Couple IR light into fiber with good MM at EY
I grab 2 hours of the PD measurements using dlData_simple.ipynb in the misaligned state.
I get pretty much a normally distributed reading without drifts (Attachements 1 and 2).
The error in the reading is ~ 0.5%.
I am pretty sure this amount of noise is enough to explain the big noise in the Loss figure measurement.
The reason is that the loss formula is #(1-P_Locked/P_Misaligned+T1)-T2) where T1 and T2 are the transmissions of the ITM and ETM.
The average of the ratio P_Locked/P_Misaligned is ~ 1.01 for a loss figure of ~ 100ppm.
The standard deviation of the ratio is ~ 1% which is also the standard deviation of the expression in the brackets.
The average of this experssion however is ~ 0.01.
The reduction of the mean amplifies the error in the loss measurments by a factor of a few 10s!
The requirement on the phase noise on the direct backscatter from the OMC back into the SRM is that it be less than @ 100 Hz, for a safety factor (arbitrarily chosen) of 10 (= 20dB below unsqueezed vacuum). Assuming 5 optics between the OMC and SRM which contribute incoherently for a factor of sqrt(5), and assuming a total of 1 ppm of the LO power to be backscattered, we need the suspensions to be moving @ 100 Hz. This seems possible to realize with single stage suspensions - I assume we get f^4 filtering from the pendulum at 100 Hz, and that there is an additional 80 dB attenuation (from the stack) of the assumed 1 micron/rtHz motion at 100 Hz, for an overall 160 dB attenutaiton, yielding 10^-14 m/rtHz at 100 Hz.
This is the same calculation as I had posted a couple of months ago (see elog that this is a reply to), except that Koji pointed out that the LO power is expected to dominate the (carrier) power incident on the OMC cavity(ies). So the more meaningful comparison to make is to have the x-axes of the plots denote the backscatter fraction, rather than the LO power. One subtlety is that because the phase of the scattered field is random, the displacement-noise induced phase noise could show up in the amplitude quadrature. I think that in these quadrature field amplitude units, the RIN and phase noise are directly comparable but I might have missed a factor of 2*pi. But in the worst case, if all the phase noise shows up in the amplitude quadrature, we end up being only ~10dB below unsqueezed vacuum (for 1 ppm backscatter).
For the requirement on the noise in the intensity quadrature - I think this is automatically satisfied because the RIN requirement on the incident LO field is in the mid 10^-9 1/rtHz regime.
ML2013 is unable to open Simulink on any of the workstations. We decided to make the default version of Matlab R2015b (the default of the version of RCG we are using).
I commenced the procedure of the migration, starting with making a tagged commit of the current running simulink models. A local backup was also made, plus we have the usual chiara-based backup so I think we're in good hands.
Currently the branch and tag are protected - once we verify that everything works as expected post migration, I will open it up. I changed the directory structure of the models, need to confirm that the rtcds compilers don't have any hardcoded paths which may break due to my change.
The symlink to Matlab R2013 was deleted and a new symlink to R2015b was made. I activated the license using the Caltech campus license. Now running matlab from shell starts up R2015b . Simulink even works 😲 .
cdsutils is not working on rossa.
Import cdsutils produces this error:
In : import cdsutils
OSError Traceback (most recent call last)
<ipython-input-2-949babce8459> in <module>()
----> 1 import cdsutils
/ligo/apps/linux-x86_64/cdsutils-480/lib/python2.7/site-packages/cdsutils/__init__.py in <module>()
---> 55 import awg
56 except ImportError:
/ligo/apps/linux-x86_64/cdsutils-480/lib/python2.7/site-packages/cdsutils/awg.py in <module>()
---> 32 import sys, numpy, awgbase
33 from time import sleep
34 from threading import Thread, Event, Lock
/ligo/apps/linux-x86_64/cdsutils-480/lib/python2.7/site-packages/cdsutils/awgbase.py in <module>()
17 libawg = CDLL('libawg.so')
18 libtestpoint = CDLL('libtestpoint.so')
---> 19 libSIStr = CDLL('libSIStr.so')
/ligo/apps/anaconda/lib/python2.7/ctypes/__init__.pyc in __init__(self, name, mode, handle, use_errno, use_last_error)
365 if handle is None:
--> 366 self._handle = _dlopen(self._name, mode)
368 self._handle = handle
OSError: libSIStr.so: cannot open shared object file: No such file or directory
We check for unexpected drifts in the PD reading (clipping and such). We put a pickoff mirror where the PD used to be and place the PD at the edge of the table such that the beam is focused on it (see attachment).
The arms are completley misaligned. We note the time of start of measurement to be 1249086917.
The VEA laptop asia was configured to be able to connect to too many WiFi networks - it was getting conflicted in its default position at the vertex and trying to hop between networks, for some reason trying to connect to networks that had poor signal strength. I deleted all options from the known networks except 40MARS. Now the network connection seems much more stable and reliable.
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.
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%.
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.
We run a loss measurement on the Y arm with 50 repetitions.
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.
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.
vanna --> QIL.
gautam 20190804: The GPIB module + power supply were returned to me by Duo ~5pm today at the 40m.
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.
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.
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.
One of the biggest challenges in LIGO is reducing the alignment control noise. If you haven't worked on it for at least a few years, it probably seems like a trivial problem. But all versions of LIGO since 2001 have been limited by ASC noise below ~50 Hz.
I think the 40m IMC is a good testbed for us to try a few approaches towards mitigating this noise in LIGO. The following is a list of steps to take to get there:
I think that steps 1-6 are well within our existing experience, but we should do it anyway so as to reduce the IMC beam motion at low frequencies, and also to reduce the 10-100 Hz frequency noise as seen by the rest of the interferometer.
Steps 7-8 are medium hard, but we can get some help from the CSWG in tackling it.
Step is pretty tough, but I would like to try it and also get some help from MLWG and CSWG to address it.
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.
I've started setting up the last new rackmount SuperMicro as a dedicated server for the GigE cameras. The new machine is currently sitting on the end of the electronics test bench. It is assigned the hostname c1cam at IP 192.168.113.116 on the martian network. I've installed Debian 10, which will be officially supported until July 2024.
I've added the /cvs/cds NFS mount and plan to house all the client/server code on this network disk. Any dependencies that must be built from source will be put on the network disk as well. Any dependencies that can be gotten through the package manager, however, will be installed locally but in an automated way using a reqs file.
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.
I think rana did some more changes to this workstation to make it useful for commissioning activities - but the MEDM screens were still white blanks. The problem was that the firewalld wasn't disabled (last two steps of the KThorne setup wiki). I disabled it. Now donatella can run MEDM, ndscope and StripTool. DTT doesn't work to get online data because of a "Synchronization Error", I'm not bothering with this for now. I think Kruthi successfully demonstrated the fetching of offline data with DTT.
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'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.
Since there are multiple SURF projects that rely on the cameras:
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.
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.
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.
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.
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.
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,
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.
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.
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.
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.
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
The MC2 has 2 GigE cameras right now. I'll put back the analog asap.
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.
In my script I have used "CAM-ETMX_SNAP" only; while entering it in the elog I made a mistake, my bad!
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.
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.
"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.
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.
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.
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.
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.