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Swarm-intelligent search for gravitational waves from eccentric binary mergers
被引:2
|作者:
Pal, Souradeep
[1
]
Nayak, K. Rajesh
[1
]
机构:
[1] Indian Inst Sci Educ & Res Kolkata, Mohanpur 741246, W Bengal, India
基金:
美国国家科学基金会;
澳大利亚研究理事会;
日本学术振兴会;
英国科学技术设施理事会;
关键词:
DYNAMICAL FORMATION;
LIGO;
1ST;
SIGNATURES;
VIRGO;
D O I:
10.1103/PhysRevD.110.042003
中图分类号:
P1 [天文学];
学科分类号:
0704 ;
摘要:
We implement an eccentric search for compact binary mergers based on particle swarm optimization. Orbital eccentricity is an invaluable input for understanding the formation scenarios of the binary mergers and can play a pivotal role in finding their electromagnetic counterparts. Current modeled searches rely on precomputed template banks that are computationally expensive and resistant toward expanding the search parameter space dimensionality. On the other hand, particle swarm optimization offers a straightforward algorithm that dynamically selects template points while exploring an arbitrary dimensional parameter space. Through extensive evaluation using simulated signals from spin-aligned eccentric binary mergers, we discovered that the search exhibits a remarkable autonomy in capturing the effects of both eccentricity and spin. We describe our search pipeline and revisit some of the merger candidates from the gravitational wave transient catalogs.
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页数:16
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