Now that the .db files were prepared, I wanted to test for errors. So I did the following:
All the Acromags are seen on the 192.168.114 subnet on c1iscaux3 - however, when I run the modbusIOC process, I see various errors in the logfile , so more debugging is required. Nevertheless, progress.
Update 2245: Turns out the errors were indeed due to a copy/paste error - I had changed the IP addresses for the ADCs from the .115 subnet c1susaux was using, but forgot to do so for the DACs and BIOs. Now, if I turn off the existing c1iscaux so that there aren't any EPICS clashes, the EPICS server initializes correctly. There are still some errors in the log file - these pertain to (i) the mbbo notation, which I have to figure out, and (ii) the fact that this version of EPICS, 7.0.1, does not support channel descriptions longer than 28 characters (we have several that exceed this threshold). I think the latter isn't a serious problem.
Getting closer... Note that I turned off the c1iscaux VME crate to prevent any EPICS server clashes. I will turn it back on tomorrow.
[Kruthi, Yehonathan, Gautam]
Today evening, Yehonathan and I aligned the MC2 cameras. As of now there are 2 GigEs in the MC2 enclosure. For the temporary GigE (which is the analog camera's place), we are using an ethernet cable connection from the Netgear switch in 1x6. The MC2 was misaligned and the autolocker wasn't able to lock the mode cleaner. So, Gautam disabled the autolocker and manually changed the settings; the autolocker was able to take over eventually.
Rana and I talked about some (genius) options for the large range DC bias actuation on the SOS, which do not require us to supply high-voltage to the OSEMs from outside the vacuum.
What we came up with (these are pretty vague ideas at the moment):
For the thermal option, I remembered that (exactly a year ago to the day!) when we were doing cavity mode scans, once the heaters were turned on, I needed to apply significant correction to the DC bias voltage to bring the cavity alignment back to normal. The mechanism of this wasn't exactly clear to me - furthermore, we don't have a FLIRcam picture of where the heater radiation patter was centered prior to my re-centering of it on the optic earlier this year, so we don't know what exactly we were heating. Nevertheless, I decided to look at the trend data from that night's work - see Attachment #1. This is a minute trend of some ETMY channels from 0000 UTC on 18 July 2018, for 24 hours. Some remarks:
Also see this elog by Terra.
Attachment #2 shows the results from today's heating. I did 4 steps, which are obvious in the data - I=0.6A, I=0.76A, I=0.9A, and I=1.05A.
In science, one usually tries to implement some kind of interpretation. so as to translate the natural world into meaning.
Bulb replaced. Projector is back on.
The control room UPS started making a beeping noise saying batteries need replacement. I hit the "Test" button and the beeping went away. According to the label on it, the batteries were last repalced in March 2016, so maybe it is time for a replacement, @Chub, please look into this.
I did a whole lot of hyperparameter tuning for convolutional networks (without 3d convolution). Of the results I obtained, I am attaching the best results below.
The lower the power of the error signal (difference between the true and predicted X and Y positions), essentially mse, on the test data, the better the performance of the model. Of the trained models I had, I chose the one with the lowest mse.
(Note: Attachment 6 and 7 present information regarding a fraction of the data. However, the behaviour remains the same for the rest of the data.)
Observations and analysis:
P.S. I will also try the 2D convolution followed by the 1D convolution thing now.
P.P.S. Gabriele suggested that I try average pooling instead of max pooling as this is a regression task. I'll give that a shot.
Experiment file: train_both.py
For some reason, rossa's Xdisplay won't start up anymore. This happened right after the UPS reset. Koji and I tried ~1.5 hours of debugging, got nowhere.
The database files for C1ISCAUX seem to work file - the exception being the mbbo channels for the CM board.
