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ID Date Author Type Categoryup Subject
  8490   Thu Apr 25 04:10:09 2013 JenneUpdateLockingMICH_CTRL drifting away??

Koji is elogging separately of his exploration of different configurations.  The lock stretch that I'm looking at here uses the same parameters as Koji had for PRMI sb lock, using AS55Q for MICH and REFL33I for PRCL, with MICH gain of -0.8 and PRCL gain of 0.05 .

All of these plots are the same few second lock stretch, with different zooming.  Jamie's super-sweet getdata python script only accepts integers for the start time and duration parameters, so lots of this zooming happened by hand, but I tried to always keep the time axis aligned within each screenshot.  Sometimes the plot axis labels say differently, but they're lying to you.

Plot 1:  gps start time is 1050915916, duration = 6 seconds.  Overall view of the lock stretch.


Plot 2:  gps start time is 1050915921, duration = 1 second.  We're looking at the lockloss that happens at the left side of the plots.


Plot 3:  zoomed in (along the time-axis) version of plot 2, so much shorter time duration.  Some zooming on y-axes.


Plot 4:  zoomed in (along y-axes) version of plot 2.


It seems to me from these plots that maybe MICH CTRL is drifting away?  It seems like we lose the MICH lock, and that destroys the whole thing. 

Koji made some comments to me earlier, regarding his work this evening, that the MICH signal quality is poor in general, and that we should calculate/think about changing our schnupp asymmetry. 

  8535   Tue May 7 10:30:32 2013 KojiUpdateLockingPRM yaw responsible for RIN


BS is contributing a little bit, but PRM is clearly contributing


While the peak in the PRM OPLEV was more than 10 times higher than the spectrum level without the excitation,
we only saw small peaks in the RIN spectra. This suggests that the PRM angular motion did not contribute to the RIN spectra.

You should divide the POP110I and POPDC spectra by 400 and 450, which was the DC values of these channels, in order to convert them into RIN (1/rtHz)
The OPLEV spectra is calibrated to be urad/rtHz (is this true?) so you can obtain the conversion factor from OPLEV to RIN (1/urad)
by matching the peaks. This way you make a angular noise projection.


I think that I need to install one of the T240's on the new granite slab, and see what kind of coherence we have between seismic and PRM yaw motion, and if FF can get rid of it.

Yes we should do that. BTW what should be pushed?

  8557   Thu May 9 02:19:53 2013 JenneUpdateLocking50% BS installed in POP path

Koji had the good idea of trying to measure the motion of the POP beam, and feeding that signal to PRM yaw to stabilize the motion.  To facilitate this, I have installed a 50% beam splitter before the POP 110/22 PD (so also before the camera). 

Before touching anything, I locked the PRM-ITMY half-cavity so that I had a constant beam at POP.  I measured the POP DC OUT to be 58.16 counts.  I then installed a 1" 50% BS, making sure (using the 'move card in front of optic while watching camera' technique) that I was not close to clipping on the new BS.  I then remeasured POP DC OUT, and found it to be 30.63.  I closed the PSL shutter to get the dark value, which was -0.30 .  This means that I now have a factor of 0.53 less light on the POP110/22 PD.  To compensate for this, I changed the values of the power normalization matrix from 0.01 (MICH) to 0.0189, and 100 (PRCL) to 189.

After doing this, I restored the ITMX and am able to get several tens of seconds of PRMI lock (using AS55Q and REFL33I). 

I found several QPDs in the PD cabinet down the Y arm, but no readout electronics.  The QPD I found is D990272.  I don't really want to spend any significant amount of time hacking something for this together, if Valera can provide a QPD with BNC outputs. For now, I have not installed any DC PD or razor blade (which can be a temporary proxy for a QPD, enough to get us yaw information).


  8564   Mon May 13 18:44:04 2013 JenneUpdateLockingprcl angular motion

I want to redo this estimate of where RIN comes from, since Den did this measurement before I put the lens in front of the POP PD. 

While thinking about his method of estimating the PR3 effect, I realized that we have measured numbers for the pendulum frequencies of the recycling cavity tip tilt suspensions. 

I have been secreting this data away for years.  My bad.  The relevant numbers for Tip Tilts #2 and #3 were posted in elog 3425, and for #4 in elog 3303.  However, the data for #s 1 and 5 were apparently never posted.  In elog 3447, I didn't put in numbers, but rather said that the data was taken.

Anyhow, attached is the data that was taken back in 2010.  Look to elog 7601 for which TT is installed where. 


Conclusion for the estimate of TT motion to RIN - the POS pendulum frequency is ~1.75Hz for the tip tilts, with a Q of ~2.

Attachment 1: TT_Q_measurements.pdf
TT_Q_measurements.pdf TT_Q_measurements.pdf
  14448   Mon Feb 11 19:53:59 2019 gautamSummaryLoss MeasurementLoss measurement setup

To measure the Y-arm loss, I decided to start with the classic reflectivity method. To prepare for this measurement, I did the following:

