.632258064516129, 0, 0.28584846465691577\n", + "refl:, 0.6222222222222222, 0, 0.28505169560237953\n", + "refl:, 0.6124999999999999, 0, 0.28423842999521126\n", + "refl:, 0.6030769230769231, 0, 0.2834079993023883\n", + "refl:, 0.593939393939394, 0, 0.28256204719962924\n", + "refl:, 0.5850746268656717, 0, 0.2817003301974453\n", + "refl:, 0.5764705882352942, 0, 0.2808213290862427\n", + "refl:, 0.5681159420289855, 0, 0.2799244257585028\n", + "refl:, 0.56, 0, 0.27901102094601093\n", + "refl:, 0.552112676056338, 0, 0.27808043408086164\n", + "refl:, 0.5444444444444444, 0, 0.27713092101876063\n", + "refl:, 0.536986301369863, 0, 0.276162390374119\n", + "refl:, 0.5297297297297298, 0, 0.27517617587329524\n", + "refl:, 0.5226666666666667, 0, 0.2741714434357309\n", + "refl:, 0.5157894736842105, 0, 0.2731462013166033\n", + "refl:, 0.509090909090909, 0, 0.2721009043518885\n", + "refl:, 0.5025641025641026, 0, 0.2710367913111096\n", + "refl:, 0.4962025316455696, 0, 0.26995293126935566\n", + "refl:, 0.49, 0, 0.26884720575927684\n", + "refl:, 0.4839506172839506, 0, 0.2677202617255878\n", + "refl:, 0.47804878048780486, 0, 0.2665731780815131\n", + "refl:, 0.47228915662650606, 0, 0.26540397467290155\n", + "refl:, 0.4666666666666667, 0, 0.2642110318143788\n", + "refl:, 0.4611764705882353, 0, 0.2629954683396131\n", + "refl:, 0.4558139534883721, 0, 0.26175863555451606\n", + "refl:, 0.4505747126436782, 0, 0.26049896117903665\n", + "refl:, 0.4454545454545454, 0, 0.25921502222214193\n", + "refl:, 0.44044943820224725, 0, 0.2579090629603906\n", + "refl:, 0.43555555555555553, 0, 0.256580649323656\n", + "refl:, 0.4307692307692308, 0, 0.25522606552593585\n", + "refl:, 0.4260869565217391, 0, 0.25384522866650144\n", + "refl:, 0.421505376344086, 0, 0.25243801360582724\n", + "refl:, 0.41702127659574467, 0, 0.25100343004649217\n", + "refl:, 0.4126315789473684, 0, 0.24954457699982377\n", + "refl:, 0.4083333333333333, 0, 0.24806444446511278\n", + "refl:, 0.4041237113402062, 0, 0.24656495462483433\n", + "refl:, 0.4, 0, 0.24504499947625613\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000144515 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 = 0.00931418 s\n", + "-----------\n", + "on time step 19400 (time=38.8), 0.000206201 s/step\n", + "field decay(t = 50.002): 0.2516378174357578 / 0.2516378174357578 = 1.0\n", + "on time step 39049 (time=78.098), 0.000203578 s/step\n", + "field decay(t = 100.004): 6.675562675812582e-19 / 0.2516378174357578 = 2.6528455634522534e-18\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000164073 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 = 0.0216444 s\n", + "-----------\n", + "on time step 19127 (time=38.254), 0.000209134 s/step\n", + "field decay(t = 50.002): 0.25163781746810493 / 0.25163781746810493 = 1.0\n", + "on time step 38489 (time=76.978), 0.000206596 s/step\n", + "field decay(t = 100.004): 1.7877917750520137e-11 / 0.25163781746810493 = 7.104622798910645e-11\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "refl:, 0.8, 5, 0.2933716195679948\n", + "refl:, 0.784, 5, 0.29279835058754977\n", + "refl:, 0.7686274509803922, 5, 0.2922089063410139\n", + "refl:, 0.7538461538461539, 5, 0.291594110049036\n", + "refl:, 0.739622641509434, 5, 0.29094909563726257\n", + "refl:, 0.7259259259259259, 5, 0.2902947626202328\n", + "refl:, 0.7127272727272727, 5, 0.2896238391645192\n", + "refl:, 0.7, 5, 0.28894020244730007\n", + "refl:, 0.6877192982456141, 5, 0.28824286775164804\n", + "refl:, 0.6758620689655173, 5, 0.2875300970619326\n", + "refl:, 0.664406779661017, 5, 0.2868025102768468\n", + "refl:, 0.6533333333333333, 5, 0.28605690901665426\n", + "refl:, 0.6426229508196721, 5, 0.28529263354102485\n", + "refl:, 0.632258064516129, 5, 0.28451144920911653\n", + "refl:, 0.6222222222222222, 5, 0.2837156138854464\n", + "refl:, 0.6124999999999999, 5, 0.2829031570504199\n", + "refl:, 0.6030769230769231, 5, 0.2820735945863569\n", + "refl:, 0.593939393939394, 5, 0.28122814052012046\n", + "refl:, 0.5850746268656717, 5, 0.28036754772622924\n", + "refl:, 0.5764705882352942, 5, 0.2794896145667775\n", + "refl:, 0.5681159420289855, 5, 0.2785934841278731\n", + "refl:, 0.56, 5, 0.27768045608041714\n", + "refl:, 0.552112676056338, 5, 0.27675084419456775\n", + "refl:, 0.5444444444444444, 5, 0.2758026849867616\n", + "refl:, 0.536986301369863, 5, 0.2748350320221077\n", + "refl:, 0.5297297297297298, 5, 0.27384938304268597\n", + "refl:, 0.5226666666666667, 5, 0.2728457150463129\n", + "refl:, 0.5157894736842105, 5, 0.2718221260192849\n", + "refl:, 0.509090909090909, 5, 0.2707778345768521\n", + "refl:, 0.5025641025641026, 5, 0.26971435089863544\n", + "refl:, 0.4962025316455696, 5, 0.2686316686425263\n", + "refl:, 0.49, 5, 0.2675274084843396\n", + "refl:, 0.4839506172839506, 5, 0.2664011953869428\n", + "refl:, 0.47804878048780486, 5, 0.2652544215239206\n", + "refl:, 0.47228915662650606, 5, 0.26408677551716825\n", + "refl:, 0.4666666666666667, 5, 0.26289604210086376\n", + "refl:, 0.4611764705882353, 5, 0.2616817097018477\n", + "refl:, 0.4558139534883721, 5, 0.2604456919216081\n", + "refl:, 0.4505747126436782, 5, 0.2591873807606957\n", + "refl:, 0.4454545454545454, 5, 0.25790441736588227\n", + "refl:, 0.44044943820224725, 5, 0.25659747563264934\n", + "refl:, 0.43555555555555553, 5, 0.25526796410331976\n", + "refl:, 0.4307692307692308, 5, 0.25391565929403254\n", + "refl:, 0.4260869565217391, 5, 0.25253863770558993\n", + "refl:, 0.421505376344086, 5, 0.2511343570533036\n", + "refl:, 0.41702127659574467, 5, 0.24970592201516176\n", + "refl:, 0.4126315789473684, 5, 0.2482560146850886\n", + "refl:, 0.4083333333333333, 5, 0.2467768590952899\n", + "refl:, 0.4041237113402062, 5, 0.24526977150227444\n", + "refl:, 0.4, 5, 0.2437490830587842\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000154415 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 = 0.00752692 s\n", + "-----------\n", + "on time step 18723 (time=37.446), 0.000213655 s/step\n", + "field decay(t = 50.002): 0.24583636391268876 / 0.24583636391268876 = 1.0\n", + "on time step 38248 (time=76.496), 0.000204872 s/step\n", + "field decay(t = 100.004): 3.058960455182634e-17 / 0.24583636391268876 = 1.2443075574730898e-16\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000153703 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 = 0.0192925 s\n", + "-----------\n", + "on time step 19012 (time=38.024), 0.000210403 s/step\n", + "field decay(t = 50.002): 0.24583636413646928 / 0.24583636413646928 = 1.0\n", + "on time step 37801 (time=75.602), 0.000212897 s/step\n", + "field decay(t = 100.004): 1.7591438359522674e-11 / 0.24583636413646928 = 7.155751111644847e-11\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "refl:, 0.8, 10, 0.2893897843166937\n", + "refl:, 0.784, 10, 0.2887851971507613\n", + "refl:, 0.7686274509803922, 10, 0.2881690525544746\n", + "refl:, 0.7538461538461539, 10, 0.287545004251638\n", + "refl:, 0.739622641509434, 10, 0.28690878607524295\n", + "refl:, 0.7259259259259259, 10, 0.286256113450063\n", + "refl:, 0.7127272727272727, 10, 0.2855907212526786\n", + "refl:, 0.7, 10, 0.28491021267522065\n", + "refl:, 0.6877192982456141, 10, 0.28421300520951154\n", + "refl:, 0.6758620689655173, 10, 0.28349839916100333\n", + "refl:, 0.664406779661017, 10, 0.28276755972394985\n", + "refl:, 0.6533333333333333, 10, 0.28202087484202715\n", + "refl:, 0.6426229508196721, 10, 0.28125874512664\n", + "refl:, 0.632258064516129, 10, 0.28048039875815856\n", + "refl:, 0.6222222222222222, 10, 0.27968690933965706\n", + "refl:, 0.6124999999999999, 10, 0.2788774623986072\n", + "refl:, 0.6030769230769231, 10, 0.27805111131686533\n", + "refl:, 0.593939393939394, 10, 0.2772074958013216\n", + "refl:, 0.5850746268656717, 10, 0.2763481705982354\n", + "refl:, 0.5764705882352942, 10, 0.2754728932823483\n", + "refl:, 0.5681159420289855, 10, 0.2745798994044755\n", + "refl:, 0.56, 10, 0.2736691662926268\n", + "refl:, 0.552112676056338, 10, 0.27274173937221535\n", + "refl:, 0.5444444444444444, 10, 0.27179718776835593\n", + "refl:, 0.536986301369863, 10, 0.27083332306534125\n", + "refl:, 0.5297297297297298, 10, 0.26984993072354674\n", + "refl:, 0.5226666666666667, 10, 0.26884852396302145\n", + "refl:, 0.5157894736842105, 10, 0.26782858854708\n", + "refl:, 0.509090909090909, 10, 0.2667882249814247\n", + "refl:, 0.5025641025641026, 10, 0.2657272029447466\n", + "refl:, 0.4962025316455696, 10, 0.26464689667286173\n", + "refl:, 0.49, 10, 0.2635468648456616\n", + "refl:, 0.4839506172839506, 10, 0.26242468913331735\n", + "refl:, 0.47804878048780486, 10, 0.261280396259151\n", + "refl:, 0.47228915662650606, 10, 0.26011588376257166\n", + "refl:, 0.4666666666666667, 10, 0.2589302261006125\n", + "refl:, 0.4611764705882353, 10, 0.2577210207637418\n", + "refl:, 0.4558139534883721, 10, 0.2564884102692321\n", + "refl:, 0.4505747126436782, 10, 0.2552338628502107\n", + "refl:, 0.4454545454545454, 10, 0.25395659051331976\n", + "refl:, 0.44044943820224725, 10, 0.25265380316259906\n", + "refl:, 0.43555555555555553, 10, 0.251325477129935\n", + "refl:, 0.4307692307692308, 10, 0.24997496261574478\n", + "refl:, 0.4260869565217391, 10, 0.24860138157706754\n", + "refl:, 0.421505376344086, 10, 0.24720014763347223\n", + "refl:, 0.41702127659574467, 10, 0.2457739738151533\n", + "refl:, 0.4126315789473684, 10, 0.24432801931857556\n", + "refl:, 0.4083333333333333, 