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Entry  Mon Jul 29 22:30:34 2013, tara, Notes, optic, coating optimization for AlGaAs multilayer1.JPGmultilayer2.JPGopt1_2013_07_29.pngnb_opt1_2013_07_29.pngT1200003_refcav.png
    Reply  Wed Jul 31 00:31:39 2013, tara, Notes, optic, coating optimization for AlGaAs 
       Reply  Fri Aug 9 17:58:01 2013, tara, Notes, optic, coating optimization for AlGaAs TOoptimized_2013_08_09.pngTOoptimized_2013_08_09.figTO_opt_200ppm_layer.pngTO_opt_200ppm_layer.fig2013_08_09_TOopt_200ppm.mat
          Reply  Tue Aug 27 16:11:26 2013, tara, Notes, optic, coating optimization for AlGaAs:error analysis 8x
             Reply  Wed Aug 28 21:21:38 2013, tara, Notes, optic, GWINC for TO calculation: recap 
             Reply  Sun Sep 1 18:38:37 2013, tara, Notes, optic, coating optimization for AlGaAs:error analysis 7x
                Reply  Mon Sep 2 18:31:46 2013, tara, Notes, optic, coating optimization for AlGaAs:error analysis 
                   Reply  Wed Sep 18 21:55:11 2013, tara, Notes, optic, coating optimization for AlGaAs:error analysis opt_coatings.mat
                      Reply  Thu Sep 19 20:38:17 2013, tara, Notes, optic, coating optimization for AlGaAs:error analysis power_vs_mirror_size.png
                Reply  Fri Sep 20 19:26:45 2013, tara, Notes, optic, coating optimization for AlGaAs:error analysis error_check_params.pngerror_check_params.figerror_thick_params_compare.pngerror_thick_params_compare.fig
                   Reply  Fri Sep 20 21:19:29 2013, Matt A., Notes, optic, coating optimization for AlGaAs:error analysis 
                   Reply  Sat Sep 21 23:49:29 2013, rana, Notes, optic, coating optimization for AlGaAs:error analysis 
                      Reply  Sun Sep 22 00:27:09 2013, some random goon, Notes, optic, coating optimization for AlGaAs:error analysis 
                         Reply  Mon Sep 23 18:07:22 2013, rana, Notes, optic, coating optimization for AlGaAs:error analysis 
                            Reply  Mon Sep 23 18:50:05 2013, tara, Notes, optic, coating optimization for AlGaAs:error analysis compare_indices.pngcompare_indices.figcompare_indices.png
                               Reply  Thu Sep 26 23:25:40 2013, tara, Notes, optic, coating optimization for AlGaAs:error analysis  8x
                                  Reply  Thu Oct 3 10:34:32 2013, tara, Notes, optic, coating optimization for AlGaAs:error analysis  
                                     Reply  Thu Oct 10 01:59:24 2013, tara, Notes, optic, coating optimization for AlGaAs:error analysis  
                                        Reply  Fri Oct 11 15:23:54 2013, tara, Notes, optic, coating optimization for AlGaAs:electric field in coating layer 6x
                                           Reply  Mon Oct 14 21:02:00 2013, tara, Notes, optic, coating optimization for AlGaAs:variation in x 
                                           Reply  Sun Oct 27 20:12:25 2013, tara, Notes, optic, photothermal noise in AlGaAs Int_cotings.pngInt_cotings.fig
                                              Reply  Wed Dec 18 21:05:28 2013, tara, Notes, optic, photothermal noise in AlGaAs: thickness resolution 8x
                                                 Reply  Sat May 17 22:01:28 2014, tara, Notes, optic, Coating TO opt for Adv LIGO: ETM 7x
                                                    Reply  Sun May 18 10:45:42 2014, tara, Notes, optic, Coating TO opt for Adv LIGO dOpt_ITM1.pngdOpt_ITM1.figAdvLIGO_AlGaAs.pngAdvLIGO_AlGaAs.fig
                                           Reply  Sat Jun 20 10:14:50 2015, Evan, Notes, optic, coating optimization for AlGaAs:electric field in coating layer Efieldtrans.pdf
Message ID: 1315     Entry time: Tue Aug 27 16:11:26 2013     In reply to: 1291     Reply to this: 1318   1320
Author: tara 
Type: Notes 
Category: optic 
Subject: coating optimization for AlGaAs:error analysis 

Since the optimized layer structure is designed, I'm checking how the coatings properties change with error in layer thickness.