  1. Placed a PDA 520 in the AS beam path on the AS table.
  2. Centered AS beam on above PDA 520.
  3. Monitored signal from PDA520 and the MC transmission simultaneously in the single-bounce from ITMY config (i.e. all other optics were misaligned). Convinced myself that variations in the two signals were correlated, thus ruling out in this rough test any interference from ghost beams from ITMX / PRM etc.
  4. For the DAQ, I decided to use the two ALS Y arm channels in 1Y4, mainly because we have some whitening electronics available there - the OMC model would've been ideal but we don't have free whitening channels available there. So I ran long BNCs to the rack, labelled them.
  5. It'd be nice to have these signals logged to frames, so I added DQ-channels for the IN1 points of the BEATY_FINE filters, recording at 2048 Hz for now. Of course this necessitated restart of the c1lsc model, which caused all the vertex FEs to crash, but the reboot script brought everything back smoothly.
  6. Not sure what to make of the shape of the spectrum of the AS photodiode, see Attachment #1 - looks like some kind of scattering shelf but I checked the centering on the PD itself, looks good. In any case, with the whitening gains I'm using, seems like both channels are measuring above ADC noise.
  7. Found that the existing misalignment to the ETMY does not eliminate signatures of cavity flash in the AS photodiode. So I increased the amount of misalignment until I saw no evidence of flashes in the reflected photodiode.
  8. Johannes' old scripts didn't work out of the box - so I massaged it into a form that works.
  9. Re-centered Oplevs to try and keep them as well centered in the linear range as possible, maybe the DC position info from the Oplevs is useful in the analysis.

I'm running a measurement tonight, starting now (~1130PM), should be done in ~1hour, may need to do more data-quality improvements to get a realistic loss number, but I figured I'd give this a whirl.

I'm rather pleased with an initial look at the first align/misalign cycle, at least there is discernable contrast between the two states - Attachment #2. The data is normalized by MC transmission, and then sig.decimated by x512 (8**3).

Attachment 1: DQcheck.pdf
Attachment 2: initialData.pdf
  14449   Tue Feb 12 18:00:32 2019 gautamSummaryLoss MeasurementLoss measurement setup

Another arm loss measurement started at 6pm.

  14450   Tue Feb 12 22:59:17 2019 gautamSummaryLoss MeasurementY arm loss


There are still several data quality issues that can be improved. I think there is little point in reading too much into this until some of the problems outlined below are fixed and we get a better measurement.


  1. Mainly, we are plagued by the inability of the ASS system to get back to the good transmission levels - I haven't done a careful diagnosis of the servo, but the ITM PIT output always seems to run away. As a result, the later measurements are poor, as can be seen in Attachment #2.
  2. For this reason, we can't easily sample different spot positions on the ETM.
  3. Data processing:
    • Download AS reflection and MC transmission DQ channels
    • Take their ratio
    • Downsample to 4 Hz by repeated application of scipy.signal.decimate by a factor of 8 each time, thrice, with the filtfilt option enabled
  4. Attachment #1 and #2 are basically showing the same data - the former collects all locked (top left) and misaligned (top right) data segments and plots them with the corresponding TRY values in the bottom row. The second plot shows a pseudo-continuous time series (pseudo because the segments transitioning from locked to misaligned states have been excised).

As an interim fix, I'm going to try and use the Oplevs as a DC reference, and run the dither alignment from zero each time, as this prevents the runaway problem at least. Data run started at 11:20 pm.

Attachment 1: segmented.pdf
Attachment 2: consolidated.pdf
  14451   Wed Feb 13 02:28:58 2019 gautamSummaryLoss MeasurementY arm loss

Attachment #1 shows estimated systematic uncertainty contributions due to 

  1. ITM transmission by +/- 0.01 % about the nominal value of 1.384 %
  2. ETM transmission of +/- 3 ppm about the nominal value of 13.7 ppm
  3. Mode matching efficiency into the cavity by +/- 5% about the nominal value of 92%.

In all the measurements so far, the ratio seems to be < 1, so this would seem to set a lower bound on the loss of ~35 ppm. The dominant source of systematic uncertainty is the 5% assumed fudge in the mode-matching

To do: 

  1. Account for uncertainties on modulation depths
  2. To estimate if the amount of fluctuation we are seeing in the reflected signal even after normalizing by the MC transmission, get an estimate of statistical uncertainty in the reflected power due to 
    • Pointing jitter - is there some spec for the damped angular displacement of the TT1/TT2?
    • Cavity length in-loop residual

Bottom line: I think we need to have other measurements and simultaenously analyse the data to get a more precise estimate of the loss.

Attachment 1: systUnc.pdf
  14454   Thu Feb 14 21:29:24 2019 gautamSummaryLoss MeasurementInferred Y arm loss


From the measurements I have, the Y arm loss is estimated to be 58 +/- 12 ppm. The quoted values are the median (50th percentile) and the distance to the 25th and 75th quantiles. This is significantly worse than the ~25 ppm number Johannes had determined. The data quality is questionable, so I would want to get some better data and run it through this machinery and see what number that yields. I'll try and systematically fix the ASS tomorrow and give it another shot.

Model and analysis framework:

Johannes and I have cleaned up the equations used for this calculation - while we may make more edits, the v1 of the document lives here. The crux of it is that we would like to measure the quantity \kappa = \frac{P_L}{P_M}, where P_{L(M)} is the power reflected from the resonant cavity (just the ITM). This quantity can then be used to back out the round-trip loss in the resonant cavity, with further model parameters which are:

  1. ITM and ETM power transmissivities
  2. Modulation depths and mode-matching efficiency into the cavity
  3. The statistical uncertainty on the measurement of the quantity \kappa, call it \sigma_{\kappa}

If we ignore the 3rd for a start, we can calculate the "expected" value of \kappa as a function of the round-trip loss, for some assumed uncertainties on the above-mentioned model parameters. This is shown in the top plot in Attachment #1, and while this was generated using emcee, is consistent with the first order uncertainty propagation based result I posted in my previous elog on this subject. The actual samples of the model parameters used to generate these curves are shown in the bottom. What this is telling us is that even if we have no measurement uncertainty on \kappa, the systematic uncertainties are of the order of 5 ppm, for the assumed variation in model parameters.

