Detecting gravitational radiation from neutron stars using a six-parameter adaptive MCMC method

TL;DR

This paper introduces a six-parameter adaptive MCMC method for detecting gravitational waves from neutron stars, capable of estimating key source parameters and scalable to multi-processor systems for narrow-band searches.

Contribution

The paper develops a novel Markov chain Monte Carlo technique with reparametrization and annealing for gravitational wave detection from neutron stars, enabling efficient parameter estimation.

Findings

Method successfully estimates up to six unknown parameters.

Extension to distributed computing allows narrow frequency band searches.

Applicable to sources with uncertain spin parameters at known locations.

Abstract

We present a Markov chain Monte Carlo technique for detecting gravitational radiation from a neutron star in laser interferometer data. The algorithm can estimate up to six unknown parameters of the target, including the rotation frequency and frequency derivative, using reparametrization, delayed rejection and simulated annealing. We highlight how a simple extension of the method, distributed over multiple computer processors, will allow for a search over a narrow frequency band. The ultimate goal of this research is to search for sources at a known locations, but uncertain spin parameters, such as may be found in SN1987A.