Automated Evaluation of Environmental Coupling for Advanced LIGO Gravitational Wave Detections

Author(s)

Helmling-Cornell, Adrian, Nguyen, Philippe, Schofield, Robert, Frey, Raymond

Abstract

The extreme sensitivity required for direct observation of gravitational waves by the Advanced LIGO detectors means that environmental noise can potentially contaminate gravitational wave signals. Consequently, environmental monitoring efforts have been undertaken and novel noise mitigation techniques have been developed which have helped keep environmental artifacts from influencing gravitational wave detections for the $90$ gravitational wave events detected from 2015--2020 by the aLIGO detectors. The increasing rate of gravitational wave detections due to detector sensitivity improvements requires sophisticated, reliable and automated ways to monitor and assess the degree of environmental coupling between gravitational wave detectors and their surroundings. We introduce a computational tool, PEMcheck, for quantifying the degree of environmental coupling present in gravitational wave signals using data from the network of environmental monitoring sensors. We study its performance when applied to the $79$ gravitational waves confidently detected in LIGO's third observing run and test its performance in the case of extreme environmental contamination of gravitational wave data. We find that PEMcheck's automated analysis identifies only a small number of gravitational waves that merit further study by environmental noise experts due to possible contamination, a substantial improvement over the manual vetting that occurred for every gravitational wave candidate in previous observing runs. Overall, PEMcheck works as intended. Consequently, PEMcheck will play a critical role in event validation during LIGO's fourth observing run.

Figures

Vibrational coupling between \ac{LLO}'s \ac{HAM} 6 vacuum chamber Z-axis accelerometer and \ac{DARM} as measured prior to \ac{O3}. The vibrational coupling here is likely driven by stray light scattering off of the septum window dividing this vacuum chamber and the adjoining \ac{HAM} 5 chamber and then recombining with the main beam~\cite{septumalog}. The large fraction of upper limit estimates, rather than measured values, for the vibrational coupling is because \ac{PEM} injections could not be increased to an amplitude such that the injection was visible in the \ac{DARM} data without saturating the accelerometer signal. Each sensor count corresponds to $\unit[6.1]{\mu m~s^{-2}}$ of acceleration in the vertical direction~\cite{PEMpage}.

\ac{ASD} of the Z-axis \ac{HAM} 6 accelerometer during the background time. Background \ac{PEM} sensor data is used to compute the tuned \ac{CF} of section~\ref{sssec:tunedasd}. $\unit[45.75]{s}$ of sensor data were used to calculate this \ac{ASD}.

Top: Comparison of the \ac{CF} interpolated from the data in figure~\ref{fig:example_cf} to the interpolated, tuned \ac{CF} computed by analyzing the \ac{DARM} background \ac{ASD}. The untuned and tuned predictions for the \ac{ASD} largely agree, except near $30$ and $\unit[90]{Hz}$. The points where environmental contributions to \ac{DARM} are overestimated and need tuning are derived from upper limit estimates of the chamber motion to \ac{DARM} coupling. These frequencies are marked with black arrows. Bottom: Comparison of the \ac{DARM} $t_{\mathrm{back}}$ \ac{ASD} with the estimated contribution from the \ac{HAM} 6 accelerometer. The result of the tuning procedure is to constrain the predicted environmental contribution from a sensor to be not greater than the observed \ac{DARM} \ac{ASD}. As in the top plot, black arrows mark where the untuned \ac{CF} predicts that the \ac{DARM} \ac{ASD} should exceed its observed value to the \ac{HAM} 6 accelerometer data. These are the points which require tuning to reconcile the predicted and actual \ac{DARM} \ac{ASD}s.

The results of the $c$-statistic calculation for each spectrogram tile for the \ac{LLO} \ac{HAM} 6 accelerometer during GW190707. The value of $1-c$ is plotted for each tile so that time-frequency tiles with the highest likelihood of contamination, as calculated by \textsc{PEMcheck}, appear brighter. The time-frequency tiles enclosed by the red box track the evolution of the \ac{GW} signal as predicted by \ac{NR}. The lowest $c$-statistic found within the \ac{GW} track occurs at $\sim\unit[0.1]{s}$ and $\sim\unit[78]{Hz}$ prior to the event's $t_c$. A minimum $c$-statistic of $0.52$ indicates that environmental disturbances witnessed by this sensor do not couple to the \ac{GW} strain data during the event.

Histogram of the minimum $c$-statistic calculated by \textsc{PEMcheck} for all GWTC-2.1 and GWTC-3 confident events using the pre-\ac{O3} coupling data. The \textsc{PEMcheck} analysis identifies $6$ of the $149$ \ac{O3} \ac{GW} events as having a minimum $c$ below $0.2$

Cumulative distribution of the $c$-statistic found for each \ac{PEM} channel studied by \textsc{PEMcheck} for each \ac{GW} event in \ac{O3} using the pre-\ac{O3} coupling data. Each light grey trace corresponds to the \ac{CDF} of the $c$-statistic for an individual \ac{GW} event, while the black trace denotes the mean number of sensors with that particular value of $c$ or less. GW190707 as well as the three events with the lowest $c$ are highlighted.

\ac{CDF} of the $c$-statistic for each run of \textsc{PEMcheck} at \ac{LHO} with GW200115's properties. The \ac{CDF} marked ``foreground" corresponds to \textsc{PEMcheck} run at the actual time of the \ac{GW} event.

Below: constant-Q transform of \ac{LLO} \ac{GW} strain data during a thunderclap witnessed. The 31 red time-frequency tracks overlaid on the thunderclap data represent 31 hypothetical \ac{GW} time-frequency tracks with the properties given in table~\ref{tab:190521g_props} vetted by \textsc{PEMcheck}. Above: the lowest value of $c$ found by \textsc{PEMcheck} for the series of hypothetical \ac{GW} tracks overlaid on thunderclap data. The channel with the lowest $c$-statistic for a given trial is denoted by the marker style. The bold line corresponds to $c=0.2$.

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