The same machinery can be run backwards - assuming we have multiple measurements of \kappa, we then also have a sample variance, \sigma_{\kappa}. The uncertainty on the sample variance estimator is also known, and serves to quantify the prior distribution on the parameter \sigma_{\kappa} for our Monte-Carlo sampling. The parameter \sigma_{\kappa} itself is required to quantify the likelihood of a given set of model parameters, given our measurement. For the measurements I did this week, my best estimate of \kappa \pm \sigma_{\kappa} = 0.995 \pm 0.005. Plugging this in, and assuming uncorrelated gaussian uncertainties on the model parameters, I can back out the posterior distributions.

For convenience, I separate the parameters into two groups - (i) All the model parameters excluding the RT loss, and (ii) the RT loss. Attachment #2 and Attachment #3 show the priors (orange) and posteriors (black) of these quantities. 


  1. This particular technique only gives us information about the RT loss - much less so about the other model parameters. This can be seen by the fact that the posteriors for the loss is significantly different from the prior for the loss, but not for the other parameters. Potentially, the power of the technique is improved if we throw other measurements at it, like ringdowns.
  2. If we want to reach the 5 ppm uncertainty target, we need to do better both on the measurement of the DC reflection signals, and also narrow down the uncertainties on the other model parameters.

Some assumptions:

So that the experts on MC analysis can correct me wheere I'm wrong.

  1. The prior distributions are truncated independent Gaussians - truncated to avoid sampling from unphysical regions (e.g. negative ITM transmission). I've not enforced the truncation analytically - i.e. I just assume a -infinity probability to samples drawn from the unphysical parts, but to be completely sure, the actual cavity equations enforce physicality independently (i.e. the MC generates a set of parameters which is input to another function, which checks for the feasibility before making an evaluation). One could argue that the priors on some of these should be different - e.g. uniform PDF for loss between some bounds? Jeffrey's prior for \sigma_{\kappa}?
  2. How reasonable is it to assume the model parameter uncertainties are uncorrelated? For exaple, \eta, \beta_1, \beta_2 are all determined from the ALS-controlled cavity scan
Attachment 1: modelPerturb.pdf
Attachment 2: posterior_modelParams.pdf
Attachment 3: posterior_Loss.pdf
  14463   Sun Feb 17 17:35:04 2019 gautamSummaryLoss MeasurementInferred X arm loss


To complete the story before moving on to ALS, I decided to measure the X arm loss. It is estimated to be 20 +/- 5 ppm. This is surprising to say the least, so I'm skeptical - the camera image of the ETMX spot when locked almost certainly looks brighter than in Oct 2016, but I don't have numerical proof. But I don't see any obvious red flags in the data quality/analysis yet. If true, this suggests that the "cleaning" of the Yarm optics actually did more harm than good, and if that's true, we should attempt to identify where in the procedure the problem lies - was it in my usage of non-optical grade solvents?


  1. Unlike the Y arm, the ratio \kappa = 1.006 \pm 0.002 is quite unambiguously greater than 1, which is already indicative of the loss being lower than for the Y arm. This is reliably repeatable over 15 datapoints at least.
  2. Attachment #1 shows the spectrum of the single-bounce off ITMX beam and compares it to ITMY - there is clearly a difference, and my intuition is to suspect some scatter / clipping, but I confirmed that on the AS table, in air, there is no clipping. So maybe it's something in vacuum? But I'm not sure how to explain its absence for the ITMX reflection. I didn't check the Michelson alignment since I misaligned ITMY before locking the XARM - so maybe there's a small shift in the axis of the X arm reflection relative to the Yarm because of the BS alignment. The other possibility is clipping at the BS?
  3. Attachment #2 shows the filtered time series for a short segment of the measurement. The X arm ASS is mostly well behaved, but the main thing preventing me from getting more statistics in is the familiar ETMX glitching problem, which while doesn't directly break the lock causes large swings in TRX. Given the recent experience with ETMY satellite box, I'm leaning towards blaming flaky electronics for this. If this weren't a problem, I'd run a spatial scan of ETMX, but I'm not going to attack this problem today.
  4. Attachments #3 and #4 show the posterior distributions for model parameters and loss respectively. 
  5. Data quality checks done so far (suggestions welcome):
    • Confirmed that there is no fringing from other ITM (in this case ITMY) / PRM / SRM / ETM in the single-bounce off ITMX config, by first macroscopically misaligning all these optics (the spots could be seen to move on the AS port PD, until they vanished, at some point presumably getting clipped in-vac), and then moving the optics around in PIT/YAW and looking for any effect in the fast time-series using NDScope.
    • Checked for slow drifts in locked / misaligned states - looks okay.
    • Checked centering on PDA520 using both o'scope plateau method and IR viewer - I believe the beam to be well centered.

Provisional conclusions:

  1. The actual act of venting / pumping down doesn't have nearly as large an effect on the round-trip loss as does working in chamber - the IX and EX chambers have not been opened since the 2016 vent.
  2. The solvent marks visible with the green flashlight on ETMY possibly signals the larger loss for the Y arm. 
Attachment 1: DQcheck_XARM.pdf
Attachment 2: consolidated.pdf
Attachment 3: posterior_modelParams_XARM.pdf
Attachment 4: posterior_Loss_XARM.pdf
  14552   Thu Apr 18 23:10:12 2019 gautamUpdateLoss MeasurementX arm misaligned

Yehonathan wanted to take some measurements for loss determination. I misaligned the X arm completely and we installed a PD on the AS table so there is no light reaching the AS55 and AS110 PDs. Yehonathan will post the detailed elog.

  14568   Wed Apr 24 17:39:15 2019 YehonathanSummaryLoss MeasurementBasic analysis of loss measurement


  • Getting myself familiar with Python.
  • Characterize statistical errors in the loss measurement.


