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Title: Hierarchical Searches for Subsolar-mass Binaries and the Third-generation Gravitational Wave Detector Era
Abstract Detecting gravitational waves (GWs) from coalescing compact binaries has become routine with ground-based detectors like Advanced LIGO and Advanced Virgo. However, beyond standard sources such as binary black holes and neutron stars and neutron star black holes, no exotic sources revealing new physics have been discovered. Detecting ultracompact objects, such as subsolar mass (SSM), offers a promising opportunity to explore diverse astrophysical populations. However, searching for these objects using standard matched-filtering techniques is computationally intensive due to the dense parameter space involved. This increasing computational demand not only challenges current search methodologies but also poses a significant obstacle for third-generation (3G) ground-based GW detectors. In the 3G detectors, signals are expected to be observed for tens of minutes and detection rates to reach one per minute. This requires efficient search strategies to manage the computational load of long-duration signal search. In this paper, we demonstrate how hierarchical search strategies can address the computational challenges associated with detecting long-duration signals in current detectors and the 3G era. Using SSM searches as an example, we show that optimizing data sampling rates and adjusting the number of templates in matched filtering at each stage of low-frequency searches can improve the signal-to-noise ratio by 6% and detection volume by 10%–20%. This sensitivity improvement is achieved with a 2.5-fold reduction in computational time compared to standard PyCBC searches. We also discuss how this approach could be adapted and refined for searches involving eccentric and precessing binaries with future detectors.  more » « less
Award ID(s):
2309240
PAR ID:
10580403
Author(s) / Creator(s):
;
Publisher / Repository:
The Astrophysical Journal
Date Published:
Journal Name:
The Astrophysical Journal
Volume:
978
Issue:
1
ISSN:
0004-637X
Page Range / eLocation ID:
69
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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