This was just a software test - the actual functionality of the channels will have to be tested once the Acromag crate has been installed in the rack. One change I had to make on the MEDM screen for the LSC PD whitening gains was to get rid of the "NMS" suffix on the EPICS channel names for whitening gain sliders/drop-down-menus. I suspect this has to do with the EPICS version we are using, 7.0.1. Furthermore, AS165 and POP55 no longer exist - I hold off removing them from the MEDM screen for the moment.
From the software point of view, the major steps are:
I am stopping the EPICS server on the new machine and restarting the old VME crate over the weekend.
I'm not able to get trends of the TM adjustment test that Rana had asked us to perform, from the dataviewer. It's throwing the following error:
Connecting to NDS Server fb (TCP port 8088)
Server error 7: connect() failed
datasrv: DataWrite failed: daq_send: Resource temporarily unavailable
T0=19-07-20-01-27-39; Length=600 (s)
No data output.
What channels are you trying to read?
Connecting to NDS Server fb (TCP port 8088)
Server error 7: connect() failed
datasrv: DataWrite failed: daq_send: Resource temporarily unavailable
T0=19-07-20-01-27-39; Length=600 (s)
No data output.
SnapPy scripts made to work on Pianosa.
Of course rossa was the only machine in the lab that could run the python scripts to interface with the GigE camera. And it is totally bricked now. Lame.
So I installed several packages. The key was to install pypylon - if you go to the basler webpage, pypylon1.4.0 does not offer python2.7 support for x86_64 architecture, so I installed pypylon1.3.0. Here are the relevant lines from the changelog:
gstreamer-plugins-bad-0.10.23-5.el7.x86_64 Sat 20 Jul 2019 11:22:21 AM PDT
gstreamer-plugins-good-0.10.31-13.el7.x86_64 Sat 20 Jul 2019 11:22:11 AM PDT
gstreamer-plugins-ugly-0.10.19-31.el7.x86_64 Sat 20 Jul 2019 11:20:08 AM PDT
gstreamer-python-devel-0.10.22-6.el7.x86_64 Sat 20 Jul 2019 10:34:35 AM PDT
pygtk2-devel-2.24.0-9.el7.x86_64 Sat 20 Jul 2019 10:34:34 AM PDT
pygobject2-devel-2.28.6-11.el7.x86_64 Sat 20 Jul 2019 10:34:33 AM PDT
pygobject2-codegen-2.28.6-11.el7.x86_64 Sat 20 Jul 2019 10:34:33 AM PDT
gstreamer-devel-0.10.36-7.el7.x86_64 Sat 20 Jul 2019 10:34:32 AM PDT
gstreamer-python-0.10.22-6.el7.x86_64 Sat 20 Jul 2019 10:34:31 AM PDT
gtk2-devel-2.24.31-1.el7.x86_64 Sat 20 Jul 2019 10:34:30 AM PDT
libXrandr-devel-1.5.1-2.el7.x86_64 Sat 20 Jul 2019 10:34:28 AM PDT
pango-devel-1.42.4-1.el7.x86_64 Sat 20 Jul 2019 10:34:27 AM PDT
harfbuzz-devel-1.7.5-2.el7.x86_64 Sat 20 Jul 2019 10:34:26 AM PDT
graphite2-devel-1.3.10-1.el7_3.x86_64 Sat 20 Jul 2019 10:34:26 AM PDT
pycairo-devel-1.8.10-8.el7.x86_64 Sat 20 Jul 2019 10:34:25 AM PDT
cairo-devel-1.15.12-3.el7.x86_64 Sat 20 Jul 2019 10:34:25 AM PDT
mesa-libEGL-devel-18.0.5-3.el7.x86_64 Sat 20 Jul 2019 10:34:24 AM PDT
libXi-devel-1.7.9-1.el7.x86_64 Sat 20 Jul 2019 10:34:24 AM PDT
pygtk2-doc-2.24.0-9.el7.noarch Sat 20 Jul 2019 10:34:23 AM PDT
atk-devel-2.28.1-1.el7.x86_64 Sat 20 Jul 2019 10:34:21 AM PDT
libXcursor-devel-1.1.15-1.el7.x86_64 Sat 20 Jul 2019 10:34:20 AM PDT
fribidi-devel-1.0.2-1.el7.x86_64 Sat 20 Jul 2019 10:34:20 AM PDT
pixman-devel-0.34.0-1.el7.x86_64 Sat 20 Jul 2019 10:34:19 AM PDT
libXinerama-devel-1.1.3-2.1.el7.x86_64 Sat 20 Jul 2019 10:34:19 AM PDT
libXcomposite-devel-0.4.4-4.1.el7.x86_64 Sat 20 Jul 2019 10:34:19 AM PDT
libicu-devel-50.1.2-15.el7.x86_64 Sat 20 Jul 2019 10:34:18 AM PDT
gdk-pixbuf2-devel-2.36.12-3.el7.x86_64 Sat 20 Jul 2019 10:34:17 AM PDT