​The precision of the measurement is excellent. We should move on to look for systematic errors. 

In Detail

According to Johannes and Gautam (see T1700117_ReflectionLoss .pdf in Attachment 1), the loss in the cavity mirror is obtained by measuring the light reflected from the cavity when it is locked and when it is misaligned. From these two measurements and by using the known transmissions of the cavity mirrors, the roundtrip loss is extracted.

I write a Python notebook (AnalyzeLossData.ipynb in Attachment 1) extracting the raw data from the measurement file (data20190216.hdf5 in Attachment 1) analyzing the statistics of the measurement and its PSD.

Attachment 2 shows the raw data. 

Attachment 3 shows the histogram of the measurement. It can be seen that the distribution is very close to being Gaussian.

The loss in the cavity pre roundtrip is measured to be 73.7+/-0.2 parts per million. The error is only due to the deviation in the PD measurement. Considering the uncertainty of the transmissions of the cavity mirrors should give a much bigger error.

Attachment 4 shows noise PSD of the PD readings. It can be seen that the noise spectrum is quite constant and there would be no big improvement by chopping the signal.

The situation might be different when the measurement is taken from the cavity lock PD where the signal is much weaker.

Attachment 1: LossMeasurementAnalysis.zip
Attachment 2: LossMeasurement_RawData.pdf
Attachment 3: LossMeasurement_Hist.pdf
Attachment 4: LossMeasurement_PSD.pdf
  14733   Mon Jul 8 17:33:10 2019 KruthiUpdateLoss MeasurementOptical scattering measurements

I came across a paper (see reference) where they have used DAOPHOT, an astronomical software tool developed by NOAO, to study the point scatterers in LIGO test masses using images of varying exposure times. I'm going through the paper now. I think using this we can analyze the MC2 images and make some interesting observations.

Reference:  L.Glover et al., Optical scattering measurements and implications on thermal noise in Gravitational Wave detectors test-mass coatings Physics Letters A. 382. (2018)

  14758   Mon Jul 15 03:15:24 2019 KruthiUpdateLoss MeasurementImaging scatterometer

On Friday, Koji helped me find various components required for the scatterometer setup. Like he suggested, I'll first set it up on the SP table and try it out with an usual mirror. Later on, once I know it's working, I'll move the setup to the flow bench near the south arm and measure the BRDF of a spare end test mass.

  14788   Sun Jul 21 02:07:04 2019 KruthiUpdateLoss MeasurementMC2 loss map

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.

  14789   Sun Jul 21 12:54:18 2019 gautamUpdateLoss MeasurementMC2 loss map

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 :(

  14791   Sun Jul 21 17:17:03 2019 KruthiUpdateLoss MeasurementMC2 loss map

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 :(

  14792   Sun Jul 21 19:27:25 2019 MilindUpdateLoss MeasurementMC2 loss map

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.

  14796   Mon Jul 22 12:57:35 2019 KruthiUpdateLoss MeasurementMC2 loss map

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.

  14815   Mon Jul 29 13:32:56 2019 gautamUpdateLoss MeasurementLoss measurement PD installed in AS path

[yehonathan, gautam]

  • we placed a PDA520 photodiode in the AS beampath, so AS110 and AS55 no longer see any light.
  • ITMX and ETMX were misaligned (since the plan is to measure the Y arm loss).
  • The PDA520 and MC2 transmission are currently going to the Y arm ALS beat channels in the DAQ system. Unfortunately, we have no control over the whitening gains for these channels because of the c1iscaux2 situation.
  14816   Mon Jul 29 19:08:55 2019 yehonathanUpdateLoss MeasurementReviving loss measurement by reflection

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.

  14825   Fri Aug 2 17:07:33 2019 yehonathan, gautamUpdateLoss Measurement 

We run a loss measurement on the Y arm with 50 repetitions.

  14827   Mon Aug 5 14:47:36 2019 yehonathanUpdateLoss Measurement 


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 Detail

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%.

  Draft   Mon Aug 5 16:28:41 2019 yehonathanUpdateLoss Measurementwhat is going on with the loss measurements ?

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.

  14830   Mon Aug 5 17:36:04 2019 yehonathanUpdateLoss Measurement 

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.

Attachment 1: 20190805_171511.jpg
  14834   Tue Aug 6 16:44:50 2019 yehonathanUpdateLoss Measurement 

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!

Attachment 1: figure_1.png
Attachment 2: figure_1-1.png
  15076   Thu Dec 5 08:44:44 2019 GavinUpdateLoss MeasurementQ Measurements of Test Masses

[Yehonathan, Gavin]

Measuring POX11_Q_MON and injecting a signal into the ITMX_UL_IN port a signal could not be seen on the function generator. After debugging the source of the issue was two fold:

  • By using the quadrant drives for coils (UL, UR etc) a signal has to pass through a switch before reaching the driver. To resolve this the signal input was switched to POS_IN (driving the entire coil at once rather than in quadrants) which has no switch to bypass.
  • The averaging on the Stanford SR785 was set too low. By increasing the averages from 10 to 25 the signal became more visible.

Unrelated to these issues the signal input was switched to POY11_Q_MON and ITMY_POS_IN as part of the debugging process. The function generator used was switched from the Stanford to the Siglant SDG 1032X.

An unrelated issue but note worthy was the Lenovo 40m laptop used to measure the IFO state (locked or unlocked) ran out of battery in a very short timespan.

To gauge where the resonance of the test masses are FEA model of a simple 40m test mass was computed to give an esitimate at what frequency the eigenmodes exist. For the first two modes the model gave resonances at 20.366 kHz (butterfly mode) and 28.820 kHz (drumhead mode). Then by measuring with an acquisition time of 1 s at they frequencies on the SR785 and injecting broad band white noise with a mean of 0 V and a stdev of 2 V, small peaks were seen above the noise at 20.260 kHz and 28.846 kHz. By then injecting a sine wave at those frequencies with 9 Vpp, the peak became clearly visible above the noise floor.

