I repeated this measurement as follows:

1. Added a filter in the MC_F filterbank (FM9) to account for the Pomona box between the PZT control signal and the laser PZT (pole@2.9Hz). So the filter bank at the time of TF measurement looks like this:
   
2. Measured TF from driving MC2 (with C1:SUS-MC2_MCL_OUT channel) to C1:IOO-MC_F, which is the output of the above filter bank. The response is the expected 1/f^2 shape of the free optic
    
   
3. From this transfer function, the magnitude is 0.0316 ct/ct. Using the value of 6nm/ct for the MC2 actuator gain that I found in a previous elog entry, I calibrated the MC_F output into Hz using the calibration factor 3.95MHz/ct (FM10 in the above filterbank).

Here is a calibrated MC_F spectrum:

RXA: I've added this plot of the free-running noise of the Lightwave NPRO which is probably similar to our Innolight Mephisto. Seems like the laser is quieter than MC_F everywhere below 100 Hz.

What readouts do we have for the PMC length? If we could have a calibrated & whitened error and control signal for the PMC up to 16 kHz, perhaps we could see at what frequencies we can use it as a faux-RefCav.

In http://nodus.ligo.caltech.edu:8080/40m/11793 I posted the calibrated PMC free-running displcament with/without IMC locked. Unfortunately, this measurement was done with a part of the IMC electronics not perfect (https://nodus.ligo.caltech.edu:8081/40m/11794). I did the same measurement after the fix, but there is no low freq data http://nodus.ligo.caltech.edu:8080/40m/11795.

Assuming we have the similar error signal leve in the low freq band as The entry 11793, the IMC is considered to be noisier than the PMC between 0.8 and 4Hz. But we should do the same measurement with the current electronics.

The PMC calibration can be found in this entry http://nodus.ligo.caltech.edu:8080/40m/11780

I took some training data during Sunday night/Monday morning while the MCL MISO FF was turned on. We wanted to see how much residual noise was left in the WFS1/WFS2 YAW and PITCH signals. 

The offline subtractions that can be achieved are:

For WFS1

For WFS2

I need to download data for these signals while the MCL FF is off in order to measure how much subtraction was achived indirectly with the MCL FF. In a previous elog:11472, I showed some offline subtractions for the WFS1 YAW and PITCH before any online FF was implemented either by me or Jessica. From the plots of that eLOG, one can clearly see that the YAW1 signal is clearly unchanged in the sense of how much seismic noise was mitigated indirectly torugh MCL. 

Koji has implemented the FF paths (thank you based Koji) necessary for these subtractions to be implemented. The thing to figure out now is where we want to actually actuate and to measure the corresponding transfer functions. I will try to have either Koji or Eric help me measure some of these transfer functions.

Finally, I looked at the ARMS and see what residual seismic noise can be subtracted

I'm not too concerned about noise in the arms as if the WFS subtractions turn out to be promising then I expect for some of the arms seismic noise to go down a bit further. We also don't need to measure an actuator transfer function for arm subtractions, give that its essentially flat at low frequencies, (less than 50 Hz).

In my last post I calculated the different subtractions (offline) that could be done to YARM alone just to get a sense of what seismometers were better witnesses for the Wiener filter calculation. 

In this eLOG I show what subtractions can be done when the MCL has FF on (as well as Eric's PRC FF), with the SISO filter described on elog:11496.

The plot below shows what can be done offline,

What is great about this results is that the T240-X and T240-Y channels are plenty enough to mitigate any remaining YARM seismic noise but also to get rid of that nasty peak at 55 Hz induced by the MCL FF filter.

The caviat, I haven't measured the TF for the ETMY actuator to YARM control signal. I need to do this and recompute the FIR filters with the prefiltered witnesses in order to move on to the IIR converions and online FF!

The old MCL filters are not completely useless - I find a factor of ~2 reduction in the MCL RMS when I turn the FF on. It'd be interesting to see how effective the FF is during the periods of enhanced seismic activity we see. I also wonder if this means the old PRC angular FF filters are also working, it'd help locking, tbc with PRMI carrrier...

Update: The PRC angular FF loops also do some good it seems - though the PIT loop probably needs some retuning.

As a starting point, I was looking at some of the old elogs and tried turning on the MCL feedback path with the existing control filters today. I tried various combinations of MCL Feedback and FF on and off, and looked at the MCL error signal (which I believe comes from the analog MC servo board?) spectrum for each case. We had used this earlier this year when EricQ and I were debugging the EX laser frequency noise to stabilize the low frequency excursions of the PSL frequency. The low frequency suppression can be seen in Attachment #1, there looks to be some excess MCL noise around 16Hz when the servo is turned on. But the MC transmission (and hence the arm transmission) decays and gets noisier when the MCL feedback path is turned on (see Attached StripTool screenshots).