10, 0.2428566896842107\n", + "refl:, 0.4041237113402062, 10, 0.2413551019637171\n", + "refl:, 0.4, 10, 0.23983142722536951\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000147251 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 = 0.00721024 s\n", + "-----------\n", + "on time step 19239 (time=38.478), 0.000207924 s/step\n", + "field decay(t = 50.002): 0.23637163700895852 / 0.23637163700895852 = 1.0\n", + "on time step 38420 (time=76.84), 0.000208543 s/step\n", + "field decay(t = 100.004): 1.0916710215991391e-18 / 0.23637163700895852 = 4.618451838863242e-18\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000219658 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 = 0.0208905 s\n", + "-----------\n", + "on time step 19064 (time=38.128), 0.00020982 s/step\n", + "field decay(t = 50.002): 0.23637163767302732 / 0.23637163767302732 = 1.0\n", + "on time step 38455 (time=76.91), 0.000206286 s/step\n", + "field decay(t = 100.004): 1.6804772428196017e-11 / 0.23637163767302732 = 7.109470744303952e-11\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "refl:, 0.8, 15, 0.28261653978833406\n", + "refl:, 0.784, 15, 0.28198065000385614\n", + "refl:, 0.7686274509803922, 15, 0.28135684907998176\n", + "refl:, 0.7538461538461539, 15, 0.2807348929461326\n", + "refl:, 0.739622641509434, 15, 0.2801028414727844\n", + "refl:, 0.7259259259259259, 15, 0.27945275072374515\n", + "refl:, 0.7127272727272727, 15, 0.2787910773937956\n", + "refl:, 0.7, 15, 0.27811262380034074\n", + "refl:, 0.6877192982456141, 15, 0.2774179067711086\n", + "refl:, 0.6758620689655173, 15, 0.27670403924183556\n", + "refl:, 0.664406779661017, 15, 0.27597247131957753\n", + "refl:, 0.6533333333333333, 15, 0.2752268255648048\n", + "refl:, 0.6426229508196721, 15, 0.27446732197021323\n", + "refl:, 0.632258064516129, 15, 0.273693039169977\n", + "refl:, 0.6222222222222222, 15, 0.27290226401116086\n", + "refl:, 0.6124999999999999, 15, 0.272095804221068\n", + "refl:, 0.6030769230769231, 15, 0.2712745732770359\n", + "refl:, 0.593939393939394, 15, 0.27043681028119204\n", + "refl:, 0.5850746268656717, 15, 0.2695816045673884\n", + "refl:, 0.5764705882352942, 15, 0.2687099636334329\n", + "refl:, 0.5681159420289855, 15, 0.2678223407194867\n", + "refl:, 0.56, 15, 0.26691741036016503\n", + "refl:, 0.552112676056338, 15, 0.2659939143519373\n", + "refl:, 0.5444444444444444, 15, 0.26505260126422936\n", + "refl:, 0.536986301369863, 15, 0.2640940771702438\n", + "refl:, 0.5297297297297298, 15, 0.2631168004652539\n", + "refl:, 0.5226666666666667, 15, 0.26211965500176415\n", + "refl:, 0.5157894736842105, 15, 0.2611035759981257\n", + "refl:, 0.509090909090909, 15, 0.26006900028195795\n", + "refl:, 0.5025641025641026, 15, 0.2590144821801946\n", + "refl:, 0.4962025316455696, 15, 0.2579388916455253\n", + "refl:, 0.49, 15, 0.2568429734049643\n", + "refl:, 0.4839506172839506, 15, 0.255727475628118\n", + "refl:, 0.47804878048780486, 15, 0.25459112844601306\n", + "refl:, 0.47228915662650606, 15, 0.25343252600168487\n", + "refl:, 0.4666666666666667, 15, 0.25225264121852287\n", + "refl:, 0.4611764705882353, 15, 0.2510523897372336\n", + "refl:, 0.4558139534883721, 15, 0.2498296092803488\n", + "refl:, 0.4505747126436782, 15, 0.2485822245131237\n", + "refl:, 0.4454545454545454, 15, 0.2473113763570066\n", + "refl:, 0.44044943820224725, 15, 0.24601746382979553\n", + "refl:, 0.43555555555555553, 15, 0.24469774799830904\n", + "refl:, 0.4307692307692308, 15, 0.24335176178468873\n", + "refl:, 0.4260869565217391, 15, 0.24198309713114388\n", + "refl:, 0.421505376344086, 15, 0.24059292031900087\n", + "refl:, 0.41702127659574467, 15, 0.23917887002166027\n", + "refl:, 0.4126315789473684, 15, 0.23774109605840296\n", + "refl:, 0.4083333333333333, 15, 0.2362802952094362\n", + "refl:, 0.4041237113402062, 15, 0.2347900347477055\n", + "refl:, 0.4, 15, 0.23325925289032198\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000143423 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 = 0.00749935 s\n", + "-----------\n", + "on time step 19620 (time=39.24), 0.000203883 s/step\n", + "field decay(t = 50.002): 0.2235423173560802 / 0.2235423173560802 = 1.0\n", + "on time step 38572 (time=77.144), 0.000211067 s/step\n", + "field decay(t = 100.004): 9.183665348658521e-18 / 0.2235423173560802 = 4.1082446747789033e-17\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000159775 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 = 0.0283588 s\n", + "-----------\n", + "on time step 18970 (time=37.94), 0.000210868 s/step\n", + "field decay(t = 50.002): 0.22354231896670912 / 0.22354231896670912 = 1.0\n", + "on time step 38119 (time=76.238), 0.000208896 s/step\n", + "field decay(t = 100.004): 1.6613045111537723e-11 / 0.22354231896670912 = 7.431722632353926e-11\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "refl:, 0.8, 20, 0.27289867606625623\n", + "refl:, 0.784, 20, 0.27230040124836113\n", + "refl:, 0.7686274509803922, 20, 0.27168906341916277\n", + "refl:, 0.7538461538461539, 20, 0.27105929675373486\n", + "refl:, 0.739622641509434, 20, 0.2704162527879995\n", + "refl:, 0.7259259259259259, 20, 0.2697691525026485\n", + "refl:, 0.7127272727272727, 20, 0.26910962359950025\n", + "refl:, 0.7, 20, 0.2684335629975832\n", + "refl:, 0.6877192982456141, 20, 0.2677417375212695\n", + "refl:, 0.6758620689655173, 20, 0.2670333122483468\n", + "refl:, 0.664406779661017, 20, 0.2663090270813368\n", + "refl:, 0.6533333333333333, 20, 0.2655691358960935\n", + "refl:, 0.6426229508196721, 20, 0.2648132362745719\n", + "refl:, 0.632258064516129, 20, 0.2640428077689008\n", + "refl:, 0.6222222222222222, 20, 0.2632585237763119\n", + "refl:, 0.6124999999999999, 20, 0.26245878401209544\n", + "refl:, 0.6030769230769231, 20, 0.2616428876940047\n", + "refl:, 0.593939393939394, 20, 0.2608116033945687\n", + "refl:, 0.5850746268656717, 20, 0.25996451916227536\n", + "refl:, 0.5764705882352942, 20, 0.25909999483378815\n", + "refl:, 0.5681159420289855, 20, 0.25821759641286085\n", + "refl:, 0.56, 20, 0.2573182961573138\n", + "refl:, 0.552112676056338, 20, 0.2564021279074438\n", + "refl:, 0.5444444444444444, 20, 0.25546758082555293\n", + "refl:, 0.536986301369863, 20, 0.2545138484210118\n", + "refl:, 0.5297297297297298, 20, 0.2535418429685966\n", + "refl:, 0.5226666666666667, 20, 0.25255207333368906\n", + "refl:, 0.5157894736842105, 20, 0.25154325729308175\n", + "refl:, 0.509090909090909, 20, 0.25051428182967067\n", + "refl:, 0.5025641025641026, 20, 0.2494659488889207\n", + "refl:, 0.4962025316455696, 20, 0.24839919845305766\n", + "refl:, 0.49, 20, 0.2473129492507779\n", + "refl:, 0.4839506172839506, 20, 0.24620559116994845\n", + "refl:, 0.47804878048780486, 20, 0.24507749720583905\n", + "refl:, 0.47228915662650606, 20, 0.24392979708128154\n", + "refl:, 0.4666666666666667, 20, 0.24276157676008236\n", + "refl:, 0.4611764705882353, 20, 0.24157093714223418\n", + "refl:, 0.4558139534883721, 20, 0.24035802728025488\n", + "refl:, 0.4505747126436782, 20, 0.23912410697168635\n", + "refl:, 0.4454545454545454, 20, 0.23786843320525117\n", + "refl:, 0.44044943820224725, 20, 0.23658914986547744\n", + "refl:, 0.43555555555555553, 20, 0.2352861084922003\n", + "refl:, 0.4307692307692308, 20, 0.23395953588668647\n", + "refl:, 0.4260869565217391, 20, 0.2326076330473713\n", + "refl:, 0.421505376344086, 20, 0.23122884695865362\n", + "refl:, 0.41702127659574467, 20, 0.22982368408308648\n", + "refl:, 0.4126315789473684, 20, 0.22839099800727772\n", + "refl:, 0.4083333333333333, 20, 0.22692816038076669\n", + "refl:, 0.4041237113402062, 20, 0.22544034342649155\n", + "refl:, 0.4, 20, 0.22393996689309376\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000148012 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 = 0.00809133 s\n", + "-----------\n", + "on time step 19036 (time=38.072), 0.000210131 s/step\n", + "field decay(t = 50.002): 0.20775185035757404 / 0.20775185035757404 = 1.0\n", + "on time step 38509 (time=77.018), 0.000205421 s/step\n", + "field decay(t = 100.004): 2.2436667668293042e-18 / 0.20775185035757404 = 1.0799743843280318e-17\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000277058 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 = 0.0212252 s\n", + "-----------\n", + "on time step 18198 (time=36.396), 0.000219819 s/step\n", + "field decay(t = 50.002): 0.20775185303366428 / 0.20775185303366428 = 1.0\n", + "on time step 37105 (time=74.21), 0.000211565 s/step\n", + "field decay(t = 100.004): 1.5953604416754712e-11 / 0.20775185303366428 = 7.679163474979728e-11\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "refl:, 0.8, 25, 0.26012398323401736\n", + "refl:, 0.784, 25, 0.25954389716621834\n", + "refl:, 0.7686274509803922, 25, 0.2589508728393948\n", + "refl:, 0.7538461538461539, 25, 0.2583446329374831\n", + "refl:, 0.739622641509434, 25, 0.2577236426681682\n", + "refl:, 0.7259259259259259, 25, 0.2570806362415459\n", + "refl:, 0.7127272727272727, 25, 0.25641708008638014\n", + "refl:, 0.7, 25, 0.25573920340901296\n", + "refl:, 0.6877192982456141, 25, 0.2550482140295809\n", + "refl:, 0.6758620689655173, 25, 0.25434283027886817\n", + "refl:, 0.664406779661017, 25, 0.2536239050654776\n", + "refl:, 0.6533333333333333, 25, 0.2528925660556876\n", + "refl:, 0.6426229508196721, 25, 0.252147907965881\n", + "refl:, 0.632258064516129, 25, 0.251388230565196\n", + "refl:, 