The last step is to measure the natural decay of these modes when the excitation is turned off. It is difficult to tell currently if these are indeed eigenmodes or just large cavity injections with an associated stabilisation time (what could appear as a ringdown decay). More investigation is required.


Attachment 1: 20191205_132158.jpg
  15264   Tue Mar 10 19:59:09 2020 YehonathanUpdateLoss MeasurementArm transfer function measurement

I want to measure the transfer function of the arm cavities to extract the pole frequencies and get more insight into what is going on with the DC loss measurements.

The idea is to modulate the light using the PSL AOM. Measure the light transmitted from the arm cavities and use the light transferred from the IMC as a reference.

I tried to start measuring the X arm but the transmission PD is connected to the QPD whitening filter board with a 4 pin Lemo for which I couldn't find an adapter.

  • I switch to the Y arm where the transmission PD - Thorlabs PDA520 (250KHz Bandwidth) - is BNC all the way.
  • I lay an 82ft BNC cable from the Y Arm 1Y4 to 1Y1 where the BNC from the IMC Trans PD and an SR785 are found. 
  • I lock the Arm cavities.
  • I connect the AOM cable to the source, the TRY PD (Teed off from the QPD whitening filter) to CH1 and IMC_TRANS to CH2 and measure the transfer function using a swept sine with an offset of 300mV and amplitude of 100mV.
  • I fit it to a low pass filter function - see attachment 1 - but it seems like the fit rails off at 10KHz. 

Could this be because of the PDA520 limited BWs? I tried playing with the PD gain/bandwidth switch but it seems like it was already set to high bandwidth/low gain.

In any case, the extracted pole frequency ~ 2.9kHz implies a finesse > 600 (assuming FSR = 3.9MHz) which is way above the maximal finesse (~ 450) for the arm cavities.

I disconnected the source from the AOM. But left the other two BNCs connected to the SR785. Also, TRY PD is still teed off. Long BNC cable is still on the ground.

Attachment 1: YArmFrequencyResponse.pdf
  15269   Thu Mar 12 10:43:50 2020 ranaUpdateLoss MeasurementArm transfer function measurement

                               when doing the AM sweeps of cavities

make sure to cross-calibrate the detectors

                       else you'll make of science much frivolities

            much like the U.S. elections electors

  15277   Mon Mar 16 15:23:03 2020 YehonathanUpdateLoss MeasurementArm transfer function measurement

I measured the cross-calibration of the two PDs on the PSL table.

I used the existing flip mounted BS that routes the beam into a PDA255, the same as in the IMC transmission.

I placed a PDA520, the same as the one measuring TRY_OUT on the ETMY table,  on the transmission of the BS (Attachment 1).

I used the SR785 to measure the frequency response of PDA520 with reference to PDA255 (Attachment 2). Indeed, calibration is quite significant.

I calibrated the Y arm frequency response measurement.

However, the data seem to fit well to 1/sqrt(f^2+fp^2) - electric field response - but not to 1/(f^2+fp^2) - intensity response. (Attachment 3).

Also, the extracted fp is 3.8KHz (Finesse ~ 500) in the good fit -> too small.

When I did this measurement for the IMC in the past I fitted the response to 1/sqrt(f^2+fp^2) by mistake but I didn't notice it because I got a pole frequency that was consistent with ringdown measurements.

I also cross calibrated the PDs participating in the IMC measurement but found that the calibration amounted for distortions no bigger than 1db.

Attachment 1: Cross_calibration_setup.jpg
Attachment 2: PDA520overPDA255_Response.pdf
Attachment 3: YArmFrequencyResponse.pdf
  15307   Sat Apr 18 14:57:44 2020 YehonathanUpdateLoss MeasurementArm transfer function measurement

Ok, now I understand my foolishness. It should definitely be 1/sqrt(f^2+fp^2) .

However, the data seem to fit well to 1/sqrt(f^2+fp^2) - electric field response - but not to 1/(f^2+fp^2) - intensity response. (Attachment 3).
  15323   Sat May 9 17:01:08 2020 YehonathanUpdateLoss Measurement40m Phase maps loss estimation
I took the phase maps of the 40m X arm mirrors and calculated what is the loss of a gaussian beam due to a single bounce. I did it by simply calculating 1 - (overlap integral)^2 where the overlap is between an input Gaussian mode (calculated from the parameters of the cavity. Waist ~ 3.1mm) and the reflected beam (Gaussian imprinted with the phase map). The phase maps were prepared using PyKat surfacemap class to remove a flat surface, spherical surface, centering, etc. (Attachments 3, 4)
I calculated the loss map (Attachments 1,2: ~ 4X4 mm for ITM, 3X3mm for ETM) by shifting the beam around the phase map. It can be seen that there is a great variation in the loss: some areas are < 10 ppm some are > 80 ppm.
For the ITM (where the beam waist is) the average loss is ~ 23ppm and for the ETM its ~ 61ppm due to the enlarged beam. The ETM case is less physical because it takes a pure gaussian as an input where in reality the beam first interacts with the ITM.
I plan to do some first-order perturbation theory to include the cavity effects. I expect that the losses will be slightly lower due to HOMs not being completely lost, but who knows.
Attachment 1: ITMX_Loss_Map.pdf
Attachment 2: ETMX_Loss_Map.pdf
Attachment 3: ITMX_Phase_Map_(nm).pdf
Attachment 4: ETMX_Phase_Map_(nm).pdf
  15329   Wed May 13 15:13:11 2020 YehonathanUpdateLoss Measurement40m Phase maps loss estimation

Koji pointed out during the group meeting that I should compensate for local tilt when I move the beam around the mirror for calculating the loss map.

