Here are the results in the annulus thickness vs annulus diameter space ...
I added a COMSOL model of the aLIGO ITM being heated by an axicon-formed annulus to the 40m SVN. The model assumes a fixed input beam size into an axicon pair and then varies the distance between the axicons. The output is imaged onto the ITM with varying magnitudes. The thermal lens is determined in the ITM and added to the self-heating thermal lens (assuming 1W absorption, I think - need to check). The power in the annulus is varied until the sum of the two thermal lenses scatters the least amount of power out of the TEM00 mode of the IFO.
The results across the parameter space (axicon separation and post-axicon-magnification) are attached. These were then mapped from this space to the space of annulus thickness vs annulus diameter, also attached.
As I started setting up my next experiment, I noticed that the beam size from the SLED appeared to be larger than expected from previous analysis. It was therefore necessary to conduct further experiments to characterize the divergence angle of the beam.
First, I set up the photodetector attached to an SLED and mounted a razor blade on a translational stage, in the same manner as done previously. All of these components were the exact same ones used in the previous beam size experiment. The only differences in the components of the apparatus were as follows: first, the photodetector was placed considerably closer to the SLED source than was done previously. Second, a different lens was used to focus the light onto the photodetector. Lens LX082 from the lenskit was used, which is a one-inch lens of focal length f=50.20mm.
Experiment 1: Columnated Beam Size Measurement
Before repeating the previous experiment, the following experiment was done: the beam was columnated by placing the lens 50.20mm away from the source and then adjusting until columnation was observed. Columnation was confirmed by setting a mirror in the optical path of the beam directing it to the other side of the room. The position of the lens along the optical axis was adjusted until the beam exiting the lens did not change in size across the length of the table and appeared to be roughly the same size as the spot on the opposite side of the room (as gauged roughly by the apparent size on an IR card and through an IR viewer).
Then,the translational stage onto with the laser was mounted was placed after the lens against the ruler clamped to the table, and beam size was measured using the same experimental procedure used to find the width in the previous experiment. The only variation in the experimental procedure was that measurements were not taken strictly at 0.5V intervals; rather, intensity readings were taken for 28 different intensity outputs. The following measurements were collected:
When fit to gsbeam.m using lsqcurvefit, this yielded a width of 4.232mm. Since the beam is columnated through the lens, we know that it is approximately f=50.2mm from the source. Thus the divergence angle is approximately 0.084.
At this point, to double-check that the discrepency between this value and the previous experiment was not a result of a mistake in the function, I wrote a simpler function to go through the steps of using lsqcurvefit and plotting the fit curve versus the data automatically, 'manualbeam.m' (attached), which simply fits a curve to one set of data from a constant z-value. Using this one-by-one on each z-value in the previous experiment, it was shown that the slope of the widths was still ~0.05, so this discrepency was not the result of a mistake in the previous function somewhere.
Experiment 2: Blocked Beam Analysis 2
I then placed the razor before the lens in the beampath and repeated the previous experiment exactly. See the previous eLog for details on experimental procedure. Sets of measurements were taken at 6 different z-values, and widths were found using manualbeam.m in MATLAB. A curve of the calculated widths versus the z-position of the stage on the ruler is below:
Note that this appears to be consistant with the first experiment.
Experiment 3: Direct Beam Measurements on CCD
The front-plate of the Hartmann sensor was replaced with the new invar design (on a related note, the thread on the front plate needs a larger chamfer). In doing this, the Hartmann plate was removed. The sensor was moved much closer to the SLED along the optical axis, and an optical filter of OD 0.7 was screwed into the new frontplate. This setup allows for the direct imaging of the intensity of the beam, as shown below:
The spots and distortions on the image are from dust and other blemishes on the optical filter, as was confirmed by rotating the filter and observing the subsequent rotation of each feature.
Note that in some images, there may be a jump in intensity in the middle of the image. This is believed to be due to a inconsistant gain between the two sides of the image.
The means of the intensities of each row and each column will be Gaussian, and thus can be fit to a Gaussian using lsqcurvefit. Function 'gauss_beam1D.m' was written and this function was fit to using function 'autogaussfit1', which automatically imports the data from .raw files, fits Gaussians to the means of each row and column, and plots everything.
