A one-stop function for gravitational-wave detection, identification and inference

Abstract

I define here a novel function on a modeled space of gravitational-wave signals, before studying its properties as a statistic for detection, as an objective function for identification, and as an effective likelihood function for inference. The main motivation behind this work is the open data-analysis problem for signals from extreme-mass-ratio inspirals, which is severely hindered by the presence of strong non-local parameter degeneracy in the signal space. I demonstrate the utility of the proposed function for the analysis of such signals, and suggest various possible directions for future research.

Published version

References in corpus (9)

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Cited by in corpus (7)

• Identification of Gravitational-waves from Extreme Mass Ratio Inspirals
• LISA stellar-mass black hole searches with semicoherent and particle-swarm methods
• Testing gravity with Extreme-Mass-Ratio Inspirals
• Scalable data-analysis framework for long-duration gravitational waves from compact binaries using short Fourier transforms
• Toward a computationally-efficient follow-up pipeline for blind continuous gravitational-wave searches
• Constraining the Deviation of Kerr Metric via Bumpy Parameterization and Particle Swarm Optimization in Extreme Mass-Ratio Inspirals
• Secular evolution of orbital parameters for general bound orbits in Kerr spacetime