English

Comparison of Gravitational Wave Detector Network Sky Localization Approximations

General Relativity and Quantum Cosmology 2015-06-17 v1 Instrumentation and Methods for Astrophysics

Abstract

Gravitational waves emitted during compact binary coalescences are a promising source for gravitational-wave detector networks. The accuracy with which the location of the source on the sky can be inferred from gravitational wave data is a limiting factor for several potential scientific goals of gravitational-wave astronomy, including multi-messenger observations. Various methods have been used to estimate the ability of a proposed network to localize sources. Here we compare two techniques for predicting the uncertainty of sky localization -- timing triangulation and the Fisher information matrix approximations -- with Bayesian inference on the full, coherent data set. We find that timing triangulation alone tends to over-estimate the uncertainty in sky localization by a median factor of 44 for a set of signals from non-spinning compact object binaries ranging up to a total mass of 20M20 M_\odot, and the over-estimation increases with the mass of the system. We find that average predictions can be brought to better agreement by the inclusion of phase consistency information in timing-triangulation techniques. However, even after corrections, these techniques can yield significantly different results to the full analysis on specific mock signals. Thus, while the approximate techniques may be useful in providing rapid, large scale estimates of network localization capability, the fully coherent Bayesian analysis gives more robust results for individual signals, particularly in the presence of detector noise.

Keywords

Cite

@article{arxiv.1310.7454,
  title  = {Comparison of Gravitational Wave Detector Network Sky Localization Approximations},
  author = {K. Grover and S. Fairhurst and B. F. Farr and I. Mandel and C. Rodriguez and T. Sidery and A. Vecchio},
  journal= {arXiv preprint arXiv:1310.7454},
  year   = {2015}
}

Comments

11 pages, 7 Figures

R2 v1 2026-06-22T01:55:29.654Z