I wanted to get a clearer idea of the FSS servo and the various boxes in the signal chain and so Lydia and I poked around the IOO rack and the PSL table - I will post a diagram here tomorrow.

We then wanted to characterize the existing loop. It occurred to me later in the evening to measure the plant itself to verify the model shape used to construct the invP filter in the feedback path. I made the measurement with a unity gain control path, and I think there may be an extra zero @10Hz in the model.

Earlier in the evening, we measured the OLG of the MCL loop using the usual IN1/IN2 prescription, in which above 10Hz, the measurement and FOTON disagree, which is not surprising given Attachment #1.

I didn't play around with the loop shape too much tonight, but we did perform some trials using the existing loop, taking into account some things I realized since my previous attempts. The summary of the performanceof the existing loop is:

• Below 1Hz, MCL loop injects noise to the arm control signal. I need to think about why this is, but perhaps it is IMC sensing noise?
• Between 1-4Hz, the MCL loop suppresses the arm control signal
• Between 4-10Hz (and also between 60-100Hz for the Xarm), the MCL loop injects noise. Earlier in the evening, we had noticed that there was a bump in the X arm control signal between 60-100Hz (which was absent in the Y arm control signal). Koji later helped me diagnose this as too low loop gain, this has since been rectified, but the HF noise of the X arm remains somewhat higher than the Y arm.

All of the above is summarized in the below plots - this behaviour is (not surprisingly) in line with what Den observed back when he put these in.

The eventual goal here is to figure out if we can get an adaptive feedback loop working in this path, which can take into account prevailing environmental conditions and optimally shape the servo to make the arms follow the laser frequency more closely at low frequencies (i.e. minimize the effect of the noise injected by IMC length fluctuations at low frequency). But first we need to make a robust 'static' feedback path that doesn't inject control noise at higher frequencies, I need to think a little more about this and work out the loop algebra to figure out how to best do this...

In the Generic Pentek interface board, which is used to take in the analog 2-pin LEMO cable from the MC Servo board, there is some analog whitening before the signal is sent into the ADC.

There are jumpers in there to set whether it is 0, 1, or 2 stages of 150:15 (z:p) whitening.

Quick summary elog, details to follow. I did the following:

• Updated the Simulink model based on Koji's feedback. 
• Today morning, I measured the (electronic) open-loop TFs of
  • MC Servo Board
  • FSS Fast path (PZT)
  • FSS PC Drive path
• The summing amplifiers in the latter two paths are assumed to be broadband for the purposes of this model.

The measurements I have look reasonable. But I had a hard time trying to look at the schematic and determine what is the appropriate number and locations of poles/zeros with which to fit the measured transfer function. Koji and I spent some time trying to go through the MC Servo board schematic, but looks like the version uploaded on the 40m DCC tree doesn't have changes made to it reflected (we compared to pictures on the 40m google photos page and saw a number of component values were different). Since the deviation between fit and measurement only occurs above 1MHz (while using poles/zeros inferred from the schematic), we decided against pulling out the servo board and investigating further - but this should be done at the next opportunity. I've marked the changes we caught on a schematic and will upload it to the 40m DCC page, and we can update this when we get the chance.

So it remains to fit the other two measured TFs, and add them to the Simulink model. Then the only unknown will be the PDH discriminant, which we anyway want to characterize given that we will soon have much more modulation.  

Data + plots + fits + updated schematics to follow...

Here are the details as promised.

Attachment #1: Updated simulink model. Since I haven't actually run this model, all the TF blocks are annotated "???", but I will post an updated version once I have run the model (and fix some of the questionable aesthetic choices)

Attachment #2: Measured and fitted transfer functions from the "IN1" input (where the demodulated MC REFL goes) to the "SERVO" output of the MC servo board (to FSS box). As mentioned in my previous elog, I had to put in a pole (fitted to be at ~2MHz, called pole 9 in the plot) in order to get good agreement between fit an measurement up to 10MHz. I didn't bother fitting all the high frequency features. Both gain sliders on the MEDM screen ("IN1 Gain" and "VCO gain") were set to 0dB for this measurement, while the super boosts were all OFF.

Attachment #3: Measured and fitted transfer function from "TEST 1 IN" to "FAST OUT" of the FSS box. Both gains on the FSS MEDM screen ("Common gain adjust" and "fast gain adjust") were set to 0dB for this measurement. I didn't need any ad-hoc poles and zeros for this fit (i.e. I can map all the fitted poles and zeros to the schematic), but the fit starts to deviate from the measurement just below 1 MHz.. perhaps I need to add a zero above 1MHz, but I can't see why from the schematic...

