Had since yesterday evening some trouble with getting a channel from rfm on c1sus to oaf on c1lsc via dolphin. Several restarts of c1lsc and c1sus didn't help. At some point this morning a restart of c1lsc helped. Everything ok again.
At the bad time the dolphin TF looked like this:

Should be flat at gain 1 and no phase change obviously.

With fancy analysis tools approaching usability I looked some more into noise projections from PIT,YAW motion of the MC mirrors to MC length.

Injection channels are: C1:IOO-MC1-PIT_EXC. Actual injection signal is recorded in C1:IOO-MC1-PIT_OUT and similar.
Source channels for the projection are C1:IOO-WFS1_I_PIT_OUT_DQ and similar.
Response channel is C1:OAF-MCL_IN_IN1 or C1:IOO-MC_F_DQ.
MC auto-alignment was off.

1. Fixed sine injection @ 0.5Hz

Every injection lasted 4mins.

2. Filtered white noise injection

Generated white noise from 0.5Hz-20Hz, then filtered that in the C1:IOO-MC1-PIT and similar filters by the following TF, (Notch 1Hz, Q=3, 40dB &  2 zeros @ 1.1Hz)

All injections lasted 4mins. I left the filters in the first filter bank but disabled them. 

The Matlab NDS1 access seems to only work for some channels. With other channels it just hangs 'Busy' and does nothing.
Below you can see some channels that make matlab hang. Everyting happened on allegra. I tried compiling the NDS1 sources (from https://www.gravity.phy.syr.edu/dokuwiki/doku.php?id=ligodv:nds1_ligodv_install ) into mex files myself. Same result. I
 

a=NDS_GetChannels('fb:8088'); %/cvs/cds/caltech/apps/linux64/share/matlab/NDS_GetChannels.m
%data=NDS_GetData({'C1:IOO-MC_F_DQ'},1004826500,100,'fb:8088',a)     %Works
%data=NDS_GetData({'C1:IOO-WFS1_PIT_IN1_DQ'},1004826500,100,'fb:8088',a)     %Works
data=NDS_GetData({'C1:LSC-AS11_I_OUT'},1004826500,100,'fb:8088',a)         %Doesn't work, hangs
%%%which NDS_GetData.m: /cvs/cds/caltech/apps/linux64/share/matlab/NDS_GetData.m

Very elaborated measurement ;-)

On 11-11-08:
18:40 Stomp near STS1 for 2mins
18:47 Jump near GUR1 for 2mins
18:52 Walk from MC2 approx. half-way to vertex for 2mins

Tried to see if jumping / stomping the ground near STS1 / vertex or GUR1 / MC2 would show up in the seismometer or MC length data.
In GUR1 jumping / stomping clearly shows up in the timeseries. Also it clearly shows up as a low frequency signal if you walk to a position near MC2. E.g. walk from the vertex to MC2. Stop near the cones. Gives a big dip on GUR1X, that recovers in 10-20sec if you remain stationary. Big "hill" if you come from x-arm end and stop on the x side of MC2. So probably lots of tilt to GUR1X coupling at low frequencies.

Nothing was really visible in spectra (see below).

Resonances:

There appear to be a lot of resonances in the 10-20Hz range, see e.g. 1st attached pic.

Coherence:

Looking at the coherence of difference axis of the seismometers. Kind of dirty measurement, could have all kinds of reasons.
Quite a bit of coherence in STS1 at 5-6Hz. Possibly limiting the STS1X to MC-F coherence to up to 4Hz?

Put the accelerometers on top of MC2. Orientated as the arms,GUR1 and STS1:

Should be fixed a bit more rigidly.

Looking into the signals at a quiet time:

Hmm. Either the acc. are mislabeled or there is really bad x-y coupling. The connectors in the back of the acc. power supply / amplifier box are in ascending order.

Had to restart the elog many times. For some reason firefox 8 on Win 7 kills the elog pretty consistently when trying to make a new entry. IE9 works fine ....

 [Den, Mirko]

While doing the things below we accidentally misaligned the PSL laser. Thanks to Suresh and Jenne for realigning!!

There are a lot of strange features in MC_F (see for example http://nodus.ligo.caltech.edu:8080/40m/5738 )
To get some better understanding of the signals in the control loop we looked some more into what happens to the MC feedback signal after it exits the MC servo board (D040180 see DCC).

The MC_F signal is actually the servo signal: http://nodus.ligo.caltech.edu:8080/40m/5695
The Thorlabs temperature controller is actually used in the PZT path!

 We measured the LP filter in the PZT path (that is kind of mislabeled as temp.)

