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Message ID: 16373     Entry time: Mon Oct 4 15:50:31 2021
Author: Hang 
Type: Update 
Category: Calibration 
Subject: Fisher matrix estimation on XARM parameters 

[Anchal, Hang]

What: Anchal and I measured the XARM OLTF last Thursday.

Goal: 1. measure the 2 zeros and 2 poles in the analog whitening filter, and potentially constrain the cavity pole and an overall gain. 

          2. Compare the parameter distribution obtained from measurements and that estimated analytically from the Fisher matrix calculation.

          3. Obtain the optimized excitation spectrum for future measurements.   

How: we inject at C1:SUS-ETMX_LSC_EXC so that each digital count should be directly proportional to the force applied to the suspension. We read out the signal at C1:SUS-ETMX_LSC_OUT_DQ. We use an approximately white excitation in the 50-300 Hz band, and intentionally choose the coherence to be only slightly above 0.9 so that we can get some statistical error to be compared with the Fisher matrix's prediction. For each measurement, we use a bandwidth of 0.25 Hz and 10 averages (no overlapping between adjacent segments). 

The 2 zeros and 2 poles in the analog whitening filter and an overall gain are treated as free parameters to be fitted, while the rest are taken from the model by Anchal and Paco (elog:16363). The optical response of the arm cavity seems missing in that model, and thus we additionally include a real pole (for the cavity pole) in the model we fit. Thus in total, our model has 6 free parameters, 2 zeros, 3 poles, and 1 overall gain. 

The analysis codes are pushed to the 40m/sysID repo. 

===========================================================

Results:

Fig. 1 shows one measurement. The gray trace is the data and the olive one is the maximum likelihood estimation. The uncertainty for each frequency bin is shown in the shaded region. Note that the SNR is related to the coherence as 

        SNR^2 = [coherence / (1-coherence)] * (# of average), 

and for a complex TF written as G = A * exp[1j*Phi], one can show the uncertainty is given by 

        \Delta A / A = 1/SNR,  \Delta \Phi = 1/SNR [rad]. 

Fig. 2. The gray contours show the 1- and 2-sigma levels of the model parameters using the Fisher matrix calculation. We repeated the measurement shown in Fig. 1 three times, and the best-fit parameters for each measurement are indicated in the red-crosses. Although we only did a small number of experiments, the amount of scattering is consistent with the Fisher matrix's prediction, giving us some confidence in our analytical calculation. 

One thing to note though is that in order to fit the measured data, we would need an additional pole at around 1,500 Hz. This seems a bit low for the cavity pole frequency. For aLIGO w/ 4km arms, the single-arm pole is about 40-50 Hz. The arm is 100 times shorter here and I would naively expect the cavity pole to be at 3k-4k Hz if the test masses are similar. 

Fig. 3. We then follow the algorithm outlined in Pintelon & Schoukens, sec. 5.4.2.2, to calculate how we should change the excitation spectrum. Note that here we are fixing the rms of the force applied to the suspension constant. 

Fig. 4 then shows how the expected error changes as we optimize the excitation. It seems in this case a white-ish excitation is already decent (as the TF itself is quite flat in the range of interest), and we only get some mild improvement as we iterate the excitation spectra (note we use the color gray, olive, and purple for the results after the 0th, 1st, and 2nd iteration; same color-coding as in Fig. 3).   

 

 

 

Attachment 1: tf_meas.pdf  220 kB  Uploaded Mon Oct 4 16:54:17 2021  | Hide | Hide all
tf_meas.pdf
Attachment 2: fisher_est_vs_data.pdf  163 kB  Uploaded Mon Oct 4 16:54:36 2021  | Hide | Hide all
fisher_est_vs_data.pdf
Attachment 3: Pxx_evol.pdf  159 kB  Uploaded Mon Oct 4 16:54:49 2021  | Hide | Hide all
Pxx_evol.pdf
Attachment 4: fisher_evol.pdf  181 kB  Uploaded Mon Oct 4 16:55:03 2021  | Hide | Hide all
fisher_evol.pdf
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