Gravity Seminar: Moving towards the analysis of gravitational-wave data in the next-generation detector era, Justin Janquart, Utrecht University, The Netherlands

Since 2015, the LIGO-Virgo-KAGRA collaboration has been detecting and analyzing gravitational-wave signals, with about 90 observations of compact binary coalescence signals after the third-observing runs. As the detectors get upgraded and their sensitivity enhanced, the detection rate will increase. This will put more strain on our current analysis methods. This stress will increase even more when moving to the next generation of ground-based detectors such as Einstein Telescope and Cosmic Explorer. On the one hand, their increased sensitivity will lead to many more detectable signals. On the other hand, their increased sensitive frequency range will lead to the signals being in band for a longer period of time. The combination of these two effects will lead to signals overlapping one another, requiring adapted analysis methods. Here, after having established how often overlaps occur, we explore different ways of analyzing data when signals overlap. In particular, we look at how one can adapt the single-signal Bayesian framework to multiple signals and show a proof-of-concept application of machine learning techniques. While not fully developed yet, these methods are capable of analyzing overlapping signals, paving the way for the development of more complete and robust methods to analyze data in the future.