0.6222222222222222, 25, 0.2506128153138932\n", + "refl:, 0.6124999999999999, 25, 0.24982182642925282\n", + "refl:, 0.6030769230769231, 25, 0.24901506779124943\n", + "refl:, 0.593939393939394, 25, 0.24819154480860195\n", + "refl:, 0.5850746268656717, 25, 0.24735063125458245\n", + "refl:, 0.5764705882352942, 25, 0.24649293394495944\n", + "refl:, 0.5681159420289855, 25, 0.24561896072701594\n", + "refl:, 0.56, 25, 0.24472768225111574\n", + "refl:, 0.552112676056338, 25, 0.24381784112289007\n", + "refl:, 0.5444444444444444, 25, 0.24288984662670204\n", + "refl:, 0.536986301369863, 25, 0.24194470426421394\n", + "refl:, 0.5297297297297298, 25, 0.24098190382451873\n", + "refl:, 0.5226666666666667, 25, 0.2400001516208727\n", + "refl:, 0.5157894736842105, 25, 0.23899948341373228\n", + "refl:, 0.509090909090909, 25, 0.23798088715116694\n", + "refl:, 0.5025641025641026, 25, 0.2369442791570512\n", + "refl:, 0.4962025316455696, 25, 0.23588841339830457\n", + "refl:, 0.49, 25, 0.23481264062401186\n", + "refl:, 0.4839506172839506, 25, 0.23371748398038839\n", + "refl:, 0.47804878048780486, 25, 0.23260326175933413\n", + "refl:, 0.47228915662650606, 25, 0.23146909962749695\n", + "refl:, 0.4666666666666667, 25, 0.2303139380175622\n", + "refl:, 0.4611764705882353, 25, 0.229137908506649\n", + "refl:, 0.4558139534883721, 25, 0.22794166972203914\n", + "refl:, 0.4505747126436782, 25, 0.22672465782677115\n", + "refl:, 0.4454545454545454, 25, 0.22548542251025588\n", + "refl:, 0.44044943820224725, 25, 0.2242237030312985\n", + "refl:, 0.43555555555555553, 25, 0.22294036437178213\n", + "refl:, 0.4307692307692308, 25, 0.22163500702160932\n", + "refl:, 0.4260869565217391, 25, 0.22030568267317235\n", + "refl:, 0.421505376344086, 25, 0.21895158468397222\n", + "refl:, 0.41702127659574467, 25, 0.2175740575077417\n", + "refl:, 0.4126315789473684, 25, 0.21617396969192526\n", + "refl:, 0.4083333333333333, 25, 0.21474956430492415\n", + "refl:, 0.4041237113402062, 25, 0.2132978500140713\n", + "refl:, 0.4, 25, 0.2118182028468839\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000153172 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 = 0.00705134 s\n", + "-----------\n", + "on time step 18726 (time=37.452), 0.00021361 s/step\n", + "field decay(t = 50.002): 0.18949483737263706 / 0.18949483737263706 = 1.0\n", + "on time step 37791 (time=75.582), 0.000209809 s/step\n", + "field decay(t = 100.004): 1.517868453573768e-17 / 0.18949483737263706 = 8.010078135210174e-17\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000180514 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 = 0.0215817 s\n", + "-----------\n", + "on time step 17781 (time=35.562), 0.000224967 s/step\n", + "field decay(t = 50.002): 0.1894948373905043 / 0.1894948373905043 = 1.0\n", + "on time step 36146 (time=72.292), 0.000217812 s/step\n", + "field decay(t = 100.004): 1.48019127608089e-11 / 0.1894948373905043 = 7.811248562041633e-11\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "refl:, 0.8, 30, 0.24421641907449407\n", + "refl:, 0.784, 30, 0.24360093955278922\n", + "refl:, 0.7686274509803922, 30, 0.2429976016564938\n", + "refl:, 0.7538461538461539, 30, 0.24239413218573944\n", + "refl:, 0.739622641509434, 30, 0.24177998687342056\n", + "refl:, 0.7259259259259259, 30, 0.2411478814458524\n", + "refl:, 0.7127272727272727, 30, 0.24049865179188887\n", + "refl:, 0.7, 30, 0.23983250134820114\n", + "refl:, 0.6877192982456141, 30, 0.23915053786633636\n", + "refl:, 0.6758620689655173, 30, 0.2384576453300517\n", + "refl:, 0.664406779661017, 30, 0.2377517460238491\n", + "refl:, 0.6533333333333333, 30, 0.23703136208347433\n", + "refl:, 0.6426229508196721, 30, 0.2362966039197676\n", + "refl:, 0.632258064516129, 30, 0.23554724331990862\n", + "refl:, 0.6222222222222222, 30, 0.234782448251556\n", + "refl:, 0.6124999999999999, 30, 0.23400159338841844\n", + "refl:, 0.6030769230769231, 30, 0.2332039344066757\n", + "refl:, 0.593939393939394, 30, 0.23238908318526785\n", + "refl:, 0.5850746268656717, 30, 0.23155771127094135\n", + "refl:, 0.5764705882352942, 30, 0.23070992231742166\n", + "refl:, 0.5681159420289855, 30, 0.22984545822121927\n", + "refl:, 0.56, 30, 0.22896350395602233\n", + "refl:, 0.552112676056338, 30, 0.22806455199725\n", + "refl:, 0.5444444444444444, 30, 0.22714950183158236\n", + "refl:, 0.536986301369863, 30, 0.22621788128902362\n", + "refl:, 0.5297297297297298, 30, 0.22526837754028084\n", + "refl:, 0.5226666666666667, 30, 0.22430094941304654\n", + "refl:, 0.5157894736842105, 30, 0.22331660974578546\n", + "refl:, 0.509090909090909, 30, 0.2223152106928716\n", + "refl:, 0.5025641025641026, 30, 0.22129526922098985\n", + "refl:, 0.4962025316455696, 30, 0.2202561149480662\n", + "refl:, 0.49, 30, 0.21919847904389847\n", + "refl:, 0.4839506172839506, 30, 0.21812271396012425\n", + "refl:, 0.47804878048780486, 30, 0.21702786674336033\n", + "refl:, 0.47228915662650606, 30, 0.2159128597011861\n", + "refl:, 0.4666666666666667, 30, 0.21477758775110917\n", + "refl:, 0.4611764705882353, 30, 0.2136224006522148\n", + "refl:, 0.4558139534883721, 30, 0.21244704496865824\n", + "refl:, 0.4505747126436782, 30, 0.21125056638781006\n", + "refl:, 0.4454545454545454, 30, 0.2100322879751378\n", + "refl:, 0.44044943820224725, 30, 0.20879259807585807\n", + "refl:, 0.43555555555555553, 30, 0.2075320923986216\n", + "refl:, 0.4307692307692308, 30, 0.20625003649863047\n", + "refl:, 0.4260869565217391, 30, 0.20494496839731002\n", + "refl:, 0.421505376344086, 30, 0.20361711007494473\n", + "refl:, 0.41702127659574467, 30, 0.20226842596891553\n", + "refl:, 0.4126315789473684, 30, 0.20089903538573398\n", + "refl:, 0.4083333333333333, 30, 0.19950550975612025\n", + "refl:, 0.4041237113402062, 30, 0.19808546462539633\n", + "refl:, 0.4, 30, 0.19664308828503746\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000154284 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 = 0.00678781 s\n", + "-----------\n", + "on time step 18657 (time=37.314), 0.000214402 s/step\n", + "field decay(t = 50.002): 0.16933926312056236 / 0.16933926312056236 = 1.0\n", + "on time step 37949 (time=75.898), 0.000207347 s/step\n", + "field decay(t = 100.004): 1.2575510355119989e-17 / 0.16933926312056236 = 7.426222438541474e-17\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000156599 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 = 0.0180583 s\n", + "-----------\n", + "on time step 17981 (time=35.962), 0.000222459 s/step\n", + "field decay(t = 50.002): 0.16933924712178453 / 0.16933924712178453 = 1.0\n", + "on time step 36953 (time=73.906), 0.000210853 s/step\n", + "field decay(t = 100.004): 1.3708470006527105e-11 / 0.16933924712178453 = 8.095270434660855e-11\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "refl:, 0.8, 35, 0.22480324707261776\n", + "refl:, 0.784, 35, 0.2242289273149656\n", + "refl:, 0.7686274509803922, 35, 0.22365291835158363\n", + "refl:, 0.7538461538461539, 35, 0.22305349322877624\n", + "refl:, 0.739622641509434, 35, 0.2224376317753956\n", + "refl:, 0.7259259259259259, 35, 0.22180785324655725\n", + "refl:, 0.7127272727272727, 35, 0.22116315068807135\n", + "refl:, 0.7, 35, 0.22051008634386499\n", + "refl:, 0.6877192982456141, 35, 0.21984672944075373\n", + "refl:, 0.6758620689655173, 35, 0.21916955959907036\n", + "refl:, 0.664406779661017, 35, 0.2184780826996305\n", + "refl:, 0.6533333333333333, 35, 0.21777103948890367\n", + "refl:, 0.6426229508196721, 35, 0.2170493557254865\n", + "refl:, 0.632258064516129, 35, 0.21631263919849697\n", + "refl:, 0.6222222222222222, 35, 0.21555937258624308\n", + "refl:, 0.6124999999999999, 35, 0.21479000085015504\n", + "refl:, 0.6030769230769231, 35, 0.21400465403001961\n", + "refl:, 0.593939393939394, 35, 0.2132037273014299\n", + "refl:, 0.5850746268656717, 35, 0.21238753323129475\n", + "refl:, 0.5764705882352942, 35, 0.2115559971433431\n", + "refl:, 0.5681159420289855, 35, 0.21070912774214903\n", + "refl:, 0.56, 35, 0.20984637156833424\n", + "refl:, 0.552112676056338, 35, 0.20896820092695811\n", + "refl:, 0.5444444444444444, 35, 0.20807487323265844\n", + "refl:, 0.536986301369863, 35, 0.20716553842784746\n", + "refl:, 0.5297297297297298, 35, 0.20623898542947244\n", + "refl:, 0.5226666666666667, 35, 0.20529521504626091\n", + "refl:, 0.5157894736842105, 35, 0.20433540651345897\n", + "refl:, 0.509090909090909, 35, 0.20335904044265615\n", + "refl:, 0.5025641025641026, 35, 0.20236462727710636\n", + "refl:, 0.4962025316455696, 35, 0.20135136216589572\n", + "refl:, 0.49, 35, 0.20032042764571187\n", + "refl:, 0.4839506172839506, 35, 0.19927184354875485\n", + "refl:, 0.47804878048780486, 35, 0.19820465930712272\n", + "refl:, 0.47228915662650606, 35, 0.19711756369920136\n", + "refl:, 0.4666666666666667, 35, 0.196010991407721\n", + "refl:, 0.4611764705882353, 35, 0.19488509462057793\n", + "refl:, 0.4558139534883721, 35, 0.1937400269437345\n", + "refl:, 0.4505747126436782, 35, 0.19257433333916665\n", + "refl:, 0.4454545454545454, 35, 0.19138799802621484\n", + "refl:, 0.44044943820224725, 35, 0.19018196489143802\n", + "refl:, 0.43555555555555553, 35, 0.18895471069694567\n", + "refl:, 0.4307692307692308, 35, 0.18770789805074498\n", + "refl:, 0.4260869565217391, 35, 0.18643794982567657\n", + "refl:, 0.421505376344086, 35, 0.1851439967686107\n", + "refl:, 0.41702127659574467, 35, 0.1838297680187505\n", + "refl:, 