So I did.

Also, I made a mistake earlier by calculating the loss map for a much bigger (X7) area than what I thought.

Both these mistakes made it seem like the loss is very inhomogeneous across the mirror.

Attachment 1 and 2 show the corrected loss maps for ITMX and ETMX respectively.

The loss now seems much more reasonable and homogeneous and the average total arm loss sums up to ~ 22ppm which is consistent with the after-cleaning arm loss measurements.

Attachment 1: ITMX_Loss_Map.pdf
Attachment 2: ETMX_Loss_Map.pdf
  15332   Thu May 14 12:21:56 2020 YehonathanUpdateLoss Measurement40m Phase maps loss estimation

I finished calculating the X Arm loss using first-order perturbation theory. I will post the details of the calculation later.

I calculated loss maps of ITM and ETM (attachments 1,2 respectively). It's a little different than previous calculation because now both mirrors are considered and total cavity loss is calculated. The map is calculated by fixing one mirror and shifting the other one around.


The losin total is pretty much the same as calculated before using a different method. At the center of the mirror, the loss is 21.8ppm which is very close to the value that was calculated. 


Next thing is to try SIS.

Attachment 1: ITMX_Loss_Map_Perturbation_Theory.pdf
Attachment 2: ETMX_Loss_Map_Perturbation_Theory(1).pdf
  15333   Thu May 14 19:00:43 2020 YehonathanUpdateLoss Measurement40m Phase maps loss estimation

Perturbation theory:

The cavity modes \left|q\rangle_{mn} , where q is the complex beam parameter and m,n is the mode index, are the eigenmodes of the cavity propagator. That is:


where \hat{R} is the mirror reflection matrix. At the 40m, ITM is flat, so \hat{R}_{ITM}=\mathbb{I}. ETM is curved, so \hat{R}_{ETM}=e^{-i\frac{kr^2}{2R}}, where R is the ETM's radius of curvature.

\phi_g is the Gouy phase.

\hat{K}_L=\frac{ik}{2\pi L}e^{\frac{ik}{2L}\left|\vec{r}-\vec{r}'\right|^2}is the free-space field propagator. When acting on a state it propagates the field a distance L.


The phase maps perturb the reflection matrices slightly so:

\hat{R}_{ITM}\rightarrow e^{ikh_1\left(x,y \right )}\approx 1+ikh_1\left(x,y \right )

\hat{R}_{ETM}\rightarrow e^{ikh_2\left(x,y \right )}e^{-i\frac{kr^2}{2R}}\approx\left[1+ikh_2\left(x,y \right )\right]e^{-i\frac{kr^2}{2R}},

Where h_12 are the height profiles of the ITM and ETM respectively. The new propagator is

H = H_0+V, where H_0 is the unperturbed propagator and

V=ikh_1\left(x,y \right )H_0+ik\hat{K}_Lh_2\left(x,y \right )e^{-i\frac{kr^2}{2R}}\hat{K}_L

To find the perturbed ground state mode we use first-order perturbation theory. The new ground state is then

|\psi\rangle=\textsl{N}\left[ |q\rangle_{00}+\sum_{m\geq 1,n\geq1}^{}\frac{{}_{mn}\langle q|V|q\rangle_{00}}{1-e^{i\left(m+n \right )\phi_g}}|q\rangle_{mn}\right]

Where N is the normalization factor. The (0,1) and (1,0) modes are omitted because they can be zeroed by tilting the mirrors. Gouy phase of TEM00 mode is taken to be 0.

Some simplification can be made here:

{}_{mn}\langle q|V|q\rangle_{00}={}_{mn}\langle q|ikh_1\left(x,y \right )|q\rangle_{00}+{}_{mn}\langle q|\hat{K}_Likh_2\left(x,y \right )e^{-i\frac{kr^2}{2R}}\hat{K}_L|q\rangle_{00}

{}_{mn}\langle q|\hat{K}_Likh_2\left(x,y \right )e^{-i\frac{kr^2}{2R}}\hat{K}_L|q\rangle_{00}={}_{mn}\langle q-L|ikh_2\left(x,y \right )e^{-i\frac{kr^2}{2R}}|q+L\rangle_{00}={}_{mn}\langle q+L|ikh_2\left(x,y \right )|q+L\rangle_{00}

The last step is possible since the beam parameter q matches the cavity.


The loss of the TEM00 mode is then:

L=1-\left|{}_{00}\langle q|\psi\rangle\right|^2





  15338   Tue May 19 15:39:04 2020 YehonathanUpdateLoss Measurement40m Phase maps loss estimation

I have a serious concern about this low angle scattering analysis:

Phase maps perturb the spatial mode of the steady-state of the cavity, but how is this different than mode-mismatch? The loss that I calculated is an overall loss, not roundtrip loss.

The only way I can think this can become serious loss is when the HOMs themselves have very high roundtrip loss. Attached is the modal power fraction that I calculated.


Attachment 1: Mode_power_fraction1.pdf
  16253   Wed Jul 21 18:08:35 2021 yehonathanUpdateLoss MeasurementLoss measurement

{Gautam, Yehonathan, Anchal, Paco}

We prepared for the loss measurement using DC reflection method. We did the following changes:

1. REFL55_Q was disconnected and replaced with MC_T cable coming from the PD on the MC2 table. The cable has a red tag on it. Consequently we lost the AS beam. We realigned the optics and regained arm locks. The spot on the AS QPD had to be corrected.