An example of the fit for the means of the columns of one image is as follows:
And for the rows:
Note that for all the fits, the fitting generally looks a little better along the row than along the column (which is true here, as well).
The following procedure was used to calculate the change of the beam width as a function of distance: the left edge of the base of the Hartmann sensor was measured against a ruler which was clamped to the table. The ruler position z was recorded. Then, preliminary images would be taken and the exposure time would be adjusted as needed. The exposure time was then noted. Then, an image was taken and curves were fit to it, and the width was calculated. This was done for 15 different positions of the Hartmann sensor along the optical axis.
The calculated widths vs. displacements plot from this can be seen below:
Note that the row width and column width are not the same, implying that the beam is not circularly symmetric and is thusly probably off alignment by a little bit. Also, the calculated slopes are different than the value of 0.085 acquired from the previous two measurements. Further investigation into the beam size and divergence angle is required to finally put this question to rest.
xlabel('Stage Translation (mm)')
ylabel('Photodetector Output (V)')
text(0.8,0.2,['A = ' num2str(x(1))],'FontSize',12,'Interpreter','none','Units','normalized');
text(0.8,0.15,['x0 = ' num2str(x(2))],'FontSize',12,'Interpreter','none','Units','normalized');
text(0.8,0.1,['w = ' num2str(x(3))],'FontSize',12,'Interpreter','none','Units','normalized');
function result = gauss_beam1D(x0, xdata)
% x0(1) = offset
% x0(2) = amplitude
% x0(3) = x centroid location
% x0(4) = x width
result = x0(1) + x0(2).*exp(-2.0.*( ...
((xdata - x0(3)).^2)/(x0(4).^2)));
function [x y wx wy]=autogaussfit1(imgname,guess,imgdetails)
%guess = [offset amplitude centroidlocation width]
%imgdetails = [HWSrulerlocation exp.time]
%output vectors same format as guess
rulerz = imgdetails(1,1);
exposure = imgdetails(1,2);
In the previous log, I describe the direct measurement of the fiber output beam using the Hartmann sensor with the plate removed. In order to analyze how these properties might change as a function of time, we left the camera running over the holiday weekend, Dr. Brooks having written a bash script which took images from the sensor every 500 seconds. This morning I wrote a MATLAB script to automatically analyze all of these images and plot the fit parameters as a function of time (weekendbeamtime.m, attached). Note that the formatiing of a few of the following graphs was edited manually after being outputted by the program (just to note why the plots look different than the code might imply).
The following plots were made:
Amplitude as a function of time:
Amplitude again, focused in with more analysis:
Centroid Displacement (note the axis values, it's fairly zoomed in):
Note that these values were converted into radians by approximating the fiber-output/CCD distance and dividing this from the displacement in mm (after converting from pixels). This distance was approximated by assuming a divergence angle of 0.085 and a beam size of ~5.1mm (being a value inbetween the horizontal and vertical beam sizes calculated). This gave a value of ~60mm, which was confirmed as plausible by a quick examination in the lab.
In the first three plots, there are obvious temporary effects which seem to cause the values to fluctuate much more rapidly than they do for the rest of the duration. It is suspected that this could be related to temperature changes within the sensor as the camera begins taking images. Further investigation (tomorrow) will investigate these effects further, while collecting temperature data.
function [X Y wX wY]=weekendbeamtime(basename,guess,N)
%fits 1D gaussian curve to N images in sequence of basename basefile
A quick write-up on recent work can be found at: Google Docs
I can't find a Tex interpreter or any other sort of equation editor on the eLog, is why I kept it on Google Docs for now instead of transferring it over.
display(['Image Number ' num2str(n)])
%Imports mainoutbase.raw generated by python framesumexport2 and outputs
%Nth image matrix I
mainout=['/opt/EDTpdv/' mainoutbase '.raw'];
%open main output array
fid = fopen(mainout,'r');
arr = fread(fid,1024*1024,'float');
maintxt=['/opt/EDTpdv/' mainoutbase '.txt'];
str=strrep(str,'Camera Temperature on Digitizer Board:','');
str=strrep(str,'Camera Temperature on Sensor Board:','');
#Number of loops LoopN over which to sum SumN images of dim num_H by num_W
num_H = 1024
num_W = 1024
As discussed during the teleconference, a series of experiments have been conducted which attempt to measure the thermally induced defocus in the Hartmann sensor measurement. However, there was a limiting source of noise which caused a very large displacement of the centroids between images, making the images much too noisy to properly analyze.