pygobject2-doc-2.28.6-11.el7.x86_64 Sat 20 Jul 2019 10:34:16 AM PDT
pygtk2-codegen-2.24.0-9.el7.x86_64 Sat 20 Jul 2019 10:34:15 AM PDT
Camera server is running on a tmux session on pianosa. But it keeps throwing up some gstreamer warnings/errors, and periodically (~every 20 mins) crashes. Kruthi tells me that this behavior was seen on Rossa as well, so whatever the problem is, doesn't seem to be because I missed out on installing some packages on pianosa. Moreover, if the server is in fact running, I am able to take a snapshot - but the camera client does not run.
See Attachment #2.
Make the MSE a subplot on the same axes as the time series for easier interpretation.
Do I need to provide any more details here?
Describe the training dataset - what is the pk-to-pk amplitude of the beam spot motion you are using for training in physical units? What was the frequency of the dither applied? Is this using a zoomed-in view of the spot or a zoomed out one with the OSEMs in it? If the excursion is large, and you are moving the spot by dithering MC2, the WFS servos may not have time to adjust the cavity alignment to the nominal maximum value.
What is the minimum detectable motion given the CCD resolution?
see attachment #4.
I wrote what I think is a handy script to observe if the frames are saturated. I thought this might be handy for if/when I collect data with higher exposure times. I assumed there was no saturation in the images because I'd set the exposure value to something low. I thought it'd be useful to just verify that. Attachment #3 has log scale on the x axis.
What is the significance of Attachment #6? I think the x-axis of that plot should also be log-scaled.
I'm running the MC2 loss map scripts on pianosa now. The camera server is throwing an error and is not grabbing snapshots :(
Update: I finished taking the readings for MC2 loss map. I couldn't get the snapshots with the script, so I manually took some 4-5 pictures.
Can you please be more specific about what the error is? Is this the usual instability with the camera server code? Or was it something new?
The camera server is throwing an error and is not grabbing snapshots :(
DATED, SEE ELOG14941 for the most up-to-date info on latch.py.
I wrote (/cvs/cds/caltech/target/c1iscaux3/latch.py) and tested the logic illustrated in Attachment #1. Results of a test are shown in Attachment #2, the various channels change as expected. Note that for negative values of the gain channel, the corresponding "BITS" channel will take on values like 65536 - this is because the mbboDirect data type is a 16 bit data type, and presumably the MSB is the sign bit. A bit mask is applied to this channel before the actual BIO unit bits are set - we should verify that the correct behavior happens, but I don't immediately see any problems.
To me, this is a robust logic, but it will benefit from more sets of eyes giving it a look over. The idea is to run this continuously on the Supermicro machine.
Apart from this, I also fixed some errors in the mbboDirect record syntax - so now I am able to start up the EPICS server without it throwing any error messages. It remains to verify that changing an EPICS gain slider results in the appropriate gain bits being flipped in the correct way (on the hardware side, I think the correct behavior is happening on the software end). For this testing, I turned off the old c1iscaux crate at ~10am, and started up the server on c1iscaux3. I am reverting to the nominal config now (~1pm).
