TL;DR
This paper addresses the challenge of accounting for uncertainty in noise power spectral density estimation in gravitational-wave data analysis, deriving the correct likelihood for median average estimates and examining their impact on astrophysical inferences.
Contribution
It derives the proper likelihood function for median average noise PSD estimation and evaluates its effects on gravitational-wave parameter inference.
Findings
Simulated Gaussian noise matches predicted distributions.
Real GW data around GW151012 is consistent with stationary-Gaussian noise.
Different PSD estimation methods influence astrophysical inferences.
Abstract
In order to extract information about the properties of compact binaries, we must estimate the noise power spectral density of gravitational-wave data, which depends on the properties of the gravitational-wave detector. In practice, it is not possible to know this perfectly, only to estimate it from the data. Multiple estimation methods are commonly used and each has a corresponding statistical uncertainty. However, this uncertainty is widely ignored when measuring the physical parameters describing compact binary coalescences, and the appropriate likelihoods which account for the uncertainty are not well known. In order to perform increasingly precise astrophysical inference and model selection, it will be essential to account for this uncertainty. In this work, we derive the correct likelihood for one of the most widely used estimation methods in gravitational-wave transient analysis,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