The general setup of this series of experiments is as follows: the fiber output from the SLED was mounted about one meter away from the Hartmann sensor. No other optics were placed in the optical path. Everything except for the Hartmann sensor was enclosed (a box was constructed out of wall segments and posterboard, with a hole cut in the end which allowed the beam to propagate into the sensor. The sensor was a short distance from the end of the box, less than a centimeter. There was no obvious difference in test images taken with the lights on and the lights off, which previously suggested to me that ambient light would not have a large effect). Temperature variations in the sensor were induced by changing the set temperature of the lab with the thermostat. A python script was used to take cumulative sums of 200 images (taken at 11Hz) every ~5 minutes.
This overly large centroid displacement appeared only in certain areas of the images. However, changing the orientation of the plate appeared to change the regions which were noisy. That is, if the orientation of the Hartmann plate was not changed between measurements, the noise would appear in the same regions in consecutive experiments (even in experiments conducted on different days). However, if the orientation of the Hartmann plate was changed between measurements, the noise would appear in a different region in the next experiment. This suggests that the noise is perhaps due to a physical phenomenon which would change with the orientation of the plate.
There were a few hypotheses which attempted to explain this noise but were shown to not be the likely cause. I hypothesized that the large thermal expansion coefficient of the aluminum camera housing could be inducing a stress on the invar frontplate, causing the Hartmann plate to warp. This hypothesis was tested by loosening the screws which attach the front and back portion of the frontplate (such that the Hartmann plate was not strongly mechanically coupled with the rest of the frontplate) and running another iteration of the experiment. The noisy regions were seen to still appear, indicating that thermally induced stress was not the cause of the distortion. Furthermore, experiments done while the sensor was in relative thermal equilibrium over long periods still showed noisy regions, and there was no apparent correlation between noise magnitude and sensor temperature for any experiment, indicating that thermal effects in general were not responsible.
Another suspected cause was the increased noise at intensity levels of 128 (as discussed in a previous eLog). However, it was observed that there was no apparent difference in the prevalence of 128-count pixels between the noisy regions and the cleaner regions, indicating that this was not the cause either.
A video was made which shows vector plots of centroid displacements for each summed image relative to the first image taken in an experiment, and was posted as an unlisted youtube video at: http://www.youtube.com/watch?v=HUH1tHRr98I
The length of each vector in the video is proportional to the magnitude of the displacement. The localization of the noise can be seen. Notice also the sudden appearance and disappearance of the noise at images 19 and 33, indicating that the cause of the noise is relatively sudden and does not vary smoothly.
Another video showing a logarithmic plot of the absolute value of the difference of each image from the first image (for the same experiment as previous) can be seen here: http://www.youtube.com/watch?v=_CiaMpw9Ig0
Notice there are jumps in the background level which appear to correspond with the disappearance and appearance of the noisy regions in the centroids (at images 18 and 32) (I forgot to manually set the framerate on these last three .avi's, so they go by a little too quickly, but it's still all there). The one-image delay between the intensity shift and centroid noise shift is perhaps related to the fact that the analysis uses the previous image centroids as the reference to find the new image centroid locations.
A video showing histograms of the intensity of each pixel in an image (within the intensity range of 50 and 140 in the averaged summed-image) for this same experiment can be seen at: http://www.youtube.com/watch?v=MogPd-vaWn4
Notice that the peak of the distribution corresponding to the background appears to shift by ~5 counts at images 18 and 32.
