Gaussian processes reconstruction of modified gravitational wave propagation

TL;DR

This paper employs Gaussian processes to reconstruct modified gravitational wave propagation from simulated data, demonstrating potential to detect deviations from general relativity with current and future GW detectors.

Contribution

It introduces a Gaussian processes-based method for model-independent reconstruction of modified GW propagation using simulated joint GW-GRB and electromagnetic data.

Findings

HVLKI network can detect deviations from GR with ~15 neutron star binaries.

Third-generation detectors like ET have high potential for discovering modified gravity effects.

Gaussian processes complement existing parametrizations of GW propagation modifications.

Abstract

Recent work has shown that modified gravitational wave (GW) propagation can be a powerful probe of dark energy and modified gravity, specific to GW observations. We use the technique of Gaussian processes, that allows the reconstruction of a function from the data without assuming any parametrization, to measurements of the GW luminosity distance from simulated joint GW-GRB detections, combined with measurements of the electromagnetic luminosity distance by simulated DES data. For the GW events we consider both a second-generation LIGO/Virgo/Kagra (HVLKI) network, and a third-generation detector such as the Einstein Telescope. We find that the HVLKI network at target sensitivity, with $O(15)$ neutron star binaries with electromagnetic counterpart, could already detect deviations from GR at a level predicted by some modified gravity models, and a third-generation detector such as ET would have a remarkable discovery potential. We discuss the complementarity of the Gaussian processes technique to the $(\Xi_0,n)$ parametrization of modified GW propagation.