Further testing will require the wiring inside the Acromag chassis to be completed. This should be the priority task for next week.
*Update 1130 22 July 2019: I've now installed the required dependencies on c1iscaux3 and setup the latch.py script to run as a systemctl process dependent on modbusIOC.service.
The camera server keeps throwing the error: failed to grab frames. Milind suggested that it might a problem with the ethernet cable, so I even unplugged it and connected it again; it still had the same issue. One more thing I noticed was, it does take snapshots sometimes with the terminal command caput C1:CAM-ETMX_SNAP 1, but produces a segmentation fault when ezca.Ezca().write(C1:CAM-ETMX_SNAP, 1) ezca.Ezca().write(CAM-ETMX_SNAP, 1) is used via ipython. When the terminal command also fails to take snapshots, I noticed that the SNAP button on the GigE medm screen remains on and doesn't switch back to OFF like it is supposed to.
I think ezca.Ezca().write() takes the string "CAM-ETMX_SNAP" as an argument and not C1:CAM-ETMX_SNAP. See this, line 47. Are you sure this is not the problem?
The camera server keeps throwing the error: failed to grab frames. Milind suggested that it might a problem with the ethernet cable, so I even unplugged it and connected it again; it still had the same issue. One more thing I noticed was, it does take snapshots sometimes with the terminal command caput C1:CAM-ETMX_SNAP 1, but produces a segmentation fault when ezca.Ezca().write(C1:CAM-ETMX_SNAP, 1) is used via ipython. When the terminal command also fails to take snapshots, I noticed that the SNAP button on the GigE medm screen remains on and doesn't switch back to OFF like it is supposed to.
I found the MC2 face camera disabled(?) and the MC servo board input turned off. I turned the MC locking back on but I don't see any camera image yet.
"bricked" is to mean that it has the functionality of a brick and can be tossed. But rossa seems to have just gotten some software config corruption. I spent a couple hours reinstalling SL7 today as per my previous elog notes and the X display seems to work as before.
i.e. it was fine with the default setup, except for the ole "X chrashes if the mouse goes to left side of screen". As before, I
left side of screen is safe again
This time I installed SL7.6 and followed the K Thorne wiki. But its having trouble installing cds-root because it can't find root.
Somebody changed the settings on painosa without elogging anything about it. Why does this keep happening? I thought the point of the elog was to communicate. I think there are sufficient number of problems in the lab without me having to manually reset the control room workstation settings every week. Please make an elog if you change something.
In my script I have used "CAM-ETMX_SNAP" only; while entering it in the elog I made a mistake, my bad!
The MC2 has 2 GigE cameras right now. I'll put back the analog asap.
On Friday, Milind and I performed the pitch adjustment test Rana had asked us to do. Only 1 blue beam in case of ITMX and two in case of ETMY, ETMX and ITMY were accessible. Milind (of mass 72 kg as of 10 May 2019) stood on each of the accessible blue beams of the test mass chambers for one minute and I recorded the corresponding gps time. Before moving to the next beam, we spared more than a minute for relaxation after the standing end time. Following are the recorded gps times.
Standing start time (gps)
Standing end time (gps)
PS: For each blue beam relaxation time ~ 1 min after the standing end time
My goal tonight was to lock the PSL frequency to be resonant in the XARM cavity, using the PSL+EX beat as the error signal. I was not successful - mainly, I was plagued by huge BR mode coupling in the error signal, and I could not enable the BR notch filter in the control loop without breaking the lock. Need to think about next steps.
Anyway, now that I have a workable set of settings that gets me close to the ALS lock of the XARM, I expect debugging to proceed faster.
Update 2019 July 23: I looked at the control loop shape today, see Attachment #3. I'm not sure I understand why the "BounceRoll" filter in this filter bank looks like a resonant gain rather than a notch, as it does for the Oplev or SUSPOS loops for example - don't we want to not actuate at these frequencies because the reason the signal exists is because of the imperfect OSEM/magnet positioning? This does not explain the spectrum shown in Attachment #2 however, as that filter was disabled.
