Speaker
Description
I'll present methods to optimize the analysis of long-duration gravitational waves (GWs) from compact binary coalescences (CBCs) and search for sub-solar mass CBCs in LIGO data using the methods. The LIGO–Virgo–KAGRA (LVK) collaboration, operating the world’s most sensitive GW observatories, searches for CBC signals in the 0.2–1.0 solar mass range, providing leading constraints on the abundance of Primordial Black Holes (PBHs).
However, low-mass CBC signals have intrinsically long durations, which pose significant computational challenges. The sensitivity of current searches is limited by the cost of dense template banks and the memory requirements of the analysis. In addition, for very long signals, the assumption of stationary noise becomes less accurate over the signal duration, making it difficult to track noise fluctuations and leading to a loss of sensitivity. To mitigate these issues, existing analyses often adopt a higher low-frequency cutoff (e.g., 45 Hz), which reduces computational demands but sacrifices sensitivity. Our study indicates that incorporating lower-frequency data could improve PBH abundance limits by up to ~36%. This issue will become even more critical for next-generation detectors, which are expected to achieve enhanced sensitivity at low frequencies and thus observe even longer signals.
To address these challenges, I develop two complementary methods: the ratio filter and the multiband matched filtering method. The ratio filter enables efficient computation of the signal-to-noise ratio (SNR) for nearby waveforms by reusing the SNR time series of a reference waveform. Multiband matched filtering mitigates the loss of sensitivity due to non-stationary noise by dividing the waveform into multiple frequency bands, allowing the analysis to better track time-dependent noise fluctuations, while also reducing computational cost.
Using these methods, I conduct a search for sub-solar mass CBCs in LIGO data and present the result.
