1. Simultaneously search for multi-target Galactic binary gravitational waves in reduced parameter space with LMPSO-CV
- Author
-
Gao, Pin, Fan, Xilong, and Cao, Zhoujian
- Subjects
General Relativity and Quantum Cosmology ,Astrophysics - High Energy Astrophysical Phenomena ,Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
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 $\mathcal{F}$-statistic and applies astrophysical models and the properties of the $\mathcal{F}$-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 $\ge$ 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.
- Published
- 2024