2. We tried using AS55 as the PD for the DC measurement but we got ratios of ~ 0.97 which implies losses of more than 100 ppm. We decided to go with the traditional PD520 used for these measurements in the past.

3. We placed the PD520 used for loss measurements in front of the AS55 PD and optimized its position.

4. AS110 cable was disconnected from the PD and connected to PD520 to be used as the loss measurement cable.

5. In 1Y2 rack, AS110 PD cable was disconnected, REFL55_I was disconnected and AS110 cable was connected to REFL55_I channel.

So for the test, the MC transmission was measured at REFL55_Q and the AS DC was measured at REFL55_I.

We used the scripts/lossmap_scripts/armLoss/measArmLoss.py script. Note that this script assumes that you begin with the arm locked.

We are leaving the IFO in the configuration described above overnight and we plan to measure the XARM loss early AM. After which we shall restore the affected electrical and optical paths.

We ran the /scripts/lossmap_scripts/armLoss/measureArmLoss.py script in pianosa with 25 repetitions and a 30 s "duty cycle" (wait time) for the Y arm. Preliminary results give an estimated individual arm loss of ~ 30 ppm (on both X/Y arms) but we will provide a better estimate with this measurement. 

  16254   Thu Jul 22 16:06:10 2021 PacoUpdateLoss MeasurementLoss measurement

[yehonathan, anchal, paco, gautam]

We concluded estimating the XARM and YARM losses. The hardware configuration from yesterday remains, but we repeated the measurements because we realized our REFL55_I_ERR and REFL55_Q_ERR signals representing the PD520 and MC_TRANS were scaled, offset, and rotated in a way that wasn't trivially undone by our postprocessing scripts... Another caveat that we encountered today was the need to add a "macroscopic" misalignment to the ITMs when doing the measurement to avoid any accidental resonances.

The final measurements were done with 16 repetitions, 30 second duration, and the logfiles are under scripts/lossmap_scripts/armLoss/logs/20210722_1423.txt and scripts/lossmap_scripts/armLoss/logs/20210722_1513.txt

Finally, the estimated YARM loss is 39\pm7 ppm, while the estimated XARM loss is 38\pm8 ppm. This is consistent with the inferred PRC gain from Monday and a PRM loss of ~ 2%.

Future measurements may want to look into slow drift of the locked vs misaligned traces (systematic errors?) and a better way of estimating the statistical uncertainty (e.g. by splitting the raw time traces into short segments)

  16256   Sun Jul 25 20:41:47 2021 ranaUpdateLoss MeasurementLoss measurement

What are the quantitative root causes for why the statistical uncertainty is so large? Its larger than 1/sqrt(N)

  16257   Mon Jul 26 17:34:23 2021 PacoUpdateLoss MeasurementLoss measurement

[gautam, yehonathan, paco]

We went back to the loss data from last week and more carefully estimated the ARM loss uncertainties.

Before we simply stitched all N=16 repetitions into a single time-series and computed the loss: e.g. see Attachment 1 for such a YARM loss data. The mean and stdev for this long time series give the quoted loss from last time. We knew that the uncertainty was most certainly overestimated, as different realizations need not sample similar alignment conditions and are sensitive to different imperfections (e.g. beam angular motion, unnormalizable power fluctuations, etc...).

Today we analyzed the individual locked/misaligned cycles individually. From each cycle, it is possible to obtain a mean value of the loss as well as a std dev *across the duration of the trace*, but because we have a measurement ensemble, it is also possible to obtain an ensemble averaged mean and a statistical uncertainty estimate *across the independent cycle realizations*. While the mean values don't change much, in the latter estimate we find a much smaller statistical uncertainty. We obtain an XARM loss of 37.6 \pm 2.6 ppm and a YARM loss of 38.9 \pm 0.6 ppm. To make the distinction more clear, Attachment 2 and  Attachment 3 the YARM and XARM loss measurement ensembles respectively with single realization (time-series) standard deviations as vertical error bars, and the 1 sigma statistical uncertainty estimate filled color band. Note that the XARM loss drifts across different realizations (which happen to be ordered in time), which we think arise from inconsistent ASS dither alignment convergence. This is yet to be tested.

For budgeting the excessive uncertainties from a single locked/misaligned cycle, we could look at beam pointing, angular drift, power, and systematic differences in the paths from both reflection signals. We should be able to estimate the power fluctuations by looking at the recorded arm transmissions, the recorded MC transmission, PD technical noise, etc... and we might be able to correlate recorded oplev signals with the reflection data to identify angular drift. We have not done this yet.

Attachment 1: LossMeasurement_RawData.pdf
Attachment 2: YARM_loss_stats.pdf
Attachment 3: XARM_loss_stats.pdf
  335   Fri Feb 22 14:45:06 2008 steveUpdateMOPAlaser power levels

At the beginning of this 1000 days plot shows the laser that was running at 22C head temp
and it was send to LLO

The laser from LHO PA#102 with NPRO#206 were installed at Nov. 29, 2005 @ 49,943 hrs
Now,almost 20,000 hrs later we have 50% less PSL-126MOPA_AMPMON power
Attachment 1: lpower1000d.jpg
  1027   Mon Oct 6 10:00:49 2008 steveUpdateMOPAMOPA_HTEMP is up
Monday morning conditions:

The laser head temp is up to 20.5 C
The laser shut down on Friday without any good reason.
I was expecting the temp to come down slowly. It did not.
The control room temp is 73-74 F, Matt Evans air deflector in perfect position.
The laser chiller temp is 22.2 C

ISS is saturating. Alarm is on. Turning gain down from 7 to 2 pleases alarm handler.