0.4126315789473684, 35, 0.18248993271857503\n", + "refl:, 0.4083333333333333, 35, 0.18112780664565004\n", + "refl:, 0.4041237113402062, 35, 0.17973971855098006\n", + "refl:, 0.4, 35, 0.17833128965032224\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000148463 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 = 0.00784313 s\n", + "-----------\n", + "on time step 19076 (time=38.152), 0.000209704 s/step\n", + "field decay(t = 50.002): 0.14790864907196258 / 0.14790864907196258 = 1.0\n", + "on time step 37590 (time=75.18), 0.00021606 s/step\n", + "field decay(t = 100.004): 1.2790541929537606e-11 / 0.14790864907196258 = 8.647595667860216e-11\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000153032 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 = 0.0262595 s\n", + "-----------\n", + "on time step 17254 (time=34.508), 0.000231837 s/step\n", + "field decay(t = 50.002): 0.1479086137630578 / 0.1479086137630578 = 1.0\n", + "on time step 35545 (time=71.09), 0.000218693 s/step\n", + "field decay(t = 100.004): 5.060712221450255e-11 / 0.1479086137630578 = 3.421512846815847e-10\n", + "run 0 finished at t = 100.004 (50002 timesteps)\n", + "refl:, 0.8, 40, 0.2017586063136545\n", + "refl:, 0.784, 40, 0.20117817805385965\n", + "refl:, 0.7686274509803922, 40, 0.20060164822949297\n", + "refl:, 0.7538461538461539, 40, 0.20002479814481888\n", + "refl:, 0.739622641509434, 40, 0.19943570129867244\n", + "refl:, 0.7259259259259259, 40, 0.19882964252519644\n", + "refl:, 0.7127272727272727, 40, 0.19820886320514522\n", + "refl:, 0.7, 40, 0.19757555295399215\n", + "refl:, 0.6877192982456141, 40, 0.1969299214757624\n", + "refl:, 0.6758620689655173, 40, 0.19626980002530114\n", + "refl:, 0.664406779661017, 40, 0.19559404552526874\n", + "refl:, 0.6533333333333333, 40, 0.19490395810201686\n", + "refl:, 0.6426229508196721, 40, 0.19419993191145654\n", + "refl:, 0.632258064516129, 40, 0.19348049067382725\n", + "refl:, 0.6222222222222222, 40, 0.19274524912249003\n", + "refl:, 0.6124999999999999, 40, 0.1919958729567262\n", + "refl:, 0.6030769230769231, 40, 0.19123395263046447\n", + "refl:, 0.593939393939394, 40, 0.19045855279575113\n", + "refl:, 0.5850746268656717, 40, 0.18966856562408524\n", + "refl:, 0.5764705882352942, 40, 0.1888642898593234\n", + "refl:, 0.5681159420289855, 40, 0.18804630200996425\n", + "refl:, 0.56, 40, 0.18721377543692228\n", + "refl:, 0.552112676056338, 40, 0.18636576978538305\n", + "refl:, 0.5444444444444444, 40, 0.1855021229424816\n", + "refl:, 0.536986301369863, 40, 0.1846231595553309\n", + "refl:, 0.5297297297297298, 40, 0.18372817940351135\n", + "refl:, 0.5226666666666667, 40, 0.1828160480852349\n", + "refl:, 0.5157894736842105, 40, 0.18188701667124335\n", + "refl:, 0.509090909090909, 40, 0.18094176560577405\n", + "refl:, 0.5025641025641026, 40, 0.17997994424122088\n", + "refl:, 0.4962025316455696, 40, 0.1790001105952078\n", + "refl:, 0.49, 40, 0.1780018512609623\n", + "refl:, 0.4839506172839506, 40, 0.17698652424543304\n", + "refl:, 0.47804878048780486, 40, 0.17595488959790206\n", + "refl:, 0.47228915662650606, 40, 0.17490551180285582\n", + "refl:, 0.4666666666666667, 40, 0.17383683905647812\n", + "refl:, 0.4611764705882353, 40, 0.17274982383235662\n", + "refl:, 0.4558139534883721, 40, 0.17164604687544982\n", + "refl:, 0.4505747126436782, 40, 0.17052451781426345\n", + "refl:, 0.4454545454545454, 40, 0.16938331790637615\n", + "refl:, 0.44044943820224725, 40, 0.1682223832374324\n", + "refl:, 0.43555555555555553, 40, 0.167042992463954\n", + "refl:, 0.4307692307692308, 40, 0.16584353550236508\n", + "refl:, 0.4260869565217391, 40, 0.16462390370004149\n", + "refl:, 0.421505376344086, 40, 0.16338428964236099\n", + "refl:, 0.41702127659574467, 40, 0.1621253130295502\n", + "refl:, 0.4126315789473684, 40, 0.16084838418172945\n", + "refl:, 0.4083333333333333, 40, 0.15955458592740815\n", + "refl:, 0.4041237113402062, 40, 0.15823982222411875\n", + "refl:, 0.4, 40, 0.15689171357983653\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000145267 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 = 0.00782514 s\n", + "-----------\n", + "on time step 19084 (time=19.084), 0.000209606 s/step\n", + "on time step 38629 (time=38.629), 0.000204657 s/step\n", + "field decay(t = 50.001): 0.12589283219077943 / 0.12589283219077943 = 1.0\n", + "on time step 57973 (time=57.973), 0.000206787 s/step\n", + "on time step 76643 (time=76.643), 0.000214249 s/step\n", + "on time step 95549 (time=95.549), 0.000211574 s/step\n", + "field decay(t = 100.002): 6.8664398646595815e-18 / 0.12589283219077943 = 5.454194448699113e-17\n", + "run 0 finished at t = 100.002 (100002 timesteps)\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000161027 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 = 0.0195053 s\n", + "-----------\n", + "on time step 18174 (time=18.174), 0.000220101 s/step\n", + "on time step 37091 (time=37.091), 0.000211469 s/step\n", + "field decay(t = 50.001): 0.12589291511994 / 0.12589291511994 = 1.0\n", + "on time step 56595 (time=56.595), 0.000205091 s/step\n", + "on time step 75730 (time=75.73), 0.000209047 s/step\n", + "on time step 94715 (time=94.715), 0.000210693 s/step\n", + "field decay(t = 100.002): 3.0300239197362437e-12 / 0.12589291511994 = 2.4068264023034945e-11\n", + "run 0 finished at t = 100.002 (100002 timesteps)\n", + "refl:, 0.8, 45, 0.17490220794863126\n", + "refl:, 0.784, 45, 0.17433377135191452\n", + "refl:, 0.7686274509803922, 45, 0.17376853217774785\n", + "refl:, 0.7538461538461539, 45, 0.17320985238144976\n", + "refl:, 0.739622641509434, 45, 0.17264670260646717\n", + "refl:, 0.7259259259259259, 45, 0.172072578704743\n", + "refl:, 0.7127272727272727, 45, 0.17148289702813319\n", + "refl:, 0.7, 45, 0.17087641845832283\n", + "refl:, 0.6877192982456141, 45, 0.17025458472014135\n", + "refl:, 0.6758620689655173, 45, 0.16961692406481022\n", + "refl:, 0.664406779661017, 45, 0.1689635476380177\n", + "refl:, 0.6533333333333333, 45, 0.16829786443199785\n", + "refl:, 0.6426229508196721, 45, 0.16762222787675565\n", + "refl:, 0.632258064516129, 45, 0.16693478577418505\n", + "refl:, 0.6222222222222222, 45, 0.16623302001585677\n", + "refl:, 0.6124999999999999, 45, 0.16551762706826365\n", + "refl:, 0.6030769230769231, 45, 0.1647910179854295\n", + "refl:, 0.593939393939394, 45, 0.16405327045813023\n", + "refl:, 0.5850746268656717, 45, 0.1633015648395362\n", + "refl:, 0.5764705882352942, 45, 0.16253386419314395\n", + "refl:, 0.5681159420289855, 45, 0.16175137409603976\n", + "refl:, 0.56, 45, 0.16095605964964943\n", + "refl:, 0.552112676056338, 45, 0.16014709262208265\n", + "refl:, 0.5444444444444444, 45, 0.15932184557682105\n", + "refl:, 0.536986301369863, 45, 0.1584797899826377\n", + "refl:, 0.5297297297297298, 45, 0.15762299167686694\n", + "refl:, 0.5226666666666667, 45, 0.15675249873481273\n", + "refl:, 0.5157894736842105, 45, 0.15586656471132068\n", + "refl:, 0.509090909090909, 45, 0.15496350385509144\n", + "refl:, 0.5025641025641026, 45, 0.1540443796691992\n", + "refl:, 0.4962025316455696, 45, 0.1531111315733404\n", + "refl:, 0.49, 45, 0.15216326563829433\n", + "refl:, 0.4839506172839506, 45, 0.15119851527630854\n", + "refl:, 0.47804878048780486, 45, 0.15021636420269469\n", + "refl:, 0.47228915662650606, 45, 0.14921868861198098\n", + "refl:, 0.4666666666666667, 45, 0.14820642754380461\n", + "refl:, 0.4611764705882353, 45, 0.147177576429042\n", + "refl:, 0.4558139534883721, 45, 0.14612977013589654\n", + "refl:, 0.4505747126436782, 45, 0.14506355663711043\n", + "refl:, 0.4454545454545454, 45, 0.1439813369883703\n", + "refl:, 0.44044943820224725, 45, 0.1428835268230549\n", + "refl:, 0.43555555555555553, 45, 0.1417677690070384\n", + "refl:, 0.4307692307692308, 45, 0.14063258178786864\n", + "refl:, 0.4260869565217391, 45, 0.13948011048227352\n", + "refl:, 0.421505376344086, 45, 0.13831337343453576\n", + "refl:, 0.41702127659574467, 45, 0.1371311271563818\n", + "refl:, 0.4126315789473684, 45, 0.13592784826453094\n", + "refl:, 0.4083333333333333, 45, 0.1347000332695126\n", + "refl:, 0.4041237113402062, 45, 0.13344983001156094\n", + "refl:, 0.4, 45, 0.13217808847559934\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000144375 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 = 0.00987652 s\n", + "-----------\n", + "on time step 19107 (time=19.107), 0.000209349 s/step\n", + "on time step 38284 (time=38.284), 0.000208585 s/step\n", + "field decay(t = 50.001): 0.10389977739957125 / 0.10389977739957125 = 1.0\n", + "on time step 57635 (time=57.635), 0.000206716 s/step\n", + "on time step 76976 (time=76.976), 0.000206824 s/step\n", + "on time step 95998 (time=95.998), 0.000210298 s/step\n", + "field decay(t = 100.002): 5.620562833627336e-17 / 0.10389977739957125 = 5.409600457575696e-16\n", + "run 0 finished at t = 100.002 (100002 timesteps)\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000153142 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 = 0.0223738 s\n", + "-----------\n", + "on time step 18532 (time=18.532), 0.000215844 s/step\n", + "on time step 36831 (time=36.831), 0.000218593 s/step\n", + "field decay(t = 50.001): 0.10390016163905248 / 0.10390016163905248 = 1.0\n", + "on time step 55365 (time=55.365), 0.000215824 s/step\n", + "on time step 73991 (time=73.991), 0.000214791 s/step\n", + "on time step 92917 (time=92.917), 0.000211355 