Using weighting algorithms to refine source direction determinations in all-sky gravitational wave burst searches with two-detector networks

TL;DR

This paper revisits a classical, non-Bayesian method for determining gravitational wave source directions using two detectors, enhancing it with a weighting algorithm validated through simulations, and discusses its potential in multi-detector networks.

Contribution

It introduces a weighting algorithm to improve a traditional source localization method, providing an alternative to Bayesian approaches in gravitational wave detection.

Findings

The weighting algorithm improves localization accuracy.

The method remains effective with noisy and unexpected signals.

Simulations validate the enhanced approach.

Abstract

I explore the possibility of resurrecting an old, non-Bayesian computational approach for inferring the source direction of a gravitational wave from the output of a two-detector network. The method gives the beam pattern response functions and time delay, and performs well even in the presence of noise and unexpected signal forms. I further suggest an improvement to this method in the form of a weighting algorithm that usefully improves its accuracy beyond what can be achieved with simple best-fit methods, validating the new procedure with several small-scale simulations. The approach is identified as complimentary to -- rather than in competition with -- the now-standard Bayesian approach typically used by the LIGO network in parameter determination. Finally, I briefly discuss the possible applications of this method in the world of three-or-more detector networks and some directions for future work.