We looked into the signal from the MC servo board at different position at the PSL table.

We looked into the FB going into the temp. and PZT parts of the FB.
Temp.:

PZT:

We also looked at the signal in just in front of the FSS box No idea why the elog doesn't preview these pdfs.

Lots of extra noise there. We will check out where that comes from.

Regarding http://nodus.ligo.caltech.edu:8080/40m/5867 and http://nodus.ligo.caltech.edu:8080/40m/5869 :

MC_F signal:

The measurements on p. 5867 were done using the ADC attached to the PEM computer. There was a big difference between the MC_F signal recorded directly after the server board and the signal just before the FSS board as recorded by a PEM channel.
To understand how this happens we measured the signal at different places with a spec. analyzer:

1. WIth a locked MC measuring the signal just before the PEM ADCs (meaning after a 60ft BNC cable)
2. Same position, but unlocked and seemingly dark MC
3. Locked MC, signal just before the FSS box
4. MC_F signal that is usually going into the Pentek Generic board and is recorded in C1:IOO

=> The 60ft BNC cable adds a considerable amount of noise, but doesn't fundamentally change the signal. It is weird that the signal is white from approx. 4Hz on.
Due to Jenne's measurement ( http://nodus.ligo.caltech.edu:8080/40m/5848 ) we know the TF from MCL through PD, mixer Pentek and into C1:IOO looks like this:

This is with the double HP from 15Hz on that should be in the Pentek. So one might expect a less white signal going into the FSS board...

 PEM ADCs

The dark noise in the PEM ADCs is actually a factor 10 higher than in the IOO ADCs. Still ok wrt the the seismometers.
We also tried to measure essentially the dark noise of the whole seismometer readout (seismometer box, then ADC). That seemed ok, but is of limited value since the seismometer electronics behave a bit strange when there is no seismometer connected.

[Jenne, Mirko]

1. We should help the OAF by compensating for the actuator TF:

The actuator TF, from adaptive filter output to MC2, through PD, mixer, Pentek and into C1:IOO looks like this:

If we assume a white-ish error signal that the adaptive code tries to compensate for its job gets extra complicated because it has to invert this TF. So we really should compensate for that. Easiest place for that is the CORR filter directly behind the adaptive code block.

Using the TF measurement from above I used the vectfit (" /cvs/cds/caltech/apps/mDV/extra/firfit_forFotonMirkoComplex.m" ) to get fit a corresponding digital filter:

If we invert swap the zeros and poles in the digital filter we get the inverted TF.
(Todo: Figure out how to invert the TF. Just switching the poles and zeros doesn't work).

2. Wiener filtering

The idea was to use the adaptive filtering only for small corrections to the wiener filtering. So we really should try to get the wiener filtering going.

Howto:

1. Get data for STS1X and GUR1X and MC_F in matlab. E.g. via ligodv
2. Check the MC was in lock the entire time.
3, Filter MC_F with the actuator TF, so the wiener filter knows about that and compensates for it
4. Calculate the wiener filter " h1winolevLigoDV.m "
5. Export the data to the workspace. It is also saved to the disc as "h1filtcoeffTS.mat". Make sure there are first the witnesses, then MC_F
6. Execute " /cvs/cds/caltech/apps/mDV/extras/LHO/firfit_for_FotonMirko.m" while one directory higher. 
7. Copy the digital filter in SOS form that is printed into the matlab command line and put it into the corresponding filter in the OAF model via foton.

With data from 11-11-15 04:00 to 05:45. Sampling freq. 256Hz. 8000 Taps => length = 30.2s. Prefiltered to notch the 60Hz line in MC_F, but not compensation the actuator TF. This results in the following wiener filter and corresponding SOS filter to be copied into foton.
STS1X:

GUR1X:

Earlier this evening C1:LSC died then I hit the DAQ reload after adding an OAF channel to be recorded. No change to any model. Had to restart C1:SUS too. Reloaded burts from this morning 5am, except for C1:IOO, which I loaded from 16:07.

MC fell out of lock and was then quite badly misaligned. Mostly in pitch. I realigned it and it locked ok.

Turns out the MC falls often out of lock when the WFS servo comes on. I think the MC2_Trans history is not cleared on lockloss. I cleared it manually and realigned. Seems fine for now.

[Rana, Den, Mirko]

Updated the MC noise projection to include the longitudinal motion of the MC mirrors.

=> Lots of OSEM - local dampling noise!

Consistent with static wiener filter showing only benefits in the 1 - 4Hz region.