An experiment was then done which had the exact same procedure except that it was done at a stabilized lab temperature and with the SLED turned off, such that only the background appears in each image. A logarithmic plot of the absolute value of the difference in intensity at each pixel for each image can be seen at: http://www.youtube.com/watch?v=Y66wL5usN18
Other work was being done in the lab throughout the day, so the lights were on for every image but one. I made a point of turning off the lights while the 38th image was being taken. The framerate of the linked video is unfortunately a little too fast to really see what goes on (I adjusted the framerate while viewing it in MATLAB but forgot to do so for the AVI), but you can clearly see a major change in the image during the 38th image, and during that image only (it looks like a red 'flash' at the 38th frame, near the very end). The only thing that was changed while taking this specific image was the ambient light level, so this major difference must be due to ambient light. A plot of the difference between images 38 and 1 is shown below:
Note that the maximum difference between the images is 1107 levels, which for the 200 images in each summed image corresponds to an average shift of ~5.5 levels. This is of a very similar magnitude to the shift that can be seen in the histogram of the previous experiment. This suggests that changes in ambient light levels are perhaps somehow responsible for the noisy regions of the image. Note also the non-uniformity of the ambient light; such a non-uniform change could certainly shift the centroid positions.
One question is how, exactly, this change might have propagated into the analysis. The shape of the background level change appears to be very different from the shape of the noisy regions seen for this plate configuration. This is something which I need to examine further; this, combined with the fact that the changes in the noise appear to occur one image after the actual change in intensities, suggests to me that there could perhaps be some subtle things going on with my data analysis procedures which I don't currently fully understand.
Still, I highly suspect that ambient light is the root cause of the noisy regions. It would be a remarkable coincidence if the centroid displacement shift was not ultimately due to the observed intensity shift, or if the intensity shift was not due to a change in ambient light (since the intensity shift in the histogram analysis and ambient light change in the background analysis are observed to correspond to roughly the same magnitude of intensity change). I had initially suspected that effects from ambient light would be negligible since, while taking test images while setting up each experiment, the image did not appear to change based upon whether I had the lights on or off. I checked this a few times, but did not examine the images closely enough to be able to detect such a small non-uniform change in the intensity of each image.
If ambient light was responsible, this could also perhaps explain why the location of the noise appeared to depend on the orientation of the plate. The Hartmann plate would be in the optical path of any ambient light leaking in, so a change in the orientation of the plate could perhaps change the way that the ambient light was propagating onto the sensor (especially since the Hartmann plates are slightly warped and not perfectly planar). That's all purely speculation at this point, but it's something that I intend to investigate further.
I tried analyzing some previous data by subtracting part of the background, but was unsuccessful at reducing the noise in the results. I attempted to reduce the background in previous data by setting all values below a certain threshold equal to zero (before inputting the image into the centroiding function). However, the maximum threshold which I could use before getting an error message was ~130. If I set the threshold to, say, 135, I received an error from the centroiding function that the image was 'too dissimilar to the hex grid'. I did analysis of the images with a threshold of 130, but this still left random patches of background spaced between the spots in each image. The presence of only patches of background as opposed to the complete background actually increased the level of noise in the results by about a factor of 3. I would need to come up with a better method of subtracting the background level if I wanted to actually reduce the noise in this data.
The next step in this work, I think, will perhaps be to better enclose the system from ambient light to where I'm confident that it could have little or no effect. If noisy regions were not seen to appear after this was done, that would more or less confirm that ambient light was the cause of all this trouble. Hopefully, if ambient light is indeed the cause of the noise, reducing it will enable an accurate and reliable measurement of thermally induced defocus within the Hartmann sensor.
My previous eLog details how the noise in Hartmann Sensor defocus measurements appears to vary with ambient light. New troubleshooting analysis reveals that the rapid shifts in the noise were still related to the ambient light, sort of, but that ambient light is not the real issue. Rather, the noise was the result of some trouble with the centroiding algorithm.
The centroiding functions I have been using can be found on the SVN under /users/aidan/cit_centroid_code. When finding centroids for non-uniform intensity distributions, it is desirable to avoid simply using a single threshold level to isolate individual spots, as dimmer spots may be below this threshold and would therefore not be "seen" by the algorithm. The centroiding functions used here get around this issue by initially setting a relatively high threshold to find the centroids of the brighter spots, and then fitting a hexagonal close-packed array to these spots so as to be able to infer where the rest of the spots are located. Centroiding is then done within small boxes around each estimated centroid location (as determined by the hexagonal array). The functions "find_hex_grid.m" and "flesh_out_hex_grid.m" serve the purpose of finding this hexagonal grid. However, there appear to be bugs in these functions which compromise the ability of the functions to accurately locate spots and their centroids.
