File:Light scattering - Averaging.gif

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Light_scattering_-_Averaging.gif(600 × 299 pixels, file size: 4.51 MB, MIME type: image/gif, looped, 60 frames, 12 s)

Captions

Captions

Computed light scattered by a number of disks, averaged over different realizations of the disorder.

Summary[edit]

Description
English: Coherent light incident on a scattering medium will produce a volume speckle inside the material. But if you start averaging over more and more realizations of the disorder, the average doesn't look like speckle anymore.

The real part of the electric field (right panel) inside the scattering medium averages to zero, but not immediately. There is a region inside where the amplitude decays exponentially, showing that not all the light is scattered immediately (Lamber-Beer law).

The intensity of the electric field (left panel) can not average to zero, as it is a positive quantity, but it gets smoother and smoother. To a good approximation the average light intensity in a scattering medium can actually be described using the diffusion equation!
Date
Source https://twitter.com/j_bertolotti/status/1413159977854849029
Author Jacopo Bertolotti
Permission
(Reusing this file)
https://twitter.com/j_bertolotti/status/1030470604418428929

Mathematica 12.0 code[edit]

\[Lambda]0 = 1.; k0 = 
 N[(2 \[Pi])/\[Lambda]0]; (*The wavelength in vacuum is set to 1, so all lengths are now in units of wavelengths*)
\[Delta] = \[Lambda]0/10; \[CapitalDelta] = 50*\[Lambda]0; (*Parameters for the grid*)
ReMapC[x_] :=  RGBColor[(2 x - 1) UnitStep[x - 0.5], 0, (1 - 2 x) UnitStep[0.5 - x]];
\[Sigma] = 10 \[Lambda]0;
d = \[Lambda]0/2; (*typical scale of the absorbing layer*)

imn = Table[
   Chop[5 (E^-((x + \[CapitalDelta]/2)/d) + E^((x - \[CapitalDelta]/2)/d) + E^-((y + \[CapitalDelta]/2)/d) + E^((y - \[CapitalDelta]/2)/d))], {x, -\[CapitalDelta]/2, \[CapitalDelta]/2, \[Delta]}, {y, -\[CapitalDelta]/2, \[CapitalDelta]/2, \[Delta]}]; (*Imaginary part of the refractive index (used to emulate absorbing boundaries)*)
dim = Dimensions[imn][[1]];
L = -1/\[Delta]^2*KirchhoffMatrix[GridGraph[{dim, dim}]]; (*Discretized Laplacian*)
optimizedpoint = Round[0.7 dim];
sourcelist = Table[x0, {x0, -\[CapitalDelta]/2 + 2, \[CapitalDelta]/2 - 2, 1}];
sourcedim = Dimensions[sourcelist][[1]];
ren0 = 2;

\[Phi] = Table[
   ren = ren0*Clip[Total[Table[RotateRight[DiskMatrix[5, dim], {RandomInteger[{-Round[dim/2], Round[dim/2] }], RandomInteger[{ -Round[dim/8], Round[dim/2] - 10}]}], {200}]], {0, 1}] + 1;
   n = ren + I imn;
   phases = Table[
     \[Phi]in = Table[E^(-((x - sourcelist[[j]])^2/(2  (\[Lambda]0/2)^2))) E^(-((y + \[CapitalDelta]/2)^2/(2 (\[Lambda]0/2)^2))), {x, -\[CapitalDelta]/2, \[CapitalDelta]/2, \[Delta]}, {y, -\[CapitalDelta]/2, \[CapitalDelta]/2, \[Delta]}];(*Discretized source*)
     b = -(Flatten[n]^2 - 1) k0^2 Flatten[\[Phi]in]; (*Right-hand side of the equation we want to solve*)
     M = L + DiagonalMatrix[SparseArray[Flatten[n]^2 k0^2]]; (*Operator on the left-hand side of the equation we want to solve*)
     \[Phi] = Partition[LinearSolve[M, b], dim]; (*Solve the linear system*)
     Arg[\[Phi][[Round[dim/2] , optimizedpoint ]] ]
     , {j, 1, sourcedim, 1}];
   \[Phi]in = Total@Table[Table[E^(-((x - sourcelist[[j]])^2/(2  (\[Lambda]0/2)^2))) E^(-((y + \[CapitalDelta]/2)^2/(2 (\[Lambda]0/2)^2))) E^(-I phases[[j]]), {x, -\[CapitalDelta]/2, \[CapitalDelta]/2, \[Delta]}, {y, -\[CapitalDelta]/2, \[CapitalDelta]/2, \[Delta]}], {j, 1, sourcedim}];(*Discretized source*)
   b = -(Flatten[n]^2 - 1) k0^2 Flatten[\[Phi]in]; (*Right-hand side of the equation we want to solve*)
   M = L + DiagonalMatrix[SparseArray[Flatten[n]^2 k0^2]]; (*Operator on the left-hand side of the equation we want to solve*)
   Partition[LinearSolve[M, b], dim] (*Solve the linear system*)
   , {50}];