Some more info on this:
 

f > 1 Hz:

At these frequencies the pendulum should be quieter than the stacks. By quite a bit actually since there is the stack resonance at a couple Hz. 'Glueing' them together via the local control is not wise. We put an elliptic LP ( 2.5Hz, 4th order 6dB) into the C1:SUS-MC?_SUSPOS pathes and MC-F got better above 1Hz

Added an extra LP @ 10 Hz afterwards. Doesn't make a visible difference.

f < 1 Hz:

Now here is more stuff to consider.

1. The OSEMs glue the MC mirrors to the stacks
2. The pendulum TF should be 1
3. It shouldn't matter if the OSEMs do or do not act on the mirror at these frequencies, assuming they don't add extra noise.
4. Page http://nodus.ligo.caltech.edu:8080/40m/5547 seems to indicate OSEM sensor noise is so low it can be neglected.

Reduced OSEM gain below 1Hz:

If we reduce the gain in the OSEMs by adding additional HP filters ( cheby2, HP 0.3Hz, 6dB 4th order ) the happens:

1. MC length gets a bit more noisy at low frequencies - should be looked into some more
2. Coherence between the GUR1 seismometer and MC length goes up between 1E-2 and 1E-1 Hz:

( Ref is with low OSEM gain )

Possible explanation:

The stacks might be more correlatedly moving together than the pendulums. This would be not so nice for OAF test, but really fine for actually using the MC.
Todo: Measure the OSEM to seismometer coherences with high and low OSEM gains.

For reference the seismometer coherence with one another:

 The measurement was done with the MC in lock and the OSEMS active.

1. I injected noise into MC1-3 SUSPOS_EXC at a level that domiated the SUSPOS output.
2. Then I calculated the coupling coefficients of the SUSPOS outputs to MC_F during the time the noise is injected.
3. Without noise injection I projected the SUSPOS outputs to MC_F by multiplying the coupling coefficients with the SUSPOS outputs.

All on 11-11-18. White noise inj. from 0.1Hz to 20Hz. Duration 4mins each.

DOF      Amplitude(counts)     Time(UTC)
MC1      200                           22:08
MC2      25                             22:25
MC3      25                             22:50

Some thoughts on this, bare with me:

As you say this does not show the dark / bright noise of the OSEMs. It shows the influence of the OSEMS output onto MC_F in normal operation of the MC. I would have expected that to be very low everywhere except at the pendulum resonance. Reason for that not to be true could either be the OSEMs having considerable gain off of the resonance, or noise intrinsic to the OSEMs knocking the mirrors around. Since we know the OSEM signal to MC_F TF we only need to compare the OSEM signal to OSEM noise to see the noise contribution to MC_F. We know from http://nodus.ligo.caltech.edu:8080/40m/5547 that the OSEM sensor bright noise is considerably below the OSEM signal above 0.1Hz in actual operation. We checked that the MC OSEM signals are above the noise in the reference above 0.1Hz by a factor 3-10.

We actually measured the cost function with the noise projection (valid to 10Hz). It's just the coupling coefficient, right?

[Den, Mirko]

We looked some more into the the OSEM signals and their coherence to the seismometer signals.

We were able to verify that the coherence OSEM sensor <-> seismometer signal goes down with increasing the OSEM gain. This seems to indicate that the OSEM FB add noise to the distance mirror <-> frame. We injected some noise into the OSEMs to see how the coherence behaves.

MC2 SUSPOS, 0.1Hz - 0.8Hz, 3mins each

Inj. amplitude   Time(UTC) Note

-                     21:35          Free swinging
-                     21:42          Big LF OSEM gain
-                     21:48          Small LF OSEM gain
150                     21:56          -"-
300                     22:00          -"-
900                     22:05          -"-

Free swinging:

High OSEM gain:

Low OSEM gain:

We left the filters that lower the OSEM gain below 0.3Hz on.

[Jenne, Mirko]

To reiterate: We changed the OSEM loop shape for MC1-MC3. Below in black is the old loop shape, which simulated pendulum response in there. In red is the new loop shape.

The differences are due to extra filter in C1:SUS-MC?_SUSPOS module 6,7,9

6: Elliptical LP @ 2.5Hz
7: Inverse Chebychev HP @0.3Hz
8: 1st order LP @ 10Hz

This has the potential to be unstable, but is not. At some point these filters should be tuned further.

For some reason C1PEM doesn't seem to work anymore after a recompilation. It did recompile fine. We just changed some channel / subsystem names.

Tried reverting to the svn version. Doesn't work. Reboot C1SUS also no good.