Attachment #4: Measured TF from "TEST 1 IN" to "PC OUT" on the FSS box. MEDM gains were once again 0dB. I can't get a good fit to this, mainly because I can't decipher the poles and zeros for this path from the schematic (there are actually deviations from the schematic posted on the 40m DCC page in terms of component values, I will try and correct whatever I notice) . I'll work on this...

Attachment #5: Data files + .fil files used to fit the data with LISO

Most of the model has come together, I am not too far from matching the modelled OLG to the measured OLG. So I will now start thinking about designing the controller for the MCL part (there are a couple of TFs that have to be measured for this path).

Rana motivated me to take a step back and reframe the objectives and approach for this project, so I am collecting some thoughts here on my understanding of it. As I write this, some things still remain unclear to me, so I am leaving these as questions here for me to think about...

Objectives: 

1. The PSL is locked to the IMC cavity - but at frequencies near 1 Hz, the laser frequency is forced to follow the IMC cavity length fluctuations, even though the free-running PSL frequency noise at those frequencies is lower. This excess is also imprinted on the arms when locked to the IR. We would like to improve the situation by feeding back a portion of the MC PDH error signal to the cavity length actuator to stabilize the MC cavity length at low frequencies. Moreover, we would like this loop to not imprint additional control noise in the arm control signals, which is a problem we have observed with the existing MCL loop. 
    
2. The borader goal here is to use this project as a case study for designing the optimal loop and adaptive feedback. Can we come up with an algorithm, which takes
   • A model of our system (made with measured data where possible)
   • A list of our requirements (e.g. in this case, frequency noise requirements in various frequency bands, smooth crossovers between the various loops that enable locking the PSL to the IMC cavity and avoid injecting excess control noise into the plant)

and come up with the best loop that meets all our rquirements? What constitutes the "best" loop? How do we weight the relative importance of our various requirements? 

Proposed approach:

For the specific problem of making the MCL feedback loop better, the approach I have in mind right now is the following:

1. Build a model of the 40m IMC loop. Ultimately the performance of the loop we implement will depend on the transfer function from various additive noise sources and disturbances in the feedback loop (e.g. electronics noise) to the output (i.e. laser frequency). Building an accurate model will allow us to quantify the performance of the proposed control loop, and hence, optimize it with some algorithm. I did some work on a simplistic, purely analytical model of the two MC loops (MCF and MCL), but Rana pointed out that it is better to have something more realistic for this purpose. I have inherited his Simulink models, which I will now adapt to reflect the 40m topology. 
2. Come up with a list of requirements for the MCL controller. Some things that come to mind:
   • Reduce the arm control signal spectral amplitude below 20 Hz
   • Not increase the arm control signal spectral amplitude above 20 Hz
   • Crossover smoothly with the FSS slow temperature control loop and the MCF loop. 
   • What factor of suppression are we looking for? What is achievable? Once I build the model, it should shed some light on these..
   • Is the PMC a more stable frequency reference than the NPRO crystal at low frequencies? This measurement by Koji seems to suggest that it isn't (assuming the 1e4 product for the NPRO free-running frequency noise)..
3. Once we have a model and a satisfactory list of requirements, design a control loop that meets these using traditional techniques, i.e. desired tracking error in the control band of 0.1-20 Hz (is this possible? The model will tell us...), gain and phase margin requirements etc. But this need not necessarily be the optimal controller that meets all of our requirements
4. Optimize the controller - how? Can we define an objective function that, for example, rewards arm control signal suppression and penalizes injection of control noise, and just fminsearch in the [z,p,k] parameter space of the controller? Is there a smarter way to do this?
5. Can this algorithm be adaptive, and optimize the controller to adapt to prevailing seismic conditions for example? Is this the same as saying we have a model that is accurate enough for us to predict the response of the plant to environmental disturbances? 

My immediate goal is to have the Simulink model updated.

Thoughts/comments on the above will be appreciated...

In working on automatic DARM loop design, we have this code:

https://git.ligo.org/rana-adhikari/ModernControls/tree/master/OptimalFeedback/GlobalCost

the things in there like mkCost*, etc. have examples of the cost functions that are used. It may be useful to look at those and then make a similar cost function calculation for the MCL/MCF loop.

I've edited Rana's Simulink model to reflect the current IMC servo topology (to the best of my understanding). I've tried to use Transfer Function blocks wherever possible so that we can just put in the appropriate zpk model in the script that will linearize the whole loop. I've also omitted the FSS SLOW loop for now.

I've been looking through some old elogs and it looks like there have been several modifications to both the MC servo board (D040180) and the TT FSS Box (D040105). I think it is easiest just to measure these TFs since the IMC is still down, so I will set about doing that today. There is also a Pomona Box between the broadband EOM and the output of the TT FSS box, which is meant to sum in the modulation for PMC locking, about which I have not yet found anything on the elog.