The centroiding error can be clearly seen in the following plot of calculated centroids plotted against the raw image from which they were calculated:
At the bottom of the image, it can be seen that the functions fail at estimating the location of the spots. Because of this, centroiding is actually being done on a small box surrounding each point which consists only of the background of the image. This can explain why these centroids were calculated to have much larger displacements and shifted dramatically with small changes in ambient light levels. The centroiding algorithm was being applied to the background surrounding each of these points, so it's very reasonable to believe that a non-uniform background fluctuation could cause a large shift in the calculated centroid of each of these regions.
It was determined that this error arose during the application of the hex grid by going through the centroiding functions step-by-step to narrow down where specifically the results appeared to be incorrect. The function's initial estimate for the centroids right before the application of the hex grid is shown plotted against the original image:
The centroids in this image appear to correspond well to the location of each spot, so it does not appear that the error arises before this point in the function. However, when flesh_out_hex_grid and its subfunction find_hex_grid were called, they produced the following hexagonal grid:
It can be seen in this image that the estimated "spot locations" (the intersections of the grid) near the bottom of the image differ from the actual spot locations. The centroiding algorithm is applied to small regions around each of these intersections, which explains why the calculated "spot centroids" appear at incorrect locations.
It will be necessary to fix the hexagonal grid fitting so as to allow for accurate centroiding over non-uniform intensity distributions. However, recent experiments in measuring thermally induced defocus produce images with a fairly uniform distribution. It should therefore be possible to find the centroids of the images from these experiments to decent accuracy by simply temporarily bypassing the hexagonal-grid fitting functions. To demonstrate this, I analyzed some data from last week (experiment 72010a). Without bypassing the hex-grid functions, analysis yielded the following results:
However, when hexagonal grid fitting was bypassed, analysis yielded the following:
The level of noise in the centroid displacement vs. centroid location plot, though still not ideal, is seen to decrease by nearly two orders of magnitude. This indicates that bypassing or fixing the problems with the hexagonal grid fitting functions should enable a more accurate measurement of thermally induced defocus in future experiments.
This attachment is a Shockwave Flash animation of the iLIGO ETM getting a 1 W beam with a 3.5 cm radius getting fully absorbed onto the surface at t = 0.
Here are some pictures of the ring heater segments destined for the H2 Y-arm this year.
These still need to be put onto ResourceSpace.
Using some of the old data from James (attached below), I calculated the CCD conversion efficiency (CE) from electrons to bits (Counts).
Number of electrons(Ne) = QE*Number of Photons(Np)
noiseE = sqrt(Ne);
Number of Counts (NCo)= CE*Ne
Noise in Counts (noiseCo)= CE*sqrt(Ne)
noiseCo = sqrt(CE * NCo)
log(CE) = 2*noiseCo - NCo
Therefore CE = 10.0^(2*noiseCo - NCo)
From James's data on the intensity noise in the CCD, CE = 0.0269
Around a year ago, Phil and I discussed the possibility of using an OPO to possibly generate our own laser beam at ~2 microns for TCS. This was to avoid all of the usual hassle of the 10 micron CO2 laser.
As it turns out, the 1.5-3 micron range doesn't have enough absorption in fused silica: the absorption depth would be basically the whole thickness of the optics and this is not so useful when trying to correct surface heating.
During my recent trip to JILA, Jan Hall mentioned to me that it should be possible to operate instead at ~5 microns, where laser technology may be solid state and where we can use Si:As detectors instead of the inefficient HgCdTe ones which we use now.
JWST, in partnerships with industry, have developed some Si:As detectors: http://www.jwst.nasa.gov/infrared.html
Some internet searching shows that there are now several laser technologies for the mid-IR or MWIR range. Some are <1 W, but some are in the ~10 W range.
Of course, its possible that we'll switch to Silicon substrates, in which case we need to re-evaluate the goals and/or existence of TCS.
- Had a meeting to talk about the basics of LIGO (esp. TCS) and discuss the project
- Created COMSOL model for the test mass with incident Gaussian beam.
- Added a ring heater to the previous file
- Set up SVN for the COMSOL repository
- Got access to and started working with SIS on Rigel1
- Fixed SVN issues
- Refined COMSOL model parameters and worked on a better way to implement the heating ring to get the astigmatic heating pattern.