This afternoon Gautam and I assessed what to do about restoring the GigE camera software. Here's what I propose:
I've started resolving the many dependencies of this code on rossa. The idea is to get a working environment on one workstation, then generate requirements files that can be used to set up the rest of the machines. I believe the dependencies have all been installed. However, many of the packages are newer versions than before, and this seems to have broken SnapPy. I'll continue debugging this tomorrow.
I succeeded in locking the PSL frequency to the XARM cavity length, with 9 pm RMS (Attachment #1) motion below 1 kHz, by actuating on MC2 to change the IMC length. The locks were pretty stable (~20 minutes) - the dominant cause of lockloss was the infamous ETMX drifting problem.
My main motivation here is to make some measurements and investigate the SoCal idea using a toy system, i.e. a single arm cavity controlled using ALS, so that's what Craig and I will attempt next.
I have been trying a couple of HDR algorithms, all of them seem to give very different results. I don't know how suitable these algorithms are for our purpose, because they are more concerned with final display. I'm attaching the HDR image I got by modifying Jigyasa's code a bit (this image has been be modified further to make it suitable for displaying). Here, I'm trying compare the plots of images that look similar. The HDR image has a dynamic ratio of 700:1
PS: 300us_image.png file actually looks very similar to HDR image on my laptop (might be an issue with elog editor?). So I'm attaching its .tiff version also to avoid any confusion.
Summary: I calibrated MC2 pitch and yaw offsets to spot position in mm. Here's what I did:
Results: In the pitch/yaw vs pitch_offset/yaw_offset graph attached,
Moved the unstick.py code to the ifotest repository here. It now handles signals like those generated by Ctrl-C and so forth. It can still be run as python unstick.py <machine1> <machine2> etc.
I upgraded Pylon, the C/C++ API for the GigE cameras, to the latest release, 5.2.0. It is installed in the same location as before, /opt/rtcds/caltech/c1/scripts/GigE/pylon5, so environment variables do not change. The old version, 5.0.12, still exists at opt/rtcds/caltech/c1/scripts/GigE/backup_pylon5.
The package contains a GUI application (/bin/PylonViewerApp) for streaming video. The old version supports saving still images, but Milind discovered that the new version supports saving video as well. This required installing a supplementary package supporting MPEG-4 output.
Basler's GUI application is launched from the terminal using the alias pylon. I've tested it and confirm it can save both videos and still-image formats. I recommend to also try grabbing images using this program and check the bit resolution. It would be a useful diagnostic to know whether it's a bug in Joe B.'s code or something deeper in the camera settings.
At the lab meeting today, Rana suggested that I use the Pylon app to collect more data if that's what I need. Following this, Jon helped me out by updating the pylon version and installing additional software to record video. Now I am collecting data at
Consequently I have dithered the MC2 optic from around 9:00 PM.
Since there are multiple SURF projects that rely on the cameras:
My changes were necessary because the grabHDR.py script was throwing python exceptions, whereas it was running just fine before Jon's changes. We can move the "new_*" dirs to the default once the SURFs are gone.
Let's freeze the camera software config in this state until next week.
Somehow I never got around to doing the pixel sum thing for the new real data from the GigE. Since I have to do it for the presentation, I'm putting up the results here anyway. I've normalized this and computed the SNR with the true readings.
SNR = (power in true readings)/ (power in error signal between true and predicted values)
Attachment #2 is SNR of best performing CNN for comparison.
I'll keep developing the camera server on a parallel track using the "new_..." directory naming convention. One thing I forgot to note is that the new pylon/pypylon packages require Python 3, so will not work with any of the 2.7 scripts. All of the environment I need to set up is exclusively Python 3. I won't change anything in the Python 2.7 environment in current use.