So the next steps are:

1. Measure/estimate all the unknown TFs and gains in this schematic
2. Linearize the model, get the OLG, see if the model matches previously measured OLGs (with the MCL part disabled)
3. Once the model is verified to be correct, look at couplings of various noise sources in the MCL part of the loop, and come up with a suitable controller.

If anyone sees something wrong with this topology, please let me know so that I can make the required changes.

It is more accurate to model the physical frequency noises at various places.

cf. See also 40m ALS paper or Shigeo Nagano PDH thesis on https://wiki-40m.ligo.caltech.edu/40m_Library

- The output 4 should be "Laser frequency"

- Seismic path should be excluded from the summing node

- The output after the PMC: "Laser frequency after the PMC"

- "Laser frequency after the PMC" is compared (diffed) with the output 1 "mirror motion in Hz"

- The comparator output goes to the cav pole, the PD, and the PDH gain: This is the output named "PDH Error"

- Tap a new path from "Laser frequency after the PMC" and multiply with the cav pole (C_IMC)
- Tap a new path from "Mirror motion" and multiply with the cavity high pass  (s C_IMC/omega)
- Add these two: This is the output named "Frequency noise transmitted by IMC"

Today I finished fitting the transfer function to a vectfit model for seismometers T240_X and T240_Y, and then used these to filter noise online from the mode cleaner. 

The Bode plot for T240_X is in figure 1, and T240_Y is in figure 2. I made sure to weight the edges of the fit so that no DC coupling or excessive injection of high frequency noise occurs at the edges of the fit.

I used C1:IOO-MC_L_DQ as the first channel I filtered, with C1:IOO-MC_L_DQ(RMS) for RMS data. I took reference data first, without my filter on. I then turned the filter on and took data from the same channel again. The filtered data, plotted in red, subtracted from the reference and did not inject noise anywhere in the mode cleaner. 

I also looked at C1:LSC-YARM_OUT_DQ and C1:LSC-YARM_OUT_DQ(RMS) for its RMS to see if noise was being injected into the Y-Arm when my filter was implemented. I took reference data here also, shown in blue, and compared it to data taken with the filter on. My filter, in pink, subtracted from the Y-Arm and injected no noise in the region up to 10 Hz, and only minimal noise at frequencies ~80 Hz. Frequencies this high are noisy and difficult to filter anyways, so the noise injection was minimal in the Y-Arm. 

After fighting relentlessly with the mode cleaner, I believe I have achieved final results. 

I have mostly been focusing on Wiener filtering MCL with a SISO Wiener filter for a reason, simplicity. This simplicity allowed me to understand the dificulties of getting a filter to work on the online system properly and to develope a systematic way of making this online Wiener filters. The next logical step after achieving my final SISO Wiener filter using the T240-X seismometer as witness for MCL (see elog:11535) and learning how to produce good conditioned Wiener filters was to give MISO Wiener filtering of MCL a try. 

I tried performing some MISO filtering on MCL using the T240-X and T240-Y as witnesses but the procedure that I used to develope the Wiener filters did not work as well here. I made the decision to ditch it and use some of the training data I saved when the SISO (T240-X) filter was runing overnight to develope another SISO Wiener filter for MCL but this time using T240-Y as witness. I will compare how much more we gain when doing MISO Wiener filtering compared to just a bunch of SISO filtering in series, maybe a lot, or little.

I left both filters running overnight in order to get trainining data for arm and WFS yaw and pitch subtractions.

The SISO filters for MCL are shown below:

The theoretical FIR and IIR subtractions using the above filters:

Running the filters on the online system gave the following subtractions for MCL and YARM:

Comparing the subtractions using only the T240-X filter versus the T240-X and T240-Y:

Somehow it seems like the ELOG makes all of the thumbnails way too big by default. Did we get some sneaky upgrade recently?

I would only plot your results below 50 Hz. We don't care about the RMS at high frequencies and it can make the RMS misleading.

We definitely need to include one vertical Wilconox at each MC chamber so that it can subtract all of that junk at 10-20 Hz.

Big thumbnails? Could it have been this? elog:11498.

Anyways, I fixed the plots and plotted an RMS that can actaully be read in my original eLOG. I'll see what can be done with the MC1 and MC2 Wilcoxon (z-channel) for online subtractions. 

Ignacio is correct; I forgot to shrink the value back down after testing the PDF thumbnails. Default thumbnail size is now back to 600px. 

I'm not totally sure, but by eyeball, this seems like the best online MCL reduction we've ever had. Nice work.