-Discussed the actual project outline
-Installed Comsol on the system
-Learned the basics of Comsol with the help of tutorials available on 40m wiki
-Made few simple models in Comsol
-Studied LIGO GWADW slides for a better understanding of the project.
-Setup SVN to access remote repository.
- Created a COMSOL model with thermal deformations
- Added non-symmetrical heating to cause astigmatism
- Worked on a method to compute the optical path length changes in COMSOL
-Created a COMSOL model for variation of temperature in two mass system.
-Used the above model for cryogenic conditions.
-checked it analytically.
- Tried to fix COMSOL error using the (ts) module, ended up emailing support as the issue is new in 4.3
- Managed to get a symmetric geometric distortion by fixing the x and y movements of the mirror to be zero (need to look for a better way to do this as this may be unphysical)
- Worked on getting the COMSOL data into SIS, need to look through the SIS specs to find out how we should be doing this (current method isn't working well)
-Created a COMSOL model for cryogenically shielded test mass with compensation plate.
-Analyzed the behavior of the model in different size configurations.
- Fixed the (ts) model, got strange results that indicate that the antisymmetric heating mode is much more prominent than previously thought
- Managed to get COMSOL data through matlab and into SIS
-Continued with the same cryogenic model created and varied the length of outer shield and studied the temperature variation inside.
-Compared the temperature difference given by COMSOL with manually calculated one.
- Realized that the strange deformations that we were seeing only occur on the face nearest the ring heater, and not on the face we are worried about (the HR face)
- Read papers by Morrison et al. and Kogelnik to get a better understanding of the mathematics and operations of the optical cavity modeled in SIS
- Read some of the SIS manual to better understand the program and the physics that it was using (COMSOL licenses were full)
-Derived formula for manual calculation of temperature due to total influx.
-Compared the results by COMSOL and by the formula.
- Plugged the output of the model with uniform heating into SIS using both modification of the radius of curvature, and direct importation of deflection data
- Generated a graph for asymmetric heating and did the same
- Aligned axes in model to better match with the axes in MATLAB and SIS so that the extrema in deflections lie along x and y (not yet implemented in the data below)
FP cavity modal analysis using cold optics parameters
ROC(ITM) = 1934, ROC(ETM) = 2245, Cavity lenggth = 3994.499999672, total Gouy = 2.7169491305278
Fval(ITM) = -4297.7777755379, OPL(ITM) = 0.13793083662307, Fval(ETM) = -4988.8888885557
waist size = 0.01203704073212, waist position from ITM = 1834.2198819617, Rayleigh range = 427.80682127602
Mode parameters of cavity fields
ETM AR (out base) : w = 0.0619634 R = 1548.276 z = 1519.925 z0 = 207.583 w0 = 0.008384783
- Verified that the SIS output does match satisfy the equations for Gaussian beam propagation
- Investigated how changing the amount of data points going into SIS changed the output, as well as how changes in the astigmatic heating effect the output
+ The results are very dependent on number of data points (similar order changes to changing the heating)
+ Holding the number of data points the same, more assymetric heating tends to lead to more power in the H(2,0) mode, and less in the H(0,2)
-Read about blue team design for maximum power budget.
-Read third generation talks to get a better understanding of the work.
- Did more modeling for different levels of heating and different mesh densities for the SIS input.
- Lots of orientation stuff
- Started on progress report.
- Attended a lot of meetings (Safety, LIGO Orientation)
- Finished draft of week 3 report (images attached)
-Attented LIGO orientation meeting and safety session.
-Prepared 3 week report
- Paper edits and more data generation for the paper (lower resolution grid data)
- Attended a talk on LIGO
-Updated 3 week progress report with new additions and deletions.
-Attended LIGO lecture which was very interesting and full of information.
- Discussed the further project with Dr. Brooks.
-Tried to derive formula for the test mass inside cryogenic shield(infinitely long shield from one side)
Plan for building the model
- Find the fields that would be incident on the beam splitter from each arm (This is done already)
- Propagate these through until they get to the OMC using the TELESCOPE function in SIS
- Combine the fields incident on the OMC in MATLAB and minimize the power to get the input field for the OMC (Most of this is done, just waiting to figure out what kind of format we need to use it as an SIS input)
- Model the OMC as an FP cavity in SIS
+ Need to think about how to align the cavity in a sensible way in SIS (need to find out more about how they actually do it)
- Pick off the fields from both ends of the OMC-FP cavity for analysis
- Add thermal effects to one of the arms and see how that changes the fields, specifically how the signal to noise ratio changes
- Finished the MatLab code that both combines two fields and simulates the adjustment of the beamsplitter to minimize the power out (with a small offset).