Also, I found the source of the bit resolution issue: Joe B's code loads a set of initialization parameters from a config file. One of them is "Frame Type = Mono8" which sets the dynamic range of the stream. I'll look into how this should be changed.
These spectra were taken with the arm cavity length locked to the PSL frequency using POX as an error signal, and the EX laser frequency locked to the XARM cavity length by the analog PDH servo at EX, so there is no feedback control with the ALS beat signal as an error signal.
I brought one CPU (Dell T3500) and one 28" monitor from Mike Pedraza's office in Downs to the 40m. It is on Steve's desk right now, pending setup. The machine already has Solidworks and Altium installed on it, so we can set it up at our leisure. The login credentials are pasted on the CPU with a post-it should anyone wish to set it up.
1. X arm is totally misaligned in order to measure the Y arm loss using the reflection method. Each measurement round consists of measuring the reflected power when the Y arm is aligned and when it is misaligned.
2. The measurement script used is /scripts/lossmap_scripts/armLoss/measureArmLoss.py. It generates a log file in the /logs folder specifying the alignment and misalignment times.
3. The data extraction script dlData.py processes the raw data in the log file and creates a hdf5 file in the /Data folder conataining the data of the measurement it self.
4. dlData.py labels the the aligned and misaligned datas incorrectly when the number of measurement is odd. I use only even number of measurements then.
5. In order to clip the chaotic transition between the aligned and misaligned states I use tDur attribute smaller than the actual sleep time used in the measurement script itself.
6. plotData.py (written by Gautam) and AnalyzeLossData.ipynb (written by me) can be used to calculate the loss and to plot some analyses (see https://nodus.ligo.caltech.edu:8081/40m/14568). They give roughly the same answer. The descripancy can be explained by the different modulation and ITM transmissions used.
7. I take a measurement of 8 repeatitions. I plot the measured reflected power alternating between the aligned and misaligned states.
I find that the reflected power is repeatable to within 1%.
This is consistent with the transmission data plotted here which is also repeatable to within 1%.
8. I take an overnight measurement of 100 repeatitions.
We need to determine the geometry (= round-trip length and RoC of curved mirrors) of the OMC cavities for the 40m BHD experiment. Sticking to the aLIGO design of a 4 mirror bowite cavity with 2 flat mirrors and 2 curved mirrors, with a ~4deg angle of incidence, we need to modify the parameters for the 40m slightly on account of our different modulation frequencies. I've setup some infrastructure to do this analytically - even if we end up doing this with Finesse, it is useful to have an analytic calculation to validate against (also not sure if Finesse can calculate HOMs up to order 20 in a reasonable time, I've only seen maxtem 8).
Attachment #1: Heatmap of the OMC transmission for the following fields:
The code used for the ABCD matrix calcs have been uploaded to the BHD modeling GIT (but not the one for making this plot, yet, I need to clean it up a bit). Some design considerations have also been added to our laundry list on the 40m wiki.
Chub brought the replacement Supermicro we ordered to the 40m today. I stored it at the SW entrance to the VEA, along with the other Supermicro. At the time of writing, we have, in hand, two (unused) Supermicro machines. One is meant for EY and the other is meant for c1psl/c1iool0. DDR3 RAM and 120 GB SSD drives have also been ordered, but have not yet arrived (I think, Chub, please correct me if I'm wrong).
Update 20190802: The DDR3 RAM and 120 GB SSD drives arrived, and are stored in the FE hardware cabinet along the east arm. So at the time of writing, we have 2 sets of (Supermicro + 120GB HD + 4GB RAM).
We should ask Chub to reorder several more SuperMicro rackmount machines, SSD drives, and DRAM cards. Gautam has the list of parts from Johannes' last order.
4 deg is not an optimized number optimized for criteria, but to keep the cavity short width to 0.1m. But the justification of 4deg is found in Section 3 and 4 of T1000276 on Page 4.