The 3 Hz performance is the same as usual, but we've never had such good 1 Hz reduction in the online subtraction.

I would like to see a plot of the X & Y arm control signals with only the MCL filter ON/OFF. This would tell us how much of the arm signals were truly frequency noise.

We took data for the mode cleaner a while ago, June 30th I believe. This data contained signals from the six accelerometers and the three seismometers. In here I have only focused on the seimometer signals as witnesses in order to construct Wiener filters for each of the three seismometer signals (x,y,z) and for the combined seismometers signal. The following plot showing the ASD's shows the results,

 Wiener filtering works beautifully for the seismometers. Note that subtraction is best when we use all three seismometers as the witnesses in the Wiener filter calculation, as can be clearly seen in the first plot above.

Now, I used vectfit to conver the Wiener FIR filters for each seismometer to their IIR versions. The following are the bode plots for the IIR filters,

For the x-direction seismometer,

For the y-direction seismometer

,

And for the z-direction seismometer,

 The IIR filters were computed using 5 zeros and 5 poles using vectfit. That was the maximum number of poles that I could use wihtout running into trouble with matrices being almost singular in Matlab. I still need to figure out how to deal with this issue in more detail as fitting the y-seismometer was a bit problematic. I think having a greater number of poles will make the fitting a bit easier.

(updateAfter Eric gave me feedback on my previous elog post, I went back and fixed some of the silly stuff I stated.

First of all, I have come to realized that it makes zero sense to plot the ASD's of the mode cleaner against the seismometer noise. These measurements are not only quite different, but elementary, they posess different units. I have focused my attention to the MCL being Wiener filtered with the three siesmometer signals. 

One of the major improvements that I make in the following analysis is,

1) Prefiltering; a band pass filter from 1 to 5 Hz, in order to emphasize subtraction of the bump shown in the figure below.

2) I have used vectfit exclusively in the 1 to ~5 Hz range, in order to model the FIR filter properly, as in, the kind of subtraction that we care about. Limiting myself to the 1 - 5 Hz range has allowed me to play freeley with the number of poles, hence being able to fit the FIIR filter properly with an IIR rational transfer function properly,

The resulting ASD's are shown below, in blue we show the raw MCL output, in blac the Wiener filter (FIR) result, and finally in black, the resultant data being filtered with the calculated IIR Wiener filter.

Now, in the following plots I show the IIR Wiener filters for each of the three seismometers, 

X Seismometer,

For the Y seismometer,

and for the Z seismometer,

The matlab code for this work is attached: code.zip

As MCL is disturbing arm locking by injecting a lot of noise, I have modified 'mcup'  to disable MCL

As MC WFS keeps failing to start up when it is locked, the lines in 'mcwfsoff' to clear WFS filter history were restored.

MC down script is too slow to block MC_L when the cavity goes out of lock. As a result the loop strongly kicks MC2. We decided to make a threshold inside MCS model on MC TRANS that will block MC_L during lock loss. This is a lower threshold. Upper threshold can be slow and is implemented inside MC up script.

Fast threshold can be set inside MC2 POS. I did not correct MC2 top level medm screen as it is the same for all core optics.

Note: Fast trigger will also block ALS signal if MC loose lock.

I turned on some filters and gain in the SUS-MC2_MCL filter bank tonight so as suppress the seismic noise influence on MC_F. This may help the MC stay in lock in the daytime.

Koji updated the mcdown and mcup scripts to turn the MCL path on and off and to engage the Boost filters at the right time.

The attached PNG shows the MCL screen with the filters all ON. In this state the crossover frequency is ~45 Hz. MC_F at low frequencies is reduced by more than 10x.

I also think that this may help the X-Arm lock. The number of fringes per second should be 2-3x less.

I did a raw calibration of MCL and GUR. Accuracy is a factor of 2.

GUR path : 800 V/m/s => readout box (G~100) => ADC (0.7 mV/count)

MCL path : laser 1 MHz / V, cavity length ~ 25 m

I measured feedback signal before the laser with SR and avoided whitening filters for MC_F.

I've added MCL and WFS stop triggers into C1MCS/SUS model. Threshold value of MC_TRANS can be changed in the text entry located in MC2_POSITION medm screen. I tried 2 cases: trigger either blocks signal before MCL filter bank input or after output. Due to filter history in the 1 case MC2 was still slightly disturbed (C1:SUS-MC2_ULPD_VAR ~= 15) right after unlock. In the second case there was no disturbance as we zero output signal, but then I had to add "clear history" command to the mcup script.

WFS triggers block the signal before ASCPIT/YAW filter bank.

 I've redone the WFS triggers.  I left the MCL trigger alone (for now....I'll come back to it). 