c1LSC computer is down
Attachment 1: htup.jpg
  1116   Thu Nov 6 09:45:27 2008 steveUpdateMOPAhead temp hick-up vs power
The control room AC temp was lowered from 74F to 70F around Oct 10
This hold the head temp rock solid 18.45C for ~30 days as it shows on this 40 days plot.
We just had our first head temp hick-up

note: the laser chiller did not produce any water during this period
Attachment 1: htpr.jpg
  1282   Fri Feb 6 16:23:54 2009 steveUpdateMOPAMOPAs of 7 years

MOPAs and their settings, powers of 7 years in the 40m

Attachment 1: 7ymopas.jpg
  1324   Thu Feb 19 11:51:56 2009 steveUpdateMOPAHTEMP variation is too much
The C1:PSL-MOPA_HTEMP variation is more than 0.5 C daily
Normally this temp stays well within 0.1 C
This 80 days plots shows that we have just entered this unstable region some days ago.
The control room temp set unchanged at 70 F, actual temp at ac-mon 69-70 with occasional peaks at 74 F
Water temp at chiller repeatedly around 20.6 C at 8 am
This should be rock solid at 20.00C +- 0.02C


Attachment 1: 80dhtemp.jpg
  1387   Wed Mar 11 16:41:22 2009 steveUpdateMOPAspare NPRO power

The spare M126N-1064-700,  sn 5519 of Dec 2006 rebuilt  NPRO's power output

 measured   750mW at DC2.06A with Ohpir meter.

Alberto's controller  unit 125/126-OPN-PS,  sn516m was disconnected from lenght measurment NPRO on the AP table.

5519 NPRO  was clamp to the optical table  without heatsink and it was on for 15 minutes.

  1542   Mon May 4 10:38:52 2009 steveUpdateMOPAlaser power is dropped

As PSL-126MOPA_DTEC went up, the power out put went down yesterday

Attachment 1: dtecup.jpg
  1543   Mon May 4 16:49:56 2009 AlbertoUpdateMOPAlaser power is dropped


As PSL-126MOPA_DTEC went up, the power out put went down yesterday

Alberto, Jenne, Rob, Steve,
later on in the afternoon, we realized that the power from the MOPA was not recovering and we decided to hack the chiller's pipe that cools the box.
Without unlocking the safety nut on the water valve inside the box, Jenne performed some Voodoo and twisted a bit the screw that opens it with a screw driver. All the sudden some devilish bubbling was heard coming from the pipes.
The exorcism must have freed some Sumerian ghost stuck in our MOPA's chilling pipes (we have strong reasons to believe it might have looked like this) because then the NPRO's radiator started getting cooler.
I also jiggled a bit with the valve while I was trying to unlock the safety nut, but I stopped when I noticed that the nut was stuck to the plastic support it is mounted on.
We're now watching the MOPA power's monitor to see if eventually all the tinkering succeeded.


[From Jenne:  When we first opened up the MOPA box, the NPRO's cooling fins were HOT.  This is a clear sign of something badbadbad.  They should be COLD to the touch (cooler than room temp).  After jiggling the needle valve, and hearing the water-rushing sounds, the NPRO radiator fins started getting cooler.  After ~10min or so, they were once again cool to the touch.  Good news.  It was a little worrisome however that just after our needle-valve machinations, the DTEC was going down (good), but the HTEMP started to rise again (bad).  It wasn't until after Alberto's tinkering that the HTEMP actually started to go down, and the power started to go up.  This is probably a lot to do with the fact that these temperature things have a fairly long time constant. 

Also, when we first went out to check on things, there was a lot more condensation on the water tubes/connections than I have seen before.  On the outside of the MOPA box, at the metal connectors where the water pipes are connected to the box, there was actually a little puddle, ~1cm diameter, of water. Steve didn't seem concerned, and we dried it off.  It's probably just more humid than usual today, but it might be something to check up on later.]

  1547   Tue May 5 10:42:18 2009 steveUpdateMOPAlaser power is back


As PSL-126MOPA_DTEC went up, the power out put went down yesterday

 The NPRO cooling water was clogged at the needle valve. The heat sink temp was around ~37C

The flow-regulator  needle valve position is locked with a nut and it is frozen. It is not adjustable. However Jeenne's tapping and pushing down on the plastic hardware cleared the way for the water flow.

We have to remember to replace this needle valve when the new NPRO will be swapped in. I checked on the heat sink temp this morning. It is ~18C

There is condensation on the south end of the NPRO body, I wish that the DTEC value would just a little higher like 0.5V

The wavelenght of the diode is temp dependent: 0.3 nm/C. The fine tuning of this diode is done by thermo-electric cooler ( TEC )

To keep the diode precisely tuned to the absorption of the laser gain material the diode temp is held constant using electronic feedback control.

This value is zero now.


Attachment 1: uncloged.jpg
  1646   Wed Jun 3 03:30:52 2009 ranaUpdateMOPANPRO current adjust
I increased the NPRO's current to the max allowed via EPICS before the chiller shutdown. Yesterday, I did this
again just to see the effect. It is minimal.

If we trust the LMON as a proportional readout of the NPRO power, the current increase from 2.3 to 2.47 A gave us
a power boost from 525 to 585 mW (a factor of 1.11). The corresponding change in MOPA output is 2.4 to 2.5 W
( a factor of 1.04).

Therefore, I conclude that the amplifier's pump has degraded so much that it is partially saturating on the NPRO
side. So the intensity noise from NPRO should also be suppressed by a similar factor.

We should plan to replace this old MOPA with a 2 W Innolight NPRO and give the NPRO from this MOPA back to the
bridge labs. We can probably get Eric G to buy half of our new NPRO as a trade in credit.
Attachment 1: Untitled.png
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