2024/01/17 by Gao, Pin, Fan, Xilong, Cao, Zhoujian
#FOS: Physical sciences #General Relativity and Quantum Cosmology (gr-qc) #High Energy Astrophysical Phenomena (astro-ph.HE) #Instrumentation and Methods for Astrophysics (astro-ph.IM)
paper · doi:10.48550/arxiv.2401.09300
The search for Galactic binary gravitational waves is a critical challenge for future space-based gravitational wave detectors, such as LISA. We propose an innovative approach to simultaneously explore gravitational waves originating from Galactic binaries by developing a new Local Maxima Particle Swarm Optimization (LMPSO) algorithm. Our method identifies local maxima in the F-statistic and applies astrophysical models and the properties of the F-statistic within parameter space to uncover Galactic binary gravitational wave signals in the dataset. This new approach effectively addresses the inaccuracies often associated with signal subtraction contamination, a challenge for traditional iterative subtraction methods, particularly when dealing with low signal-to-noise ratio (SNR) signals (e.g., SNR < 15). We also account for the effects of overlapping signals and degeneracy noise. To demonstrate the effectiveness of our approach, we use residuals from the LISA mock data challenge (LDC1-4), where 10,982 injected sources with SNR ≥ 15 have been removed. For the remaining low-SNR sources (SNR < 15), our method efficiently identifies 6,508 signals, achieving a 63.2% detection rate.