Bayesian model comparison applied to the Explorer-Nautilus 2001 coincidence data

TL;DR

This paper applies Bayesian reasoning to analyze the 2001 Explorer-Nautilus coincidence data, enabling optimal model comparison and evidence extraction for gravitational wave signals from Galactic sources.

Contribution

It introduces a Bayesian framework for analyzing gravitational wave coincidence data, allowing for efficient combination of multiple experiments and model comparison using Bayes factors.

Findings

Bayesian analysis quantifies evidence for gravitational wave signals.

Likelihood rescaling summarizes experimental results effectively.

Bayes factors compare models based on observational data.

Abstract

Bayesian reasoning is applied to the data by the ROG Collaboration, in which gravitational wave (g.w.) signals are searched for in a coincidence experiment between Explorer and Nautilus. The use of Bayesian reasoning allows, under well defined hypotheses, even tiny pieces of evidence in favor of each model to be extracted from the data. The combination of the data of several experiments can therefore be performed in an optimal and efficient way. Some models for Galactic sources are considered and, within each model, the experimental result is summarized with the likelihood rescaled to the insensitivity limit value (``${\cal R}$ function''). The model comparison result is given in in terms of Bayes factors, which quantify how the ratio of beliefs about two alternative models are modified by the experimental observation