s/step\n", + "field decay(t = 100.002): 4.577513211008261e-13 / 0.10390016163905248 = 4.405684398172997e-12\n", + "run 0 finished at t = 100.002 (100002 timesteps)\n", + "refl:, 0.8, 50, 0.1441357885418365\n", + "refl:, 0.784, 50, 0.14361766670503187\n", + "refl:, 0.7686274509803922, 50, 0.14309801700715913\n", + "refl:, 0.7538461538461539, 50, 0.1425845419045143\n", + "refl:, 0.739622641509434, 50, 0.14206098994331326\n", + "refl:, 0.7259259259259259, 50, 0.14151748635748082\n", + "refl:, 0.7127272727272727, 50, 0.1409563206447606\n", + "refl:, 0.7, 50, 0.14038161343879071\n", + "refl:, 0.6877192982456141, 50, 0.13979825390886677\n", + "refl:, 0.6758620689655173, 50, 0.13920420769382347\n", + "refl:, 0.664406779661017, 50, 0.1385944969798535\n", + "refl:, 0.6533333333333333, 50, 0.13797096026799807\n", + "refl:, 0.6426229508196721, 50, 0.13733872718613513\n", + "refl:, 0.632258064516129, 50, 0.13669995477630967\n", + "refl:, 0.6222222222222222, 50, 0.13605075313976867\n", + "refl:, 0.6124999999999999, 50, 0.13538498717074862\n", + "refl:, 0.6030769230769231, 50, 0.13470238213417188\n", + "refl:, 0.593939393939394, 50, 0.13400766061997843\n", + "refl:, 0.5850746268656717, 50, 0.13330369186321053\n", + "refl:, 0.5764705882352942, 50, 0.1325875580009524\n", + "refl:, 0.5681159420289855, 50, 0.13185405887300286\n", + "refl:, 0.56, 50, 0.13110313447908092\n", + "refl:, 0.552112676056338, 50, 0.13033981743854497\n", + "refl:, 0.5444444444444444, 50, 0.12956790164036044\n", + "refl:, 0.536986301369863, 50, 0.12878516922359085\n", + "refl:, 0.5297297297297298, 50, 0.12798660347134214\n", + "refl:, 0.5226666666666667, 50, 0.1271714718386089\n", + "refl:, 0.5157894736842105, 50, 0.12634402724393995\n", + "refl:, 0.509090909090909, 50, 0.12550795416637034\n", + "refl:, 0.5025641025641026, 50, 0.12466107820288364\n", + "refl:, 0.4962025316455696, 50, 0.12379855600701464\n", + "refl:, 0.49, 50, 0.12291880411873447\n", + "refl:, 0.4839506172839506, 50, 0.12202547943427489\n", + "refl:, 0.47804878048780486, 50, 0.12112182241286878\n", + "refl:, 0.47228915662650606, 50, 0.1202063674993619\n", + "refl:, 0.4666666666666667, 50, 0.11927404755647308\n", + "refl:, 0.4611764705882353, 50, 0.11832326803981534\n", + "refl:, 0.4558139534883721, 50, 0.11735713020534348\n", + "refl:, 0.4505747126436782, 50, 0.11637900953999546\n", + "refl:, 0.4454545454545454, 50, 0.11538727691746767\n", + "refl:, 0.44044943820224725, 50, 0.11437786424723231\n", + "refl:, 0.43555555555555553, 50, 0.11334908234203207\n", + "refl:, 0.4307692307692308, 50, 0.11230438668343848\n", + "refl:, 0.4260869565217391, 50, 0.1112478895256101\n", + "refl:, 0.421505376344086, 50, 0.11017853302965806\n", + "refl:, 0.41702127659574467, 50, 0.1090910554310316\n", + "refl:, 0.4126315789473684, 50, 0.10798247634050744\n", + "refl:, 0.4083333333333333, 50, 0.1068536843048533\n", + "refl:, 0.4041237113402062, 50, 0.10570059169845158\n", + "refl:, 0.4, 50, 0.10451879528113295\n" + ] + } + ], + "source": [ + "theta_in = np.arange(0, 55, 5)\n", + "wvl = np.empty(nfreq)\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", + " wvl, thetas[:, j], Rmeep[:, j] = planar_reflectance(theta_in[j])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Using the original function requires a wider range of input angles in order to fill more of the space, due to the frequency dependence of the angle. " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000157701 s\n", + "Working in 1D dimensions.\n", + "Computational cell is 0 x 0 x 12 with resolution 50\n", + "time for set_epsilon = 0.000531193 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 = 9.6404e-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 = 0.000504612 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, 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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 = 0.000167339 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 = 0.0075487 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 = 0.000155307 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 = 0.0154834 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", + "refl:, 0.1089446784345727, 0.7538461538461539, 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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 = 0.0186212 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, 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0.2170602220836629, 0.4, 4.980925321928872, 0.24385884403865477\n", + "-----------\n", + "Initializing structure...\n", + "time for choose_chunkdivision = 0.000175915 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 = 0.00723663 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 = 0.000224208 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 = 0.0241591 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 = 0.000148863 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 = 0.00692405 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 = 0.000154004 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 = 0.0192281 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 = 0.000200993 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 = 0.00694266 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 = 0.000233896 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 = 0.0189372 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, 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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 = 0.00026274 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 = 0.00692336 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 = 0.000154975 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 = 0.0191058 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, 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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 = 0.000146089 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 = 0.0101679 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 = 0.000383431 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 = 0.0222895 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", + 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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 = 0.000237853 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 = 0.00819875 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 = 0.000170154 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 = 0.0210803 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, 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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 = 0.000146328 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 = 0.00878567 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 = 0.000167259 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 = 0.0157386 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", + 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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 = 0.000152601 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 = 0.00756879 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 = 0.000154434 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 = 0.0204244 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, 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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 = 0.000147621 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 = 0.00734905 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 = 0.000196184 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 = 0.0180538 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, 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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 = 0.000154154 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 = 0.00756254 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 = 0.000157691 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 = 0.0205829 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 = 0.000228616 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 = 0.00747033 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 = 0.000159334 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 = 0.01799 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:, 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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 = 0.000145978 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 = 0.00789347 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 = 0.000202426 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 = 0.0310265 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, 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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 = 0.000148583 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 = 0.00694508 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 = 0.000286416 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 = 0.0233328 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, 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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 = 0.000153011 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 = 0.00805109 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 = 0.00016239 