 It is fine again. Thanks Jamie.

Tried measuring the actuator matrix for MC1.

With the watchdogs tripped I cut the loops for pos, pitch and yaw open just before the servos. Then I injected a fixed sine at 0.4Hz into the three DOFs (suspos, suspit, susyaw) one by one, while looking into the error signal just before the servos.

                                                         Response DOF

                                     pos                 pit             yaw

Injection DOF pos          0.008417       0.00301        0.004975
                     pit            0.01295         0.01959        0.0158
                     yaw         0.007188        0.002152     0.0144

Inverting that and dividing by the norm gives us

 0.8322   -0.1096   -0.1669
-0.2456    0.2869   -0.2293
-0.3777    0.0118    0.4211

Somehow putting this into the 'To coil' matrix has an effect even with the watchdog tripped!?!?

The Striptool for the BLRMS seismic channels is running now. Channels are ( still ) recorded as slow EPICS channels.

A big peak in the 0.1 - 0.3Hz seismic region in both GUR1 and STS1 irritated us for a while. I added an extra LP filter @ 0.05Hz to the RMS_LP modules.

I calculated the F2A filters for the input mode cleaner optics as described in T010140-01-D eq (4). On Ranas recommendation I added an s/ ( w_0 * Q ) term to the numerator.

The used values are:

w_0 = 2pi / s
h= 0.0009
D= 2.46957E-2
Q=10

I put theses filters into C1:SUS-MC1_TO_COIL_1_1 to _4_1 . For convenience split in Z and P. Well it doesn't work. After a few seconds the optic begins to swing wildly.

Tried the wiener filter with the TF from p.5900

Tried it out with the TFs from p.5900:

Adding a filter element that compensates the acutator TF makes the MC lose lock.

[Rana, Den, Mirko]

It seems you can shoot yourself in the foot if your filter modules are too complex.

Den discovered this when looking into the C1:SUS-MC?_SUSPOS filter module named Cheby, consisting of cheby1("LowPass",6,1,12)cheby1("LowPass",2,0.1,3)gain(1.13501) by noticing that the coherence between input and output of the filter is low.

Cheby filter:

This is most likely due to the filter spanning more than the 16 orders of precision that the double data type spans.

The coherence is fine when one splits the filter in two, giving every cheby1 filter its own module. The coherence is also fine when you use the Cheby filter in a 2kHz system, although the freq. response looks very odd

Black: 16kHz, Red 2kHz (yes the filter was converted correctly, no text file editing there)

The problem occurs on c1lsc as well as c1sus computer.

Looking into the foton files actually points to a precision problem, with the huge range of scale covered in there:

C1:MCS 16kHz (Cheby: Original filter with low coherence. CHbyTST & ChebyTST: Original filter split amongst two filter modules)
################################################################################
### SUS_MC3_LSC                                                              ###
################################################################################
# DESIGN   SUS_MC3_LSC 0 zpk([0],[30],0.333333,"n")
# DESIGN   SUS_MC3_LSC 1 cheby1("LowPass",6,1,12)
# DESIGN   SUS_MC3_LSC 2 cheby1("LowPass",2,0.1,3)gain(1.13501) \
#                       
# DESIGN   SUS_MC3_LSC 3 cheby1("LowPass",2,0.1,3)gain(1.13501)cheby1("LowPass",6,1,12)
# DESIGN   SUS_MC3_LSC 4 ellip("BandStop",4,1,40,16.1,16.9)ellip("BandStop",4,1,40,23.7,24.5)gain(1.25871)
###                                                                          ###
SUS_MC3_LSC 0 12 1  32768      0 30:0.0          9.942903833923793  -0.9885608209680459   0.0000000000000000  -1.0000000000000000   0.0000000000000000
SUS_MC3_LSC 1 21 3      0      0 CHbyTST     9.095012702673064e-18  -1.9978637592754149   0.9978663974923444   2.0000000000000000   1.0000000000000000
                                                                 -1.9984258494490537   0.9984376515442090   2.0000000000000000   1.0000000000000000
                                                                 -1.9994068831713223   0.9994278587363880   2.0000000000000000   1.0000000000000000
SUS_MC3_LSC 2 12 1  32768      0 ChebyTST    1.228759186937126e-06  -1.9972699801052749   0.9972743606395355   2.0000000000000000   1.0000000000000000
SUS_MC3_LSC 3 12 4  32768      0 Cheby       1.117558041371939e-23  -1.9972699801052749   0.9972743606395355   2.0000000000000000   1.0000000000000000
                                                                 -1.9978637592754149   0.9978663974923444   2.0000000000000000   1.0000000000000000
                                                                 -1.9984258494490537   0.9984376515442090   2.0000000000000000   1.0000000000000000
                                                                 -1.9994068831713223   0.9994278587363880   2.0000000000000000   1.0000000000000000
SUS_MC3_LSC 4 12 8  32768      0 BounceRoll     0.9991466189294013  -1.9996634951844035   0.9997010181703262  -1.9999611719719754   0.9999999999999997
                                                                 -1.9999303040590390   0.9999684339228864  -1.9999605309876360   0.9999999999999999
                                                                 -1.9999248796830529   0.9999668732412945  -1.9999594299327190   1.0000000000000002
                                                                 -1.9996385459838455   0.9996812069238987  -1.9999587601905868   1.0000000000000000
                                                                 -1.9996161812709703   0.9996978939989944  -1.9999163485656493   0.9999999999999999
                                                                 -1.9998855694973159   0.9999681878303275  -1.9999154056705493   0.9999999999999998
                                                                 -1.9998788577090287   0.9999671193335300  -1.9999137972442669   1.0000000000000000
                                                                 -1.9995951159123118   0.9996843310430819  -1.9999128255920269   1.0000000000000000