The trigger was setup such that (a) it was totally unclear what was going on, by looking at the WFS screen.  Koji and I spent some time confused before I remembered that Den did this work recently.  Also, for some reason, the triggers were just plain thresholding, not a schmidt trigger, so any time the cavity flashed, the WFS came on.  Since the cavity can flash before the mcdown script has a chance to turn off the WFS servos, the outputs of the WFS filters are trying to output thousands of counts, and the signal goes through any time the cavity flashes.  Not so good.

I have removed the triggering for the angular DoFs from the mcs model (leaving the MCL triggering for now).  I have put new triggering into the ioo model, at the error point of the WFS loops.  The idea is that if the cavity unlocks, we don't want to lose the current pointing of the mirrors.  If the WFS servos were doing a lot of DC work, the bias sliders won't have the full information about where we want the mirrors to point.  Since we have the integrators in FM1, removing the input signal should freeze the output signal.  I need to modify the WFS on / off script so that this doesn't get turned off every lockloss.

Also, I have implemented (for the first time in a useful model, although I've done some testing in the tst model) the "wait" delay between a cavity locking and the trigger going through.  The idea is that we don't necessarily want the WFS to come on simultaneously with the cavity lock.  Since the wait delay resets any time it is un-triggered, this also prevents any signals from going through during cavity flashes.  The wait block has 3 inputs:  (1) a trigger, the output of some kind of trigger block, (2) a number of seconds to wait and (3) the model rate in Hz.  The model rate should be set with a constant in the model, the trigger passed from the trigger block, and the wait time in seconds should be available as an epics input. 

So far it looks like it's working as I expect, although I'm honestly too tired to do enough testing that I'm satisfied with, so I'm leaving the WFS off for the night.

 Your schmitt trigger has 2 threshold values - min and max. Set thresholding value in my trigger to the max of your schmitt trigger and you get the same behavior for MC,  triggers are not supposed to turn anything on in this realization as they do for locking with flashing.

 The problem is that the WFS were being engaged with your triggers every time the MC flashed.  That wasn't a schmidt trigger thing, but I like the schmidt trigger better anyway.

Anyhow, it's turned on, and it works really well.  It's kind of awesome.  I'm really excited to start using the wait block to start pushing even more of the locking out of scripts and into the real time system.

Riju did the measurement of the MCREFL PD.
I found data files in her directory on the control machine.

I was not sure how much was the transimpedance of the DC out.
I assumed the default number from the circuit diagram which was 66.7Ohm.
This may cause the error in absolute caribration of the transimpedance but the shape does not change.

The RF preamp is gain-peeking at 250MHz.

Here is further characterization of the PD response.
As you can see in the second attachment, the 3dB cut off of the resonance is about 2.3MHz.

The game plan file in dropbox was also modified.

Gautam and Steve,

Our MCREFL rfpd C30642GH 2x2mm beeing investigated for burned spots.

Atm1,           unused -  brand new pd

Atm2,3,4       MCREFL in place was not moved

More pictures will be posted on 40m Picassa site later. 

I did a quick measurement of the beam size on the MC REFL PD today morning. I disabled the MC autolocker while this measurement was in progress. The measurement set up was as follows:

This way I was able to get right up to the heat sink - so this is approximately 2cm away from the active area of the PD. I could also measure the beam size in both the horizontal and vertical directions.

The measured and fitted data are:

The beam size is ~0.4mm in diameter, while the active area of the photodiode is 2mm in diameter according to the datasheet. So the beam is ~5x smaller than the active area of the PD. I couldn't find anything in the datasheet about what the damage threshold is in terms of incident optical power, but there is ~100mW on th MC REFL PD when the MC is unlocked, which corresponds to a peak intensity of ~1.7 W / mm^2...

Even though no optics were intentionally touched for this measurement, I quickly verified that the spot is centered on the MC REFL PD by looking at the DC output of the PD, and then re-enabled the autolocker.

Kevin, Gautam and Arijit

We did a optical measurement of the MCREFL_PD transimpedance using the Jenny Laser set-up. We used 0.56mW @1064nm on the NewFocus 1611 Photodiode as reference and 0.475mW @1064nm on the MCREFL_PD. Transfer function was measured using the AG4395 network analyzer. We also fit the data using the refined LISO model. From the optical measurement, we can see that we do not have a prominent peak at about 300MHz like the one we had from the electrical transimpedence measurement. We also put in the electrical transimpedence measurement as reference. RMS contribution of 300MHz peak to follow.

As per Rana`s advice I have updated the entry with information on the LISO fit quality and parameters used. I have put all the relevant files concerning the above measurement as well as the LISO fit and output files as a zip file "LISO_fit" . I also added a note describing what each file represents. I have also updated the plot with fit parameters and errors as in elog 10406.