\[Phi]0 = Table[ren = 
    ren0*Clip[Total[Table[RotateRight[DiskMatrix[5, dim], {RandomInteger[{-Round[dim/2], Round[dim/2] }], RandomInteger[{ -Round[dim/8], Round[dim/2] - 10}]}], {250}]], {0, 1}] + 1;
   n = ren + I imn;
   \[Phi]in = Total@Table[Table[E^(-((x - sourcelist[[j]])^2/(2  (\[Lambda]0/2)^2))) E^(-((y + \[CapitalDelta]/2)^2/(2 (\[Lambda]0/2)^2))) , {x, -\[CapitalDelta]/2, \[CapitalDelta]/2, \[Delta]}, {y, -\[CapitalDelta]/2, \[CapitalDelta]/2, \[Delta]}], {j, 1, sourcedim}];(*Discretized source*)
   b = -(Flatten[n]^2 - 1) k0^2 Flatten[\[Phi]in]; (*Right-hand side of the equation we want to solve*)
   M = L + DiagonalMatrix[SparseArray[Flatten[n]^2 k0^2]]; (*Operator on the left-hand side of the equation we want to solve*)
   Partition[LinearSolve[M, b], dim] (*Solve the linear system*)
   , {50}];

frames = Table[GraphicsRow[{
     ArrayPlot[
      Transpose[(Mean[Abs[#]^2 & /@ \[Phi]0[[1 ;; j]]  ]/Max[avg\[Phi]0abs[[(4 d)/\[Delta] ;; (-4 d)/\[Delta], (4 d)/\[Delta] ;; (-4 d)/\[Delta]]]])][[(4 d)/\[Delta] ;; (-4 d)/\[Delta], (4 d)/\[Delta] ;; (-4 d)/\[Delta]]], ColorFunction -> "AvocadoColors", DataReversed -> True, Frame -> False, PlotRange -> {0, 1}, LabelStyle -> {Black, Bold}, ColorFunctionScaling -> False],
     ArrayPlot[
      Transpose[(Mean[Re[#] & /@ \[Phi]0[[1 ;; j]]  ]/Sqrt[Max[avg\[Phi]0abs[[(4 d)/\[Delta] ;; (-4 d)/\[Delta], (4 d)/\[Delta] ;; (-4 d)/\[Delta]]]]])][[(4 d)/\[Delta] ;; (-4 d)/\[Delta], (4 d)/\[Delta] ;; (-4 d)/\[Delta]]], ColorFunction -> ReMapC, DataReversed -> True, Frame -> False, PlotRange -> {-1, 1}, LabelStyle -> {Black, Bold}, ColorFunctionScaling -> True]
     }]
   , {j, 1, 50}];
ListAnimate[frames]

Licensing[edit]

I, the copyright holder of this work, hereby publish it under the following license:
Creative Commons CC-Zero This file is made available under the Creative Commons CC0 1.0 Universal Public Domain Dedication.
The person who associated a work with this deed has dedicated the work to the public domain by waiving all of their rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law. You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission.

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Date/TimeThumbnailDimensionsUserComment
current10:19, 9 July 2021Thumbnail for version as of 10:19, 9 July 2021600 × 299 (4.51 MB)Berto (talk | contribs)Uploaded own work with UploadWizard

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