C1:OAF 2kHz
###############################################################################
### YARM_IN                                                                  ###
################################################################################
# DESIGN   YARM_IN 0 zpk([0],[30],0.333333,"n")
# DESIGN   YARM_IN 3 cheby1("LowPass",6,1,12)cheby1("LowPass",2,0.1,3)gain(1.13501)
# DESIGN   YARM_IN 4 ellip("BandStop",4,1,40,16.1,16.9)ellip("BandStop",4,1,40,23.7,24.5)gain(1.25871)
# DESIGN   YARM_IN 8 cheby1("LowPass",6,1,12)cheby1("LowPass",2,0.1,3)gain(1.13501)zpk([],[10],1,"n")
###                                                                          ###
YARM_IN  0 12 1   4096      0 30:0.0           9.56649943398763  -0.9119509539166185   0.0000000000000000  -1.0000000000000000   0.0000000000000000
YARM_IN  3 12 4   4096      0 Cheby       1.829878084970283e-16  -1.9828889048300398   0.9830565293861987   2.0000000000000000   1.0000000000000000
                                                                 -1.9868188576622443   0.9875701115261976   2.0000000000000000   1.0000000000000000
                                                                 -1.9940934073784453   0.9954330165532327   2.0000000000000000   1.0000000000000000
                                                                 -1.9781245722853238   0.9784022621062476   2.0000000000000000   1.0000000000000000

 [Rana, Mirko]

I redid this calculation. The idea behind it is to get rid on any pitch that is introduced by applying longitudinal feedback to the mirrors. This coupling happens because the center of percussion for pitch , which is identical with the point where the wires lift off of the mirror, is above the center of mass.

With the same values as before, just less faulty math and Q = 2 instead of 10 we end up with the following filters:

For the lower coils (red), compared to corresponding preexisting BS filters (black):

The upper coils' TF is just mirrored at the 0dB magnitude axis, and have a corresponding frequency response.

I switched the F2a filters on for all MC mirrors. For convenience they are split into F2aZeros and F2aPoles. Everything seems fine. The F2a filters seem to be off for ( all ?) other mirrors.

We replaced the complicated Cheby filter module with three separate filter modules. Probably the filter doesn't need to be so complicated, but rather not change too many things at once. The new filter modules are called:
Ch1, Ch2, Ch3 and are in filter module 3,9, and 10 of the C1:SUS-MC?_SUSPOS filters. The coherence with these filters is fine. Someone should look into the possibility of simplifying these filters.

It would be good to check for numerical problems in other filters!

[Rana, Mirko]

I tried out the virtual pendulum idea today. The idea is to compensate the physical pendulum via the control system, and then add a virtual pendulum formed in the control system. We know the actuator TF from p. 5900 and apply its inverse to the C1:SUS-MC?_SUSPOS filters. Also we add an pendulum Q=3 with a resonance frequency of 0.1Hz to the POS control loops.

The result is pretty awesome!

1. Black: Standard config. Wfs on. New Cheby filter in place ( p. 6031 )
2. Red: With virtual pendulum. Extra eliptic LP filter @ 2.5Hz

Filter shape:

This is stable for 5-10minutes, at which point it falls out of lock, swinging in yaw.

