Keita, Sheila, Vaishali
Bullseye
On Friday we had a first look at some data from the new bullseye PD we installed this week. The point of installing this detector was to investigate the broad lump of noise which shows up at some interferometer alingments.
The first attachment shows the RIN measured on the QPD (NSUM) and the HPL diode, the bullseye signal which is labeled here as PIT and roughly calibrated into beam radii, and a yaw signal which is not correctly normalized or calibrated. The second attachment shows coherences. The bullseye signals is very coherent with intensity noise, and all the signals have small coherence with DARM both at low frequencies and up to nearly a kHz where the broad lump of noise was. (This was measured in our normal observing configuration where we don't see the broad lump of noise.) The third attachment shows the DAMR spectrum, with predictions for the level of noise based on the coherences with the bullseye detector (DARM ASD *sqrt(coherence)) Since there is a lot of coherence between the bullseye detector and intensity noise, I have also shown the intensity noise projection from the noise budget based on injections into the ISS second loop.
Other noise subtraction
Using the same long coherence data that we got for the bullseye coherences, I did a subtraction very similar to what Keita did in 33650. I used IMC WFS A+ B DC PIT and YAW, SRCL, PRCL, MICH, all 3 bullseye sensors, and ASC HARD control signals. At each frequency I used ony the channel that had the highest coherence, and estimated the noise in DARM attributed to that channel as DARM asd*sqrt(coherence). The fourth attached plot shows the estimations for some individual channels and the combined one which is the estimate for the most coherent signal at each frequency.
The last attachment shows the DARM spectrum with this signal subtracted (labeled subtraction residual) which looks very similar to Keita's result with only jitter channels subtracted, as well as this subtracted DARM with shot noise also subtracted (shown in green).
