Accelerated parameter estimation of supermassive black hole binaries in LISA using a meshfree approximation

TL;DR

This paper adapts a meshfree interpolation technique to accelerate Bayesian parameter estimation of supermassive black hole binaries in LISA data, enabling faster and accurate inference of source parameters.

Contribution

It extends a meshfree approximation method from terrestrial detectors to LISA, improving the speed of SMBHB parameter estimation in gravitational wave data.

Findings

Faithful inference of SMBHB parameters from simulated LISA signals.

Demonstrated computational efficiency of the meshfree method.

Applicable to full inspiral, merger, and ringdown waveforms.

Abstract

The Laser Interferometer Space Antenna (LISA) will be capable of detecting gravitational waves (GWs) in the milli-Hertz band. Among various sources, LISA will detect the coalescence of supermassive black hole binaries (SMBHBs). Accurate and rapid inference of parameters for such sources will be important for potential electromagnetic follow-up efforts. Rapid Bayesian inference with LISA includes additional complexities as compared to current generation terrestrial detectors in terms of time and frequency dependent antenna response functions. In this work, we extend a recently developed, computationally efficient technique that uses meshfree interpolation methods to accelerate Bayesian reconstruction of compact binaries. Originally developed for second-generation terrestrial detectors, this technique is now adapted for LISA parameter estimation. Using the full inspiral, merger, and ringdown waveform (PhenomD) and assuming rigid adiabatic antenna response function, we show faithful inference of SMBHB parameters from GW signals embedded in stationary, Gaussian instrumental noise. We discuss the computational cost and performance of the meshfree approximation method in estimating the GW source parameters.