In the above entry MC_f  signal is improved off of resonance by the implementation of the pendulum compensation. It should be checked if this is actually due to the implementation of the virtual pendulum at 0.1Hz. A way to check that might be to implement a simple double LP at 0.1Hz instead and look at the resulting MC_f signal. A projection of the OSEM FB noises with the compensation active might be interesting.
The physical resonance at 1Hz is clearly not compensated correctly, which is probably the reason for the lock losses after a few minutes. It might be a good start to measure the residual resonance with the compensation in place. The filters in bank 7 of C1:SUS-MC?_SUSPOS have both the compensation of the 1Hz resonance( really the inverse actuator TF ) and the virtual pendulum in them. The ‘pure’ compensation can be found in the InvTF module in the C1:OAF-ADAPT_MCL_CORR filter.
The fact that the beam swings in yaw at lock loss indicates that the separation of the DOFs might not be perfect. One should have a look into the yaw and pitch DOFs with the compensation active.

I have gotten the hang of the procedure for measuring phase noise on the AOMs. 

Koji suggested I right up a short guide (wiki page?) on how to do this. 

I will finish up here, then go measure the AOMs at the other lab (may have to be tomorrow, after laser safety), and then write up the instructions.

Here is the result for the measurement of the phase noise.  We used the marconi function generator and compared it with an Isomet AOM driver (model 232A-1), so this is really a measure of the relative phase between them.  We used a 5x gain and a frequency response of 13 Hz/V for the modulation.  In all the attached plots, the blue is the data and the red is the measurement limit (as determined by the noise in the SRS785).  Also note that the units on the yaxis of the Phase noise plot are incorrect, they should be dB/Sqrt(Hz), I will fix this and edit as soon as possible.

I have made some measurements of the R value for some coatings we are interested in.  The plots have statistical error bars from repeated measurements, but I would suspect that these do not dominate the noise, and would guess these should be trusted to plus or minus 5% or so.  They still should give some indication of how useful these coatings will be for the green light.  I plan to measure for the ITM as soon as possible, but with the venting and finals this may not be until late this week.

EDIT (12/9/09): I fixed the label on the y axis of the plots, and changed them to png format.

Attached are updated plots of the T&R Measurements for a variety of mirrors, and diagrams for the setup used to make the measurements.

T is plotted for the 1064 nm measurement, since these mirrors are highly reflective at 1064, and either R or R&T are plotted for the 532 nm measurement, depending on how larger the R signal is.

As with the previous set of plots, the error bars here are purely statistical, and there are certainly other sources of error not accounted for in these plots.  In general, the T measurement was quite stable, and the additional errors
are probably not enormous, perhaps a few percent.

The mirrors are:

Y1-1037-00.50CC

Y1-2037-45S

Y1-2037-45P

Y1S-1025-0

Y1S-1025-45

The most up-to-date T and R plots for the Y1 and Y1S mirrors, as well as a T measurement for the ETM, can be found on:

http://lhocds.ligo-wa.caltech.edu:8000/40m/Upgrade_09/Optics/RTmeasurement

 It looks like the PLL drifted alot over the weekend, and we couldn't get it back to 9 dBm.  We switched back to the new focus wideband PD to make it easier to find the beat signal.  I replaced all the electronics with the newly fixed UPDH box (#17) and we aligned it to the biggest beat frequency we could get, which ended up being -27 dBm with a -6.3V DC signal from the PD.  

Locking was still elusive, so we calculated the loop gain and found the UGF is about 45 kHz, which is too high.  We added a 20 dB attenuator to the RF input to suppress the gain and we think we may have locked at 0 gain.  I am going to add another attenuator (~6 dB) so that we can tune the gain using the gain knob on the UPDH box.  

Finally, attached is a picture of the cable that served as the smb - BNC adaptor for the DC output of the PD.  The signal was dependent on the angle of the cable into the scope or multimeter.  It has been destroyed so that it can never harm another innocent experiment again!

We have managed to lock the PLL to reasonable stability. The RF input is attenuated by 26 dBm and the beat signal locks very close to the carrier of the marconi (the steps on the markers of the spectrum analyzer are coarse).  We can use the marconi and the local boost of the pdh box to catch the lock at 0 gain.  Once the lock is on, the gain can be increased to stabilize the lock.  The locked signals are shown in the first photo (the yellow is the output of the mixer and the blue is the output to the fast input of the laser.  If the gain is increased too high, the error signal enters an oscillatory regime, which probably indicates we are overloading the piezo.  This is shown in the second photo, the gain is being increased in time and we enter the non-constant regime around mid-way through.

Tomorrow I will use this locked system to measure the PZT response (finally!).