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 = 0.0172302 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", + "refl:, 1.23100969126526, 0.7259259259259259, 63.331955818023665, 0.04791694905496988\n", + "refl:, 1.23100969126526, 0.7127272727272727, 61.32721657609733, 0.06192830286716911\n", + "refl:, 1.23100969126526, 0.7, 59.508764013939604, 0.07458277694558078\n", + "refl:, 1.23100969126526, 0.6877192982456141, 57.84259890532987, 0.08617714917468623\n", + "refl:, 1.23100969126526, 0.6758620689655173, 56.30398980710504, 0.0966379797155269\n", + "refl:, 1.23100969126526, 0.664406779661017, 54.87424701948212, 0.10612489602225829\n", + "refl:, 1.23100969126526, 0.6533333333333333, 53.53881754577338, 0.11477448569944776\n", + "refl:, 1.23100969126526, 0.6426229508196721, 52.2860932123638, 0.1226196975060367\n", + "refl:, 1.23100969126526, 0.632258064516129, 51.10662968356778, 0.12979595071970462\n", + "refl:, 1.23100969126526, 0.6222222222222222, 49.992614952243095, 0.1363423839815458\n", + "refl:, 1.23100969126526, 0.6124999999999999, 48.937495982303304, 0.14232506775291698\n", + "refl:, 1.23100969126526, 0.6030769230769231, 47.93570930843333, 0.14779669116407043\n", + "refl:, 1.23100969126526, 0.593939393939394, 46.98248211140486, 0.15279783449569376\n", + "refl:, 1.23100969126526, 0.5850746268656717, 46.07368235996428, 0.1573761848030311\n", + "refl:, 1.23100969126526, 0.5764705882352942, 45.205703916101704, 0.16157162995599855\n", + "refl:, 1.23100969126526, 0.5681159420289855, 44.37537706820699, 0.16542676815817645\n", + "refl:, 1.23100969126526, 0.56, 43.57989789517631, 0.16896454842958672\n", + "refl:, 1.23100969126526, 0.552112676056338, 42.81677180338089, 0.1722206134003931\n", + "refl:, 1.23100969126526, 0.5444444444444444, 42.083767886770914, 0.17520135452911917\n", + "refl:, 1.23100969126526, 0.536986301369863, 41.378881661291835, 0.17793593217612066\n", + "refl:, 1.23100969126526, 0.5297297297297298, 40.70030435652892, 0.1804419317536035\n", + "refl:, 1.23100969126526, 0.5226666666666667, 40.046397397863686, 0.18273421151574976\n", + "refl:, 1.23100969126526, 0.5157894736842105, 39.41567103836258, 0.18483834118872827\n", + "refl:, 1.23100969126526, 0.509090909090909, 38.806766338771496, 0.18675576413095382\n", + "refl:, 1.23100969126526, 0.5025641025641026, 38.218439871701385, 0.18849963174434395\n", + "refl:, 1.23100969126526, 0.4962025316455696, 37.64955065969264, 0.19008108230487103\n", + "refl:, 1.23100969126526, 0.49, 37.099048958377544, 0.19150758216597197\n", + "refl:, 1.23100969126526, 0.4839506172839506, 36.56596657389412, 0.19279776266416668\n", + "refl:, 1.23100969126526, 0.47804878048780486, 36.049408464086156, 0.19395439242202947\n", + "refl:, 1.23100969126526, 0.47228915662650606, 35.54854542021205, 0.19498180503114848\n", + "refl:, 1.23100969126526, 0.4666666666666667, 35.062607663064846, 0.19588433555808407\n", + "refl:, 1.23100969126526, 0.4611764705882353, 34.59087921692149, 0.19666557505940196\n", + "refl:, 1.23100969126526, 0.4558139534883721, 34.13269294834013, 0.19734832119524592\n", + "refl:, 1.23100969126526, 0.4505747126436782, 33.6874261758209, 0.19793121915708817\n", + "refl:, 1.23100969126526, 0.4454545454545454, 33.25449677173539, 0.19840657303015277\n", + "refl:, 1.23100969126526, 0.44044943820224725, 32.83335969046958, 0.19877980002307316\n", + "refl:, 1.23100969126526, 0.43555555555555553, 32.42350386700291, 0.19904606256565613\n", + "refl:, 1.23100969126526, 0.4307692307692308, 32.0244494386133, 0.1992480800037741\n", + "refl:, 1.23100969126526, 0.4260869565217391, 31.63574524940934, 0.19939085390804745\n", + "refl:, 1.23100969126526, 0.421505376344086, 31.2569666032255, 0.19942098648283285\n", + "refl:, 1.23100969126526, 0.41702127659574467, 30.887713235292672, 0.19934811719121265\n", + "refl:, 1.23100969126526, 0.4126315789473684, 30.527607477190394, 0.1991752884538809\n", + "refl:, 1.23100969126526, 0.4083333333333333, 30.176292593038497, 0.19904014318467667\n", + "refl:, 1.23100969126526, 0.4041237113402062, 29.83343126780691, 0.19894516024468498\n", + "refl:, 1.23100969126526, 0.4, 29.498704231103652, 0.19854708072325522\n" + ] + } + ], + "source": [ + "theta_in_orig = np.arange(0, 85, 5)\n", + "wvl_orig = np.empty(nfreq)\n", + "kxs_orig = np.empty((nfreq, theta_in_orig.size))\n", + "thetas_orig = np.empty((nfreq, theta_in_orig.size))\n", + "Rmeep_orig = np.empty((nfreq, theta_in_orig.size))\n", + "\n", + "for j in range(theta_in_orig.size):\n", + " kxs_orig[:, j], wvl_orig, thetas_orig[:, j], Rmeep_orig[:, j] = planar_reflectance_original(theta_in_orig[j])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The reflectance spectra from the 2 different functions are compared below at fixed wavelengths. The two functions agree closely." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for i in range(0,len(wvl),10):\n", + " lbl = \"bfast, wvl = %.2f μm\"%wvl[i]\n", + " plt.plot(thetas[i,:],Rmeep[i,:],'x',label=lbl)\n", + "for i in range(0,len(wvl),10):\n", + " lbl = \"original, wvl = %.2f μm\"%wvl[i]\n", + " plt.plot(thetas_orig[i,:],Rmeep_orig[i,:],label=lbl)\n", + "plt.xlabel(\"angle of incident planewave (degrees)\")\n", + "plt.ylabel(\"reflectance (μm)\")\n", + "plt.axis([theta_in.min(),theta_in.max(), Rmeep.min(), Rmeep.max()])\n", + "plt.legend()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The reflectance spectrum for all wavelengths is shown for both functions below. The two plots give the same values however, due to the frequency dependence of the original approach, some of the space is left empty." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# 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))\n", + "\n", + "plt.figure(dpi=200)\n", + "plt.pcolormesh(\n", + " thetas, wvls, Rmeep, cmap=\"inferno\", shading=\"gouraud\", vmin=0, vmax=Rmeep.max()\n", + ")\n", + "plt.axis([thetas.min(), thetas.max(), wvl_min, wvl_max])\n", + "plt.xlabel(\"angle of incident planewave (degrees)\")\n", + "plt.ylabel(\"wavelength (μm)\")\n", + "plt.title(\"reflectance (bfast)\")\n", + "cbar = plt.colorbar()\n", + "cbar.set_ticks([t for t in np.linspace(0, 0.4, 5)])\n", + "cbar.set_ticklabels([\"{:.1f}\".format(t) for t in np.linspace(0, 0.4, 5)])" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "wvls_orig = np.transpose(np.matlib.repmat(wvl_orig, theta_in_orig.size, 1))\n", + "\n", + "plt.figure(dpi=200)\n", + "plt.pcolormesh(\n", + " thetas_orig, wvls_orig, Rmeep_orig, cmap=\"inferno\", shading=\"gouraud\", vmin=0, vmax=Rmeep_orig.max()\n", + ")\n", + "plt.axis([thetas.min(), thetas.max(), wvl_min, wvl_max])\n", + "plt.xlabel(\"angle of incident planewave (degrees)\")\n", + "plt.ylabel(\"wavelength (μm)\")\n", + "plt.title(\"reflectance (original)\")\n", + "cbar = plt.colorbar()\n", + "cbar.set_ticks([t for t in np.linspace(0, 0.4, 5)])\n", + "cbar.set_ticklabels([\"{:.1f}\".format(t) for t in np.linspace(0, 0.4, 5)])" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/python/simulation.py b/python/simulation.py index ee1a731ed..1abd3c995 100644 --- a/python/simulation.py +++ b/python/simulation.py @@ -1230,6 +1230,8 @@ def __init__( force_complex_fields: bool = False, default_material: Medium = mp.Medium(), m: float = 0, + need_bfast: bool = False, + bfast_k_bar: Vector3Type = (0, 0, 0), k_point: Union[Vector3Type, bool] = False, kz_2d: str = "complex", extra_materials: Optional[List[Medium]] = None, @@ -1527,6 +1529,8 @@ def __init__( self.last_eps_filename = "" self.output_h5_hook = lambda fname: False self.interactive = False + self.need_bfast = need_bfast + self.bfast_k_bar = bfast_k_bar self.is_cylindrical = False self.material_function = material_function self.epsilon_func = epsilon_func @@ -2475,6 +2479,8 @@ def init_sim(self): not self.accurate_fields_near_cylorigin, self.loop_tile_base_db, self.loop_tile_base_eh, + self.need_bfast, + self.bfast_k_bar, ) if self.force_all_components and self.dimensions != 1: diff --git a/src/Makefile.am b/src/Makefile.am index 3196a5e79..249cfbb08 100644 --- a/src/Makefile.am +++ b/src/Makefile.am @@ -34,6 +34,6 @@ sphere-quad.h: (echo $(PRELUDE); echo; $(SPHERE_QUAD)) > $@ step_generic_stride1.cpp: step_generic.cpp - (echo $(PRELUDE); echo; sed 's/LOOP_OVER/S1LOOP_OVER/g' $(top_srcdir)/src/step_generic.cpp | sed 's/step_curl/step_curl_stride1/' | sed 's/step_update_EDHB/step_update_EDHB_stride1/' | sed 's/step_beta/step_beta_stride1/') > $@ + (echo $(PRELUDE); echo; sed 's/LOOP_OVER/S1LOOP_OVER/g' $(top_srcdir)/src/step_generic.cpp | sed 's/step_curl/step_curl_stride1/' | sed 's/step_update_EDHB/step_update_EDHB_stride1/' | sed 's/step_beta/step_beta_stride1/'| sed 's/step_bfast/step_bfast_stride1/') > $@ MAINTAINERCLEANFILES = $(BUILT_SOURCES) diff --git a/src/cw_fields.cpp b/src/cw_fields.cpp index d40b8cc98..141df5fed 100644 --- a/src/cw_fields.cpp +++ b/src/cw_fields.cpp @@ -35,6 +35,7 @@ static void fields_to_array(const fields &f, complex *x) { COPY_FROM_FIELD(f[c]); COPY_FROM_FIELD(f_u[c]); COPY_FROM_FIELD(f_cond[c]); + COPY_FROM_FIELD(f_bfast[c]); component c2 = field_type_component(is_D(c) ? E_stuff : H_stuff, c); COPY_FROM_FIELD(f_w[c2]); if (f.chunks[i]->f_w[c2][0]) COPY_FROM_FIELD(f[c2]); @@ -58,6 +59,7 @@ static void array_to_fields(const complex *x, fields &f) { COPY_TO_FIELD(f[c]); COPY_TO_FIELD(f_u[c]); COPY_TO_FIELD(f_cond[c]); + COPY_TO_FIELD(f_bfast[c]); component