Speaker
Description
We have been detecting gravitational wave (GW) signals from coalescing compact binary systems for nearly a decade. The morphology of these signals can be shaped by a variety of intrinsic and extrinsic parameters. With 90 GW events reported up to the end of the O3 run and 128 already uncovered in the ongoing O4 run, the rapidly growing catalog presents new challenges. Morphological similarities between signals produced by different astrophysical effects and/or source parameters can complicate template-based searches. In particular, the modulation in a GW signal caused by the precession of a compact binary system may mimic the beating pattern characteristic of microlensed GW signals. The talk will explore the feasibility of distinguishing these two kinds of signals by utilizing machine learning based classification techniques. We also investigate whether these two kinds of signals could be distinguished from unlensed circular binary GWs.