G.Cole said that they can control each layer thickness within 0.3%. So I tested the optimized coatings properties by adding some random number within +/- 0.5% on each layer thickness. The results are shown below for 10 000 test.

The error check does the following:

  • start from the optimized coating structure reported in PSL:1291.
  • add random thickness to each layer, within 0.5% of each layer
  • calculate the values of interest, then histogram them.

The figure below is an example of the varying layer thickness added by rand command. They are confined within 0.5%.

layer_error.png

 1) result from the error in thickness control

error_analysis_0.5percent.png

Above: histograms of the important values. top left, reflected phase. top right, ratio between PSD of Brownian noise and Thermo optic noise at 100 Hz. Bottom left, transmission. Bottom right, total coating thickness error.

 

 comments: this test is chosen for 0.5% error which is almost a factor of 2 worse than what they claimed (0.3%), so the actual result should be better. I assumed 0.5% errof because of the irregular layer structure of the optimized coatings, there might be some more error in the manufacturing process.

  • Reflected phase: we want the reflected phase to be close to 180, so that the E-field at the coating surface is close to 0. more than 50% of the results are within 179.5degree, this means that the power build up will be ~ Finesse/pi * Power input * sin^2 (0.5degree)  ~ less than 0.4 mW, so there should be no problem about burning at the surface.
  • ratio between PSD of Brownian/Thermo optic noise. This plot imply how well the cancellation works. Since Brownian noise will almost not change (both materials have the same loss, total thickness varies less than 1%), the ratio of Br/TO noise (at 100Hz) tells how much TO cancellation is. From the histogram we are quite sure that cancellation will work most of the time.
  • Transmission is good around 200+/- 10ppm this is ok with the requirement.
  • total physical error is ~5nm while the coatings thickness is ~ 4um. so the total error is <0.1% Brownian noise calculation will not change much.

2) result from different calculated Beta values:

Here I checked what happen if the beta calculation was wrong, and the error is still within 0.5% in each layer.

In Evans paper, the effect from "Thermo-refractive" comes from the phase changes of the wave travels in each layer. So it includes the effect from dn/dT and dz. The effective beta for each layer is given as

evanB8.png[evan B8],

where alpha bar is

evanA1.png[evans A1]

Where s denotes substrate, k denotes the material in each layer (high or low indices).

So my, calculation & optimization have been using these equations.

However, in the original GWINC code for TO calculation, the calculation [B8], alphabark( used in dTR) is not the same as A1, but rather.

alphaH * (1 + sigH) / (1 - sigH)

see getCoatLayerAGS.m.  Line 16-17.

This is used in the calculation for beta effective in getCoatTOphase. Line73-74. Notice that for dTE, the alpha_bar_k is the same as used in Evans. (line 77).

the comment says "Yamamoto thermo-refractive correction". I emailed kazuhiro yamamoto, but never got a response back. So I keep using the same formula as in Evans because I don't see the reason why the expansion contribution should be different between TE and TR.

So this is the nb plot for TO noise from the optimized coating, if using yamamoto TR correction.

yamamoto_TR_correction.png

Above: nb from the optimized coatings, using Yamamoto TR correction. The cancellation becomes worse, but TO is still lower than other noise.

 

Finally, I repeat the same error analysis for random noise in the thickness (+/- 0.5%).

 yamamoto_error.png

Most of the parameters behave similarly, except the cancellation (upper right plot). Now BR is only ~ x12 larger than TO noise because of the worse cancellation. Good news is, it still below Brownian noise, the cancellation still somehow works.

 

=summary=

  • From the optimized coating structure (T=200ppm), thickness control within 0.5% in each layer will make the coating work as expected.
  • The yamamoto TR correction is still an unresolved issue, but the optimized coating will still work.
  • we should be ready to order soon.
Attachment 2: error_analysis_0.5percent.fig  17 kB  Uploaded Tue Aug 27 17:15:08 2013
Attachment 6: yamamoto_TR_correction.png  104 kB  Uploaded Tue Aug 27 21:39:16 2013  | Hide | Hide all
yamamoto_TR_correction.png
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