Search for the PN coefficients for the Energy flux through Gravitational Waves from Black-Hole Binaries using Markov Chain Monte Carlo

TL;DR

This paper uses Markov Chain Monte Carlo methods to improve the estimation of post-Newtonian coefficients for gravitational wave flux from black-hole binaries, enhancing templates for LISA detection.

Contribution

It introduces a novel approach combining MCMC with post-Newtonian expansion to accurately determine gravitational flux coefficients from black-hole binaries.

Findings

MCMC can accurately recover the last PN coefficient from noisy signals.

Fast convergence of MCMC in estimating PN coefficients.

Exploration of higher-dimensional parameter spaces.

Abstract

In this work, the focus is on the improvement of the existing post-Newtonian approximation for the gravitational flux from Super Massive Black Hole Binaries. In order to improve the existing templates for LISA, we need more accurate post-Newtonian expansions for the gravitational flux. Stochastic search techniques like the Markov Chain Monte Carlo (MCMC) have been used extensively for searching for sky parameters etc. The idea is to combine the two and approach the problem of finding post-Newtonian coefficients using MCMC. It has been shown that matching against a 5.5PN signal, with noise, the last coefficient can be found by MCMC very easily and displays fast convergence. Also the space for higher dimensional searches are explored.