Kevin, Gautam and Arijit

Today we performed the in-loop noise measurements of the MCREFL-PD using the SR785 to ascertain the effect of the Noise Eater on the laser. We took the measurements at the demodulated output channel from the MCREFL-PD. We performed a series of 6 measurements with the Noise Eater ''ON'' and ''OFF''. The first data set is an outlier probably, due to some transient effects. The remaining data sets were recorded in succession with a time interval of 5 minutes each between the Noise Eater in the ''ON'' and ''OFF'' state. We used the calibration factor of 13kHz/Vrms from elog 13696 to convert the V_rms to Hz-scale.

The conclusion is that the NOISE EATER does not have any noticeable effect on the noise measurements.

ALS beat spectrum and also the arm control signal look as they did before. coherence between arm control signals (in POX/POY lock) is high between 10-100Hz, so looks like there is still excess frequency noise in the MC transmitted light. Looking at POX as an OOL sensor with the arm under ALS control shows ~10x the noise at 100 Hz compared to the "nominal" level, consistent with what Koji and I observed ~3weeks ago.

We tried swapping out Marconis. Problem persists. So Marconi is not to blame. I wanted to rule this out as in Jan, Steve and I had installed a 10MHz reference to the rear of the Marconi.

the noise eater on/off measurements should be done for 0-100 kHz and from the demod board output monitor

[Gautam, Kevin]

We redid the measurement measuring the voltage noise from the REFL PD demod board output monitor with an SR785 with the noise eater on and off. We used a 100x preamp to amplify the signal above the SR785 noise. The SR785 noise floor was measured with the input to the preamp terminated with 50 ohms. The spectra shown have been corrected for the 100x amplification.

This measurement shows no difference with the noise eater on or off.

I found that MCT QPD has a dependence of the total output on the position of the spot. Since the QPD needs the supply and bias voltages from the sum/diff amp, I could not separate the problems of the QPD itself and the sum/diff amplifier by the investigation on Tuesday. On Wednesday, I investigated a generic quad photodiode interface module D990692.

...I was so disappointed. This circuit was left uninvestigated and used so long time with the following sorrowful conditions.
- This circuit has 4 unbuffered inputs with input impedance of 300~400 Ohm. It's way too low!
- Moreover, those channels have different input impedances. Ahhhh.
- Even worse, the QPD circuit D990272 has output impedance of 50 Ohm.
- The PCB of this circuit has four layers. It is quite difficult to make modifications of the signal route.
- It is a headache: this circuit is "generic" and used in many places.

D990692 has 4 channel inputs that are not buffered. Each channel has two high impedance buffers but they are used only for the monitors. The signal paths have no buffer.

The differential amplifier is formed by R=1k Ohm. The inverted side of the input has 1kOhm impedance. The non-inverted side has 1.5kOhm impedance.

CH1: 10K // 1.5k // 1.5k // 1k = 411 Ohm
CH2: 10K // 1.5k // 1k // 1k = 361 Ohm
CH3: 10K // 1k // 1k // 1k = 323 Ohm
CH4: 10K // 1k // 1.5k // 1k = 361 Ohm

Considering the output impedance of 50Ohm for the QPD, those too low input impedances result in the following effect:
- Because of the voltage division, we suffer absolute errors of 10.8~13.4%. This is huge.
- Because of the input impedance differences, we suffer a relative error of 1.5%~3%. This is also huge.

Unfortunately, the circuit has no room to modify; the signal paths are embedded in the internal layer.

I decided to replace the resistors of the sum/diff amps from 1k to 10k. Also the input impedance of the buffer was removed as the input is terminated by the sum/diff amps in any case.This changes the input inpedance to the followings:

CH1: 15k // 15k // 10k = 4286 Ohm
CH2: 15k // 10k // 10k = 3750 Ohm
CH3: 10k // 10k // 10k = 3333 Ohm
CH4: 10K // 15k // 10k = 3750 Ohm

These yield the absolute error of 1.2-1.5%. The relative error is now 0.3%. I can accept these numbers, but later I should put additional terminating resistors to compensate the differencies.

So far I have modified the resistors for the MCT as the modification for a QPD needs 17 10k resistors.
Next thing I have to check is the dependence of the QPD outputs on the spot positions.

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Edit: Feb 11, 2010

I talked with Frank and he pointed out that the impedances are not the matter but the gains of the each channels are the matters (after considering the output impedance of the QPD channels).
If we assume the ideal voltage sources at the QPD and the symmetric output impedances of 50Ohm, the gain of the each circuit are affected but the change should be symmetric.

He found that several things:
- The analog switch (MAX333) used in the QPD unit adds more output impedance (somewhat randomly!).
- The resistance of the sum/diff circuits may vary each other unless we use 0.1% resistors.