 After realigning and getting the lock today, I tried to add in the SR785 to measure the transfer function.  As soon as I turn on the piezo input on the PDH box, however, the lock breaks and I cannot reacquire it.  We are using an SR650 to add in the signal from the network analyzer and that has worked. We also swapped the 20 dB attenuator for a box which mimics the boost functionality (-20 dB above 100 Hz, 0 dB below 6Hz).  I took some spectra with the SR750, and will get some more with the network analyzer once Alberto has finished with it. 

The SR750 spectra is posted below.  The SR750 only goes up to 100 kHz, so I will have to use the network analyzer to get the full range. 

I just put a script in the /cvs/cds/caltech/scripts/general/netgpibdata/ directory to control the network analyzer called AG4395A_Run.py .   A section has been added to the wiki with the other GPIB script sections (http://lhocds.ligo-wa.caltech.edu:8000/40m/netgpib_package#AG4395A_Run.py)

I took data for the 2 NPRO PLL using the script I wrote for the AG4395, but it is very noisy above about 1 MHz.  I assume this is something to do with the script (since I am fairly confident we don't have 600 dB response in the PZT), so I will go in tomorrow to more carefully understand what is going on, I may need to include a bit more latency in the script to allow the NA to settle a bit more.  I am attaching the spectrum just to show the incredibly high noise level, 

Kiwamu and I measure the PZT response of the Innolight this evening from 24 kHz to 2MHz.  

We locked the PLL at ~50 MHz offset using the Lightwave NPRO and and swept the Innolight with the network analyzer (using the script I made; it has one peculiar property, but it does work correctly).  

We will post the plot of the Lightwave PZT response tomorrow morning.

**EDIT**: As Koji pointed out, the calibration factor on this plot is WRONG.  See my more recent update for the correctly calibrated plot.

 Koji is absolutely right.  I just double checked my matlab code, and saw that I divided when I should have multiplied.  The correctly calibrated plots are attached here for the Innolight and the lightwave.  Kiwamu and I will measure the amplitude and the jitter today.

 We realized that we had measured the wrong calibration value; we were using the free-running error signal with the marconi far from the beat frequency, which was very small.  When we put the Marconi right at the beat, the signal increased by a factor of ~12 (turning our original calibration of 10 mV/rad into 120 mV/rad).  The re-calibrated plots are attached. 

 We measured the Amplitude Modulation response of the PZTs, to find regions with large phase modulation but small amplitude modulation.

We did this by blocking 1 arm of the PLL, feeding the source output of the Network Analyzer into the PZT input of the laser in question, and reading the output of the PD on the NA.  We calibrated by dividing by the DC voltage of the PD (scaled by the ratio of the AC gain to DC gain of the New Focus PD).

The AM response of the Innolight looks fairly smooth up to ~1MHz, and it is significantly below the PM response for most of its range.  The region between 20 and 30 kHz shows very good separation of about 10^3 rad/RIN (and up to 10^5 rad/RIN at ~21.88 kHz, where there is the negative spike in the AM response). The region between 1.5 MHz and 2MHz also looks viable if it is desirable to actuate at higher frequencies.

The Lightwave offers very good AM/PM separation up to about 500 kHz, but becomes quite noisy about 1MHz.

 I redid the PZT Phase Modulation measurement out to 5 MHz for both the Innolight and the Lightwave.  The previous measurement stopped at 2MHz, and we wanted to see if there were any sweet spots above 2MHz.  I also reduced the sweep bandwidth and increased the source amplitude at high frequency to reduce the noise (the Lighwave measurement, especially, was noise dominated above 1MHz).  I also plotted the ratio of PM/AM in rad/RIN, since this is the ultimate criterion on which we want to make a determination.

It looks like there is nothing extremely useful above 2MHz for either laser.  There are several candidates for the lightwave at about 140 kHz and again at about 1.4 MHz.  The most compelling peak, however, is in the innolight at 216 kHz, where the peak is about 2.3e5 rad/RIN.

Below about 30kHz, the loop suppresses the measurement, so one should focus on the region above there.

You guys must work harder.

 Isn't this still a factor of 2 away from the limit in the paper?

the lead spheres that were placed below the granite slab have been flattened by hammering to have lesser degree of wobbling of the slab.

the height of each piece, and the flatness of their surfaces was checked by placing another slab over them and checking by the spirit level.

From how much to how much have you chnged the gain?

I changed the gains from all 4 0.01 to o.27, 0.23, 0.32 and 0.11 and the main alignment gain to be 0.8

I like to put the credit to Aidan for teaching Nancy how to use FOTON.