Question for Koji: how is the aLIGO OMC angle of incidence of ~4 degrees chosen? Presumably we want it to be as small as possible to minimize astigmatism, and also, we want the geometric layout on the OMC breadboard to be easy to work with, but was there a quantitative metric? Koji points out that the backscatter is also expected to get worse with smaller angles of incidence.
I'd like to confirm that the IR ALS scheme will work for locking. The X-arm performance so far has been encouraging. I want to repeat the characterization for the Y arm. So I inspected the layout on the EY table, and made a list of characterization tasks. The current EY beam routing is difficult to work with, and it will definitely benefit from a re-do. However, I don't know how much time I want to spend re-doing it, so for a start, I will just try and couple some amount of light into a fiber and bring it to the PSL table, and see what noise performance I get.
Attachment #1: Photo of the current beam layout. The powers indicated were measured with the Ophir power meter.
Attachment #2: A candidate mode-matching solution, given the constraints outlined above. It isn't great, with only 85% modematching even theoretically possible. The lenses required are also pretty fast lenses. But I think it's the best possible without a complete overhaul of the EY layout. I'm still waiting for the lens kit to arrive, but as soon as they get here, I will start this work.
I've put the analog camera back and disconnected the 151 unit GigE. But I ran out of time and wasn't able to replace the beamsplitter. I've put all the equipments back to the place where I took them from. The chopper and beam dump mount, that Koji had got me for the scatterometer, are kept outside, on the table I was working on earlier, in the control room. The camera lenses, additional GigEs, wedge beamsplitter, 1050nm LED and all related equipments are kept in the GigE box. This box was put back into CCD cameras' cabinet near the X arm.
Note: To clean stuff up, I had entered the lab around 9.30pm on Monday. This might have affected Yehonathan's loss measurement readings (until then around 57 readings had been recorded).
Sorry for the late update.
We run a loss measurement on the Y arm with 50 repetitions.
I want to collect some data with the arms locked to investigate the possibility/usefullness of having seismic feedforward implemented for the arms (it is already known to help the IMC length and PRC angular stability at low frequencies). To facilitate diagnostics I modified the file /users/Templates/Seismic/Seismic_vs_TRXTRYandMC.xml to have the correct channel names in light of Lydia's channel name changes in 2016. Looking at the coherence data, the alignment of the cartesian coordinate system of the Seismometers at the ends and the global interferometer coordinate system can be improved.
I don't know if for the MISO filter design if there is any difference in using TRX/TRY as the target, or the arm length control signal.
Data collection started at 1249018179. I've setup a script running in a tmux shell to turn off the LSC enable in 2 hours.
I analyze the 100 reps loss measurement of the Y arm using the AnalyzeLossData.ipynb notebook.
The mean of the measured loss is ~ 100ppm and the variation between the repititions is ~ 27%.
In the real measurement the misaligned and locked states are repeatedly switched between each other. I plot the misaligned and locked PD readings seperately over time.
There seems to be a drift that is correlated between the two readings. This is probably a drift in the power after the MC2. To verify, I plot the ratio between those readings and find no apparent drift:
The variation in the ratio is less than 1%. The loss figure, computed to be 1 minus this ratio times a big number, give a much worse variation. I plot the histogram of the loss figure at each repitition (excluding extremely bad measurements):
The mean is ~ 100ppm. And the variation is ~ 27%.
We hypothesize that the systematic error in the loss measurement can come from the fact that the requirement on the alignment of the cavity mirrors is not stringent enough.
We repeat the loss measurement with 50 measurements. This time we change the thresholds for the error signals of the dither-align in the measureArmLoss.py file from 0.5 to 0.3.
We repeat the analysis done before:
We plot the reflected power of the two states on top of each other:
This time it appears there was no drift. The histogram of the loss measurement:
The mean is 104ppm and the variation is 27%.
What I notice this time is that the PD readings in the aligned and misaligned states are anti-correlated. This is also true in the previous run (where there was drift) when looking in the short time scales. I plot several time series to demonstrate:
I wonder what can cause this behaviour.