 This is indeed sad. But, we can perhaps bypass all of this by just using the individual segment outputs. According to the circuit diagram and the c1iool0 .db file, we should be able to just do the math on the segments and ignore the VERT/HOR/SUM signals completely. In that case, we can just use high impedance for the sum/diff buffers as Koji says and not suffer from the calibration errors at all I think.

Unfortunately, the signals for individual segments also suffer from the voltage drop as all of the low impedance amplifiers are hung from the same input.
In order to utilize the individual channels, we anyway have to remove the resistors for the VERT/HOR/SUM amps.
That is possible. But does it disable some fast channels for future ASC purposes?

For a certain investigation of the sum/diff module for MCT QPD/MC REFL QPD, I removed it from the system.

I undid Yuta's temporary setup, and put beam back on both WFS.  Since Koji had just aligned the Mode Cleaner, I centered the beam on the WFS using the WFS QPD screen, while watching the WFS Head screen, to make sure that the beam was actually hitting the QPD, and not off in lala land. 

[Mirko, Den]

Not satisfactory work of adaptive filtering make us to think about the signals that we use. Now we try to deal with mode cleaner and analize its length. We take MC_F channel. We know that MC_F is used as a feedback signal to the laser frequency and laser changes it's frequency linear to the input modulation signal up to ~1kHz. Than is MC_F is length of MC, not velocity or acceleration. If so, it's form due to seismic noise + company of other noises + stacks and wires should be approximately like the left plot. Instead we see the right plot.

Possibly, left-plot form signal is not possible to transmit through the wires and adc. Most signal at medium and high frequencies would be lost because of wire and adc noise. For that reason mode cleaner length signal might be amplified at frequecnies >~20 Hz by some bandpass filter.

Where is this highpass filter and what is the form of this filter?

It might be just after the photodetector in order not to transmit real mode cleaner length through the wires. But if wires and not very noisy, it could be somewhere before ADC.

But anyway, for the laser frequency feedback the corresponding low pass filter should be used.

Where is this lowpass filter and what is the form of the filter?

We followed the mode cleaner length signal up to TT FSS and measured the mode cleaner length, that is used as an input to TT FSS. As shown http://nodus.ligo.caltech.edu:8080/40m/5867 MC_F is different from the signal that is given to TT FSS. This is not clear because we do not have smth that could effect on the signal that much before branch node and recording of MC_F. The main difference is the cut off at the MC_F signal at 3 Hz. It might be a digital filter but we do not see any filters between adc_0_0 up to MC_F test point - straight line. This means that we have an analog filter somewhere between that blue box where the branch point is and ADC. We need to find it. But at least, we do not have a lowpass filter before FSS. So it is probably after it.

So, we need to find the 3 filters that we think affect on the MC_F channel in order to figure out why we have such a bad coherence between seismic signal and mode cleaner length.

 There should be a whitening filter in the Pentek Generic DAQ board (Eurocard with 8 differential LEMO inputs). It used to be that the MC_L channel came in through here and I believe it has 2 stages of 150:15 pole:zero filters.

I don't remember if it is one or two stages, but this should be easy to measure with a function generator or by driving this input using the MC2 UL Coil monitor and doing the transfer function in DTT (as Koji and Jenne did for the demod boards).

[Paco, Anchal]

- Saved BURT backup in /users/anchal/BURTsnaps/
- Copied existing code for mode cleaner noise budget from /users/rana/mat/mc. Will work on this from home to convert it inot new pynb way.

Get baseline IMC measurements (passive):
- MC_F:
  - What is MC_F? Let's find out.
  - On MC_F Cal window titled 'C1IOO-MC_FREQ', we turned off ON/OFF and back on again.
  - Using diaggui, we measured ASD of MC_F channel in units of counts/rtHz.

[Rana, Paco]

- Using diaggui, measured ASD from a template (under /users/Templates) and overlay the 1/f noise of the NPRO (Attachment 1)

[Anchal, Paco]

- WFS Master
  - Went through the schematic and tried to understand what is happening.
  - Accidentally switched on MC WF relief (python 3). Bunch of things were displayed on a terminal for a while and then we Ctrl-C it.
  - The only thing we noticed that change is a slight increase in WFS1 Yaw, and a corresponding decrease in WFS1 Pitch, WFS2 Pitch, and WFS2 Yaw.
  - We need to find out what this script does.

Future work:

• Create an automated script for taking MC_F_DQ spectrum and refer it against reference trace.
• Use pynb to create a noise budget for mode cleaner.
• Identify excess noise between 10-40 Hz.
• Configure output matrix in WFS Master to reduce the noise. Automate this process as well.