 Yes, I am sorry for not mentioning this.

Thanks Aidan

I have spent my first few days as a SURF getting experience working with the Network/Spectrum Analyzer (AG 4395A). After an introduction to the 40m by Koji, I was tasked with using the AG4395A to measure the transfer function of several filters (for example, Mini-Circuits Low Pass Filter SLP-30). I am now familiar with configuring the AG 4395A, taking a single set of data using a command from one of the control computers, and plotting the dataset as a Bode plot (separate plots for magnitude and phase) using Python.

To Do:

• Use AGmeasure to take multiple datasets with a single command.
• Plot multiple datasets for each filter on a single Bode plot and perform some statistical analysis. 

To experiment with plotting multiple datasets on a single Bode plot, I used a single dataset from the Network Analyzer using the SLP-30 filter and added random noise to create ten datasets to plot. I am attaching the resulting Bode plot, which has the ten generated sets of data plotted along with their average.

We discussed with Rana and Koji how to interpret this type of dataset from the Network Analyzer. Instead of considering the magnitude and phase as separate quantities, we should consider them together as a single complex number in the form H(f) = M exp(iπP/180), where M is the magnitude and P is the phase in degrees. We can then find the average value of the measured quantity in its complex number form (x + iy), as opposed to just taking the average of the magnitude and phase separately.  

I have been working on using PyKat to run Finesse. There appear to be several ways to run an equivalent simulation using Finesse:

1: .kat only

Run a .kat file directly from the terminal. For example, if in the directory containing the Finesse kat.ini file, run the command ‘./kat file.kat’. This method does not use PyKat.

To edit the simulation using this method, one must directly edit the .kat file. This is not ideal, as all parameters must be hard-coded, and there is no looping method for duplicate commands.

Both of the following methods use PyKat in some manner. To run Finesse using PyKat from a .py file, the command ‘from pykat import finesse’ should be included. In addition, two environment variables must be defined:

• ‘FINESSE_DIR': directory containing ‘kat’ executable
• ‘KATINI’: location and name of kat.ini file

Within a .py file running PyKat, the kat object contains all of the optical components and their states. To create a kat object, we use the command:

kat = finesse.kat()

2: .kat + .py

To load Finesse commands from a .kat file, we can use the command loadKatFile(). For example, using the kat object as defined above:

kat.loadKatFile(‘file.kat’)

The kat object now contains any components defined in the .kat file. The states of these components can be altered using PyKat. For example, if in the .kat file, we defined a mirror named ‘ITM’, with R = 0.9, T = 0.1, phi = 0, and with nodes 1 and 2 to its left and right, respectively, using the Finesse command

m ITM 0.9 0.1 0 n1 n2

we can now alter the state of the mirror using a PyKat command such as

kat.ITM.phi = 30

which changes the ‘phi’ property of the mirror to 30 degrees. Once all alterations to objects are made, we can run Finesse using the command

out = kat.run()

which stores the output of the Finesse simulation in the variable out.

3: .py only

We can also run a Finesse simulation without any .kat file. There are two ways to define Finesse objects within a .py file.

- Parse a string containing Finesse commands, as would be found in a .kat file, using the command parseCommands(). For example,

            kat.parseCommands(‘m ITM 0.9 0.1 0 n1 n2’)

defines the same mirror as above. This object can now be altered using pyKat in the same manner as above.

- Define an object using the classes defined in PyKat. For example, to define the same ITM mirror, we can use:

ITM = mirror(‘ITM’, ‘n1’, ‘n2’, 0.9, 0.1, 0)

kat.add(ITM)

The syntax for these classes can be found in the files included in the PyKat package named ‘commands.py’, ‘detectors.py’, and ‘components.py’.

We can also run Finesse commands (rather than just defining components) using their respective classes. These must also be added to the kat object. For example:

x = xaxis(‘lin’, [‘-4M’, ‘4M’], ‘f’, 1000, ‘laser’)

kat.add(x)

This runs the command ‘xaxis’, which sets the x-axis of the output data to run from freq = -4 MHz to 4 MHz, in 1000 steps. This is equivalent to the following Finesse command:

xaxis laser f lin -4M 4M 1000

In theory, we should be able to use PyKat to run any Finesse command. However, not all Finesse commands appear to be defined in PyKat; one example is the Finesse command ‘yaxis’, which I cannot locate in PyKat. In addition, I have had difficulty running some commands such as ‘cav’ and ‘pd’, despite following their class definitions in the PyKat files. However, these commands can still be easily run in PyKat using parseCommands().