The results of noise injection analysis are presented above. The code used is a python equivalent of the matlab code used for the analysis described here (59512). The code is shared in the following folder: /virgoDev/Automation/scripts/LSC/Pstab_injections.py

Here are the descriptions of the different figures attached:

--> Figure 1 : RIN for the injections at low and high frequencies. As expected the RIN is higher over the frequency of the injection. The RIN has been derived as the square root of PSD(PSTAB_AC/11*12*PSTAB_DC).

--> Figure 2 : Show the coherence between the RIN and h(t) during the injection at low frequency and high frequency. The projection will be done only for the values with a coherence higher than 0.5.

--> Figure 3 : Show the sensitivity curve for the 3 data set : the one used as reference (230 secondes before the first injection), the one during the injection at low frequency and the one during the injection at high frequency. We observe as expected higher strain over the frequency with noise injection.

--> Figure 4 : Show the projection. The projection is done only for the point with a coherence higher than 0.5 (see figure 2). The projection for the low frequencies is well reconstructed, but it seems that a part of the high frequency is missing by comparison with the plateau observed on the RIN (figure 1), and on the sensitivity curve during the injection (figure 3). I didn't found explanation to understand why the coherence is not satisfying for the high frequency injection.

Here is an update of the analysis presented above. In this new analysis, the ratio between the PSD of Hrec and the PSD of the PSTAB during the time of the injection is used for the projection instead of the transfert function. This is defined as:

PSD(Hrec(High_frequency_injection)) * (PSD(RIN_reference)/PSD(RIN_HIGH_FREQ_INJECTION)),

this ratio is plotted on the figure 1 and compared to the sensitivity curve during the time of the injection. Here we need to found a criteria to define which frequency keep for the projection. We tried two methods for the frequency selection.

Method 1:
Use the ratio between the PSD of the RIN during the injection and during the reference time. This is what is shown on the figure 2. The upper figure shows the PSD during the injection and during the reference time. The ratio of the two curves is plotted in the figure at the middle. For the projection, we keep only the frequency where the ratio is higher than three (the threshold is represented by the horizontal line). Finally, the projection with this method is shown on the bottom subfigure. We observe that several peak of the sensitivity curve are conserved during the projection.     

Method 2:

Use the ratio between the sensitivity curve during the injection and during the reference time. This is what is show on the figure 3. The upper subfigure show the two sensitivity curves, the one during the injection and the on during the reference time. As a criteria for the projection, we use the ratio between those two curves. The ratio is plotted on the middle graph of figure 3. The horizontal line show the position of a threshold equal to 2. Finally, The projection with this method is shown on the bottom subfigure of figure 3. With this methods, the peaks are no longer conserved.

The figure 4 show what the total projection with the second method look like. This projection is done, for the low frequency injection with the method presented in the previous logbook since no problem occur during the projection, and the high frequency projection is done with the method 2 presented in this logbook. We choose to keep the projection done with the method 2 because the peaks of the sensitivity curve are not conserved by the projection. Since the injection of noise keep the sensitivity curve below the peak, it seems reasonable to say that the method should not be able to show if the peaks are due to the PSTAB noise or not.