- Added the signal recycling telescope to the SIS code that generates the fields
To Do: Make the OMC cavity in SIS
-Discussed the project outline for next 6 weeks.
-made a write up for the tasks. (attached)
-Analyzed the variation of temperature of the test mass with input power for different lengths of the shield.
Made a COMSOL model that can include CO2 laser heating, self heating, and ring heating
Figured out how to run SIS out of a script and set up commands to run the two SIS stages of the model
Borrowed thorlabs power meter on 21 Sep 2017. It is on the south table of the ATF lab.
I've started an 80C cure of two materials bonded by EPOTEK 353ND. The objective is to see (after curing) how much the apparent glass transition temperature is increased over a room-temperature cure.
Ian and I moved some new hardware into the lab, shown in the below photos. It is from the shipment of loaned equipment recently returned by Whitman College.
The ZnSe lenses and windows were put in the CO2 drawer of the optics cabinet. The CO2 laser, AOM, and modulator drivers were left packaged in boxes underneath the large laser table.
Koji: QIL/TCS entrance flooding. Check your lab
Anchal: Can someone take a look at CTN too?
Koij: TCS needs more people @aidan
Koji: CTN ok
Aidan: On my way
Shruti: Cryo seems fine
Aidan: There was a leak in a pipe in the wall of B265A. It was coming from the building air conditioner condensation overflow. Facilities has fixed the pipe and is working on clean-up
I checked the lab this morning. It was dry and there wall was in the same state as yesterday.
11:29AM - Lab has flooded again this morning. I'm calling PMA. Looks to be the same issue as before.
Some photos of water and clean-up.
Summary: I came into the lab around 11:30AM and found water on the floor in the changing room outside QIL/TCS. Turns out the condesation overflow pipe from the AC blew out again. This time near the ceiling. Water was on the floor but also had sprayed a little onto the tool chest and East optical table. A few optics got wet on the table. Initial inspection looks like electronics were spared with the exception of the "broken" spectrum analyzer that was on the floor.
Facilities came in and cleaned up the water. A small amount got into QIL but stayed near the door as the lab floor slopes up from the door area. They fixed the pipe and were looking into whether there was a blockage cuasing this problem. PMA was notified and John Denhart is coordinating follow-up.
Triage effort: given the AC was still active, John and I strung a temporary tarp across the two tables to block any spray.
Stephen and I added a new valve to Dewar's vacuum system. This valve allows the flow of atmospheric pressure into the system. We added 3 components to the system which were the valve, an adapter, and a T-intersection. After added these components, we continued to pump down only the highlighted yellow and green area with Dewar being closed off. The system pumped down to .1 mTorr until we decided to close off the pump. Once we close the pump off, we noticed the pressure began to rise. We took apart the system again and looked over the O-rings. We came across one ring with a sticky and clear material surround the rim and another ring with a fiber on it. We proceeded to clean and reassemble the system, but ran into this same issue. We tried to find where this leak was by squirting isopropyl around each ring and posibbly so a slower rise in pressure, but had no luck.
Afterwards, I checked both T-intersections individually and came across the same rise in pressure after closing off the valve for both tests. We suspect this may have been normal beforehand?
We continued by putting it all back together and taking data of the pumpdown.
I bought this laser diode from Thorlabs today to try the current modulation trick Phil and I discussed last Friday.
It arrived on Friday.
The first pieces of the Bosch framing have arrived from Valin Corporation. These are just small pieces such as the fasteners and the gussets. There are no custom lengths of framing yet.
The details are in the attached Packing List. [1:25PM] I haven't verified that everything is there yet.
Another box of Bosch stuff arrived in my office. The packing list is attached
The custom pieces of the Bosch framing have arrived. Transportation is currently moving them downstairs to the lab. The packing list is attached.
The Thorlabs MFF001 flipper mirror recommended by Bram has arrived. The delivery note is attached.
Another box of Bosch framing parts arrived today. The delivery note is attached.