c2 = field_type_component(is_D(c) ? E_stuff : H_stuff, c); COPY_TO_FIELD(f_w[c2]); if (f.chunks[i]->f_w[c2][0]) COPY_TO_FIELD(f[c2]); @@ -162,7 +164,7 @@ bool fields::solve_cw(double tol, int maxiters, complex frequency, int L problems getting that working) */ N += 2 * chunks[i]->gv.nowned(c) * (1 + (chunks[i]->f_u[c][0] != NULL) + (chunks[i]->f_w[c2][0] != NULL) * 2 + - (chunks[i]->f_cond[c][0] != NULL)); + (chunks[i]->f_cond[c][0] != NULL) + (chunks[i]->f_bfast[c][0] != NULL)); } } } diff --git a/src/energy_and_flux.cpp b/src/energy_and_flux.cpp index 8e5bb0355..160d13115 100644 --- a/src/energy_and_flux.cpp +++ b/src/energy_and_flux.cpp @@ -110,6 +110,7 @@ void fields_chunk::backup_component(component c) { BACKUP(f_u); BACKUP(f_w); BACKUP(f_cond); + BACKUP(f_bfast); #undef BACKUP } @@ -126,6 +127,7 @@ void fields_chunk::restore_component(component c) { RESTORE(f_u); RESTORE(f_w); RESTORE(f_cond); + RESTORE(f_bfast); #undef RESTORE } diff --git a/src/fields.cpp b/src/fields.cpp index 9a5ae2b96..93d79fa17 100644 --- a/src/fields.cpp +++ b/src/fields.cpp @@ -30,10 +30,11 @@ using namespace std; namespace meep { fields::fields(structure *s, double m, double beta, bool zero_fields_near_cylorigin, - int loop_tile_base_db, int loop_tile_base_eh) + int loop_tile_base_db, int loop_tile_base_eh, bool need_bfast, + std::vector bfast_k_bar) : S(s->S), gv(s->gv), user_volume(s->user_volume), v(s->v), m(m), beta(beta), loop_tile_base_db(loop_tile_base_db), loop_tile_base_eh(loop_tile_base_eh), - working_on(×_spent) { + working_on(×_spent), need_bfast(need_bfast), bfast_k_bar(bfast_k_bar) { shared_chunks = s->shared_chunks; components_allocated = false; synchronized_magnetic_fields = 0; @@ -60,7 +61,7 @@ fields::fields(structure *s, double m, double beta, bool zero_fields_near_cylori chunks = new fields_chunk_ptr[num_chunks]; for (int i = 0; i < num_chunks; i++) chunks[i] = new fields_chunk(s->chunks[i], outdir, m, beta, zero_fields_near_cylorigin, i, - loop_tile_base_db); + loop_tile_base_db, need_bfast, bfast_k_bar); FOR_FIELD_TYPES(ft) { typedef realnum *realnum_ptr; comm_blocks[ft] = new realnum_ptr[num_chunks * num_chunks]; @@ -93,6 +94,8 @@ fields::fields(const fields &thef) outdir = new char[strlen(thef.outdir) + 1]; strcpy(outdir, thef.outdir); m = thef.m; + need_bfast = thef.need_bfast; + bfast_k_bar = thef.bfast_k_bar; beta = thef.beta; phasein_time = thef.phasein_time; for (int d = 0; d < 5; d++) { @@ -171,12 +174,14 @@ fields_chunk::~fields_chunk() { delete[] f_u[c][cmp]; delete[] f_w[c][cmp]; delete[] f_cond[c][cmp]; + delete[] f_bfast[c][cmp]; delete[] f_minus_p[c][cmp]; delete[] f_w_prev[c][cmp]; delete[] f_backup[c][cmp]; delete[] f_u_backup[c][cmp]; delete[] f_w_backup[c][cmp]; delete[] f_cond_backup[c][cmp]; + delete[] f_bfast_backup[c][cmp]; } delete[] f_rderiv_int; while (dft_chunks) { @@ -237,9 +242,10 @@ void check_tiles(grid_volume gv, const std::vector &gvs) { } fields_chunk::fields_chunk(structure_chunk *the_s, const char *od, double m, double beta, - bool zero_fields_near_cylorigin, int chunkidx, int loop_tile_base_db) + bool zero_fields_near_cylorigin, int chunkidx, int loop_tile_base_db, + bool need_bfast, std::vector bfast_k_bar) : gv(the_s->gv), v(the_s->v), m(m), zero_fields_near_cylorigin(zero_fields_near_cylorigin), - beta(beta) { + beta(beta), need_bfast(need_bfast), bfast_k_bar(bfast_k_bar) { s = the_s; chunk_idx = chunkidx; s->refcount++; @@ -278,12 +284,14 @@ fields_chunk::fields_chunk(structure_chunk *the_s, const char *od, double m, dou f_u[c][cmp] = NULL; f_w[c][cmp] = NULL; f_cond[c][cmp] = NULL; + f_bfast[c][cmp] = NULL; f_minus_p[c][cmp] = NULL; f_w_prev[c][cmp] = NULL; f_backup[c][cmp] = NULL; f_u_backup[c][cmp] = NULL; f_w_backup[c][cmp] = NULL; f_cond_backup[c][cmp] = NULL; + f_bfast_backup[c][cmp] = NULL; } f_rderiv_int = NULL; FOR_FIELD_TYPES(ft) { @@ -299,6 +307,8 @@ fields_chunk::fields_chunk(const fields_chunk &thef, int chunkidx) : gv(thef.gv) s->refcount++; outdir = thef.outdir; m = thef.m; + need_bfast = thef.need_bfast; + bfast_k_bar = thef.bfast_k_bar; zero_fields_near_cylorigin = thef.zero_fields_near_cylorigin; beta = thef.beta; new_s = thef.new_s; @@ -333,10 +343,12 @@ fields_chunk::fields_chunk(const fields_chunk &thef, int chunkidx) : gv(thef.gv) f_u[c][cmp] = NULL; f_w[c][cmp] = NULL; f_cond[c][cmp] = NULL; + f_bfast[c][cmp] = NULL; f_backup[c][cmp] = NULL; f_u_backup[c][cmp] = NULL; f_w_backup[c][cmp] = NULL; f_cond_backup[c][cmp] = NULL; + f_bfast_backup[c][cmp] = NULL; } FOR_COMPONENTS(c) DOCMP { if (!is_magnetic(c) && thef.f[c][cmp]) { @@ -355,6 +367,10 @@ fields_chunk::fields_chunk(const fields_chunk &thef, int chunkidx) : gv(thef.gv) f_cond[c][cmp] = new realnum[gv.ntot()]; memcpy(f_cond[c][cmp], thef.f_cond[c][cmp], sizeof(realnum) * gv.ntot()); } + if (thef.f_bfast[c][cmp]) { + f_bfast[c][cmp] = new realnum[gv.ntot()]; + memcpy(f_bfast[c][cmp], thef.f_bfast[c][cmp], sizeof(realnum) * gv.ntot()); + } } FOR_MAGNETIC_COMPONENTS(c) DOCMP { if (thef.f[c][cmp] == thef.f[c - Hx + Bx][cmp]) @@ -617,10 +633,12 @@ void fields_chunk::zero_fields() { ZERO(f_u[c][cmp]); ZERO(f_w[c][cmp]); ZERO(f_cond[c][cmp]); + ZERO(f_bfast[c][cmp]); ZERO(f_backup[c][cmp]); ZERO(f_u_backup[c][cmp]); ZERO(f_w_backup[c][cmp]); ZERO(f_cond_backup[c][cmp]); + ZERO(f_bfast_backup[c][cmp]); #undef ZERO } if (is_mine()) FOR_FIELD_TYPES(ft) { diff --git a/src/fields_dump.cpp b/src/fields_dump.cpp index 996f0f108..7d6001f87 100644 --- a/src/fields_dump.cpp +++ b/src/fields_dump.cpp @@ -127,6 +127,9 @@ void fields::dump(const char *filename, bool single_parallel_file) { [](fields_chunk *chunk, int c, int d) { return &(chunk->f_w[c][d]); }); dump_fields_chunk_field(&file, single_parallel_file, "f_cond", [](fields_chunk *chunk, int c, int d) { return &(chunk->f_cond[c][d]); }); + dump_fields_chunk_field( + &file, single_parallel_file, "f_bfast", + [](fields_chunk *chunk, int c, int d) { return &(chunk->f_bfast[c][d]); }); dump_fields_chunk_field( &file, single_parallel_file, "f_w_prev", [](fields_chunk *chunk, int c, int d) { return &(chunk->f_w_prev[c][d]); }); @@ -257,6 +260,9 @@ void fields::load(const char *filename, bool single_parallel_file) { [](fields_chunk *chunk, int c, int d) { return &(chunk->f_w[c][d]); }); load_fields_chunk_field(&file, single_parallel_file, "f_cond", [](fields_chunk *chunk, int c, int d) { return &(chunk->f_cond[c][d]); }); + load_fields_chunk_field( + &file, single_parallel_file, "f_bfast", + [](fields_chunk *chunk, int c, int d) { return &(chunk->f_bfast[c][d]); }); load_fields_chunk_field( &file, single_parallel_file, "f_w_prev", [](fields_chunk *chunk, int c, int d) { return &(chunk->f_w_prev[c][d]); }); diff --git a/src/meep.hpp b/src/meep.hpp index cd2e01698..8fc10fc5b 100644 --- a/src/meep.hpp +++ b/src/meep.hpp @@ -1465,6 +1465,8 @@ class fields_chunk { realnum *f_w[NUM_FIELD_COMPONENTS][2]; // E/H integrated from these realnum *f_cond[NUM_FIELD_COMPONENTS][2]; // aux field for PML+conductivity + realnum *f_bfast[NUM_FIELD_COMPONENTS][2]; + /* sometimes, to synchronize the E and H fields, e.g. for computing flux at a given time, we need to timestep H by 1/2; in this case we save backup copies of (some of) the fields to resume timestepping */ @@ -1473,6 +1475,7 @@ class fields_chunk { realnum *f_w_backup[NUM_FIELD_COMPONENTS][2]; realnum *f_cond_backup[NUM_FIELD_COMPONENTS][2]; + realnum *f_bfast_backup[NUM_FIELD_COMPONENTS][2]; // W (or E/H) field from prev. timestep, only stored if needed by update_pols realnum *f_w_prev[NUM_FIELD_COMPONENTS][2]; @@ -1499,6 +1502,8 @@ class fields_chunk { volume v; double m; // angular dependence in cyl. coords bool zero_fields_near_cylorigin; // fields=0 m pixels near r=0 for stability + bool need_bfast; + std::vector bfast_k_bar; double beta; int is_real; std::vector sources[NUM_FIELD_TYPES]; @@ -1508,7 +1513,8 @@ class fields_chunk { int chunk_idx; fields_chunk(structure_chunk *, const char *outdir, double m, double beta, - bool zero_fields_near_cylorigin, int chunkidx, int loop_tile_base_db); + bool zero_fields_near_cylorigin, int chunkidx, int loop_tile_base_db, + bool need_bfast, std::vector bfast_k_bar); fields_chunk(const fields_chunk &, int chunkidx); ~fields_chunk(); @@ -1736,6 +1742,8 @@ class fields { grid_volume gv, user_volume; volume v; double m; + bool need_bfast; + std::vector bfast_k_bar; double beta; int t, phasein_time, is_real; std::complex k[5], eikna[5]; @@ -1747,7 +1755,8 @@ class fields { // fields.cpp methods: fields(structure *, double m = 0, double beta = 0, bool zero_fields_near_cylorigin = true, - int loop_tile_base_db = 0, int loop_tile_base_eh = 0); + int loop_tile_base_db = 0, int loop_tile_base_eh = 0, bool need_bfast = false, + std::vector bfast_k_bar = {0, 0, 0}); fields(const fields &); ~fields(); bool equal_layout(const fields &f) const; diff --git a/src/meep_internals.hpp b/src/meep_internals.hpp index 939f6a1b6..99b9eec48 100644 --- a/src/meep_internals.hpp +++ b/src/meep_internals.hpp @@ -104,6 +104,14 @@ void step_beta(realnum *f, component c, const realnum *g, const grid_volume &gv, const ivec ie, realnum betadt, direction dsig, const realnum *siginv, realnum *fu, direction dsigu, const realnum *siginvu, const realnum *cndinv, realnum *fcnd); +void