Stacking time-frequency maps to enhance BNS postmerger gravitational wave signal detectability and parameter extraction

Gravitational wave (GW) signals generated by binary neutron star (BNS) coalescences encode clues about the neutron star equation of state in both the inspiral and postmerger phases. Given the signal's high frequency (a few kHz) and the lower sensitivity of current ground-based interferometric GW detectors in this band, the probability of confidently detecting a BNS postmerger gravitational wave signal is low. Therefore, one approach to analyzing the postmerger signal is to combine observations to increase its detectability. In this work, we apply continuous wavelet transform (CWT) to simulated signals, reconstructed using a model-agnostic analysis, and then stack the resulting time-frequency maps to study the postmerger frequency content. We use model selection methods to investigate how the detectability of the BNS postmerger signal changes when combining CWT scalograms from individual events. Additionally, we explore how well the postmerger peak frequency is recovered in the stacked data relative to the individual data.