step_bfast(realnum *f, component c, const realnum *g1, const realnum *g2, ptrdiff_t s1, + ptrdiff_t s2, // strides for g1/g2 shift + const grid_volume &gv, const ivec is, const ivec ie, realnum dtdx, direction dsig, + const realnum *sig, const realnum *kap, const realnum *siginv, realnum *fu, + direction dsigu, const realnum *sigu, const realnum *kapu, const realnum *siginvu, + realnum dt, const realnum *cnd, const realnum *cndinv, realnum *fcnd, realnum *F, + realnum k1, realnum k2); + // functions in step_generic_stride1.cpp, generated from step_generic.cpp: void step_curl_stride1(realnum *f, component c, const realnum *g1, const realnum *g2, ptrdiff_t s1, @@ -126,6 +134,14 @@ void step_beta_stride1(realnum *f, component c, const realnum *g, const grid_vol const realnum *siginv, realnum *fu, direction dsigu, const realnum *siginvu, const realnum *cndinv, realnum *fcnd); +void step_bfast_stride1(realnum *f, component c, const realnum *g1, const realnum *g2, ptrdiff_t s1, + ptrdiff_t s2, // strides for g1/g2 shift + const grid_volume &gv, const ivec is, const ivec ie, realnum dtdx, + direction dsig, const realnum *sig, const realnum *kap, + const realnum *siginv, realnum *fu, direction dsigu, const realnum *sigu, + const realnum *kapu, const realnum *siginvu, realnum dt, const realnum *cnd, + const realnum *cndinv, realnum *fcnd, realnum *F, realnum k1, realnum k2); + /* macro wrappers around time-stepping functions: for performance reasons, if the inner loop is stride-1 then we use the stride-1 versions, which allow gcc (and possibly other compilers) to do additional @@ -162,6 +178,17 @@ void step_beta_stride1(realnum *f, component c, const realnum *g, const grid_vol step_beta(f, c, g, gv, is, ie, betadt, dsig, siginv, fu, dsigu, siginvu, cndinv, fcnd); \ } while (0) +#define STEP_BFAST(f, c, g1, g2, s1, s2, gv, is, ie, dtdx, dsig, sig, kap, siginv, fu, dsigu, \ + sigu, kapu, siginvu, dt, cnd, cndinv, fcnd, F, k1, k2) \ + do { \ + if (LOOPS_ARE_STRIDE1(gv)) \ + step_bfast_stride1(f, c, g1, g2, s1, s2, gv, is, ie, dtdx, dsig, sig, kap, siginv, fu, \ + dsigu, sigu, kapu, siginvu, dt, cnd, cndinv, fcnd, F, k1, k2); \ + else \ + step_bfast(f, c, g1, g2, s1, s2, gv, is, ie, dtdx, dsig, sig, kap, siginv, fu, dsigu, sigu, \ + kapu, siginvu, dt, cnd, cndinv, fcnd, F, k1, k2); \ + } while (0) + // analytical Green's functions from near2far.cpp, which we might want to expose someday void green3d(std::complex *EH, const vec &x, double freq, double eps, double mu, const vec &x0, component c0, std::complex f0); diff --git a/src/step_db.cpp b/src/step_db.cpp index e9a08300d..21b227ffb 100644 --- a/src/step_db.cpp +++ b/src/step_db.cpp @@ -72,6 +72,10 @@ bool fields_chunk::step_db(field_type ft) { memcpy(f_u[cc][cmp], the_f, gv.ntot() * sizeof(realnum)); allocated_u = true; } + if (need_bfast && !f_bfast[cc][cmp]) { + f_bfast[cc][cmp] = new realnum[gv.ntot()]; + memset(f_bfast[cc][cmp], 0, sizeof(realnum) * gv.ntot()); + } if (ft == D_stuff) { // strides are opposite sign for H curl stride_p = -stride_p; @@ -120,6 +124,20 @@ bool fields_chunk::step_db(field_type ft) { sub_gv.big_corner(), Courant, dsig, s->sig[dsig], s->kap[dsig], s->siginv[dsig], f_u[cc][cmp], dsigu, s->sig[dsigu], s->kap[dsigu], s->siginv[dsigu], dt, s->conductivity[cc][d_c], s->condinv[cc][d_c], f_cond[cc][cmp]); + + if (need_bfast) { + realnum k1 = have_m ? bfast_k_bar[component_index(c_m)] : 0; // puts k1 in direction of g2 + realnum k2 = have_p ? bfast_k_bar[component_index(c_p)] : 0; // puts k2 in direction of g1 + if (ft == D_stuff) { + k1 = -k1; + k2 = -k2; + } + STEP_BFAST(the_f, cc, f_p, f_m, stride_p, stride_m, gv, sub_gv.little_owned_corner0(cc), + sub_gv.big_corner(), Courant, dsig, s->sig[dsig], s->kap[dsig], + s->siginv[dsig], f_u[cc][cmp], dsigu, s->sig[dsigu], s->kap[dsigu], + s->siginv[dsigu], dt, s->conductivity[cc][d_c], s->condinv[cc][d_c], + f_cond[cc][cmp], f_bfast[cc][cmp], k1, k2); + } } } } diff --git a/src/step_generic.cpp b/src/step_generic.cpp index 60c27b354..94b6b90ff 100644 --- a/src/step_generic.cpp +++ b/src/step_generic.cpp @@ -331,6 +331,206 @@ void step_beta(RPR f, component c, const RPR g, const grid_volume &gv, const ive } } } +// allows fixed angle broadband simulations +void step_bfast(RPR f, component c, const RPR g1, const RPR g2, ptrdiff_t s1, + ptrdiff_t s2, // strides for g1/g2 shift + const grid_volume &gv, const ivec is, const ivec ie, realnum dtdx, direction dsig, + const RPR sig, const RPR kap, const RPR siginv, RPR fu, direction dsigu, + const RPR sigu, const RPR kapu, const RPR siginvu, realnum dt, const RPR cnd, + const RPR cndinv, RPR fcnd, RPR F, realnum k1, realnum k2) { + (void)c; // currently unused + if (!g1) { // swap g1 and g2 + SWAP(const RPR, g1, g2); + SWAP(ptrdiff_t, s1, s2); + SWAP(realnum, k1, k2); // need to swap in cross product + } + if (dsig == NO_DIRECTION) { // no PML in f update + if (dsigu == NO_DIRECTION) { // no fu update + if (cnd) { + if (g2) { + PLOOP_OVER_IVECS(gv, is, ie, i) { + realnum F_prev = F[i]; + F[i] = (k1 * (g1[i + s1] + g1[i]) - k2 * (g2[i + s2] + g2[i])) - F[i]; + f[i] += (F[i] - F_prev) * cndinv[i]; + } + } + else { + PLOOP_OVER_IVECS(gv, is, ie, i) { + realnum F_prev = F[i]; + F[i] = k1 * (g1[i + s1] + g1[i]) - F[i]; + f[i] += (F[i] - F_prev) * cndinv[i]; + } + } + } + else { // no conductivity + if (g2) { + PLOOP_OVER_IVECS(gv, is, ie, i) { + realnum F_prev = F[i]; + F[i] = (k1 * (g1[i + s1] + g1[i]) - k2 * (g2[i + s2] + g2[i])) - F[i]; + f[i] += (F[i] - F_prev); + } + } + else { + PLOOP_OVER_IVECS(gv, is, ie, i) { + realnum F_prev = F[i]; + F[i] = k1 * (g1[i + s1] + g1[i]); + f[i] += (F[i] - F_prev); + } + } + } + } + else { // fu update, no PML in f update + KSTRIDE_DEF(dsigu, ku, is, gv); + if (cnd) { + if (g2) { + PLOOP_OVER_IVECS(gv, is, ie, i) { + DEF_ku; + realnum df; + realnum F_prev = F[i]; + F[i] = (k1 * (g1[i + s1] + g1[i]) - k2 * (g2[i + s2] + g2[i])) - F[i]; + fu[i] += (df = (F[i] - F_prev) * cndinv[i]); + f[i] += siginvu[ku] * df; + } + } + else { + PLOOP_OVER_IVECS(gv, is, ie, i) { + DEF_ku; + realnum df; + realnum F_prev = F[i]; + F[i] = k1 * (g1[i + s1] + g1[i]) - F[i]; + fu[i] += (df = (F[i] - F_prev) * cndinv[i]); + f[i] += siginvu[ku] * df; + } + } + } + else { // no conductivity + if (g2) { + PLOOP_OVER_IVECS(gv, is, ie, i) { + DEF_ku; + realnum df; + realnum F_prev = F[i]; + F[i] = (k1 * (g1[i + s1] + g1[i]) - k2 * (g2[i + s2] + g2[i])) - F[i]; + fu[i] += (df = (F[i] - F_prev)); + f[i] += siginvu[ku] * df; + } + } + else { + PLOOP_OVER_IVECS(gv, is, ie, i) { + DEF_ku; + realnum df; + realnum F_prev = F[i]; + F[i] = k1 * (g1[i + s1] + g1[i]) - F[i]; + fu[i] += (df = (F[i] - F_prev)); + f[i] += siginvu[ku] * df; + } + } + } + } + } + else { // PML in f update + KSTRIDE_DEF(dsig, k, is, gv); + if (dsigu == NO_DIRECTION) { // no fu update + if (cnd) { + realnum dt2 = dt * 0.5; + if (g2) { + PLOOP_OVER_IVECS(gv, is, ie, i) { + DEF_k; + realnum F_prev = F[i]; + F[i] = (k1 * (g1[i + s1] + g1[i]) - k2 * (g2[i + s2] + g2[i])) - F[i]; + realnum dfcnd = (F[i] - F_prev) * cndinv[i]; + fcnd[i] += dfcnd; + f[i] += dfcnd * siginv[k]; + } + } + else { + PLOOP_OVER_IVECS(gv, is, ie, i) { + DEF_k; + realnum F_prev = F[i]; + F[i] = k1 * (g1[i + s1] + g1[i]) - F[i]; + realnum dfcnd = (F[i] - F_prev) * cndinv[i]; + fcnd[i] += dfcnd; + f[i] += dfcnd * siginv[k]; + } + } + } + else { // no conductivity (other than PML conductivity) + if (g2) { + PLOOP_OVER_IVECS(gv, is, ie, i) { + DEF_k; + realnum F_prev = F[i]; + F[i] = (k1 * (g1[i + s1] + g1[i]) - k2 * (g2[i + s2] + g2[i])) - F[i]; + f[i] += (F[i] - F_prev) * siginv[k]; + } + } + else { + PLOOP_OVER_IVECS(gv, is, ie, i) { + DEF_k; + realnum F_prev = F[i]; + F[i] = k1 * (g1[i + s1] + g1[i]) - F[i]; + f[i] += (F[i] - F_prev) * siginv[k]; + } + } + } + } + else { // fu update + PML in f update + KSTRIDE_DEF(dsigu, ku, is, gv); + if (cnd) { + if (g2) { + //////////////////// MOST GENERAL CASE ////////////////////// + PLOOP_OVER_IVECS(gv, is, ie, i) { + DEF_k; + DEF_ku; + realnum df; + realnum F_prev = F[i]; + F[i] = (k1 * (g1[i + s1] + g1[i]) - k2 * (g2[i + s2] + g2[i])) - F[i]; + realnum dfcnd = (F[i] - F_prev) * cndinv[i]; + fcnd[i] += dfcnd; + fu[i] += (df = dfcnd * siginv[k]); + f[i] += siginvu[ku] * df; + } + ///////////////////////////////////////////////////////////// + } + else { + PLOOP_OVER_IVECS(gv, is, ie, i) { + DEF_k; + DEF_ku; + realnum df; + realnum F_prev = F[i]; + F[i] = k1 * (g1[i + s1] + g1[i]) - F[i]; + realnum dfcnd = (F[i] - F_prev) * cndinv[i]; + fcnd[i] += dfcnd; + fu[i] += (df = dfcnd * siginv[k]); + f[i] += siginvu[ku] * df; + } + } + } + else { // no conductivity (other than PML conductivity) + if (g2) { + PLOOP_OVER_IVECS(gv, is, ie, i) { + DEF_k; + DEF_ku; + realnum df; + realnum F_prev = F[i]; + F[i] = (k1 * (g1[i + s1] + g1[i]) - k2 * (g2[i + s2] + g2[i])) - F[i]; + fu[i] += (df = (F[i] - F_prev) * siginv[k]); + f[i] += siginvu[ku] * df; + } + } + else { + PLOOP_OVER_IVECS(gv, is, ie, i) { + DEF_k; + DEF_ku; + realnum df; + realnum F_prev = F[i]; + F[i] = k1 * (g1[i + s1] + g1[i]) - F[i]; + fu[i] += (df = (F[i] - F_prev) * siginv[k]); + f[i] += siginvu[ku] * df; + } + } + } + } + } +} /* Given Dsqr = |D|^2 and Di = component of D, compute the factor f so that Ei = chi1inv * f * Di. In principle, this would involve solving