A rapid multi-modal parameter estimation technique for LISA

TL;DR

This paper extends a rapid parameter estimation method to LISA gravitational-wave sources, significantly reducing computation time and aiding in bias mitigation for massive black hole binary analysis.

Contribution

It adapts the simple-pe technique for LISA data, enabling at least 100 times faster parameter estimation including higher order effects.

Findings

Achieves ~12 hours analysis time on a single CPU.

Infers source properties of MBHBs in zero-noise at least 100 times faster.

Helps mitigate biases in multi-modal Bayesian analyses.

Abstract

The Laser Interferometer Space Antenna (LISA) will observe gravitational-wave signals from a wide range of sources, including massive black hole binaries. Although numerous techniques have been developed to perform Bayesian inference for LISA, they are often computationally expensive; analyses often take at least $\sim 1$ month on a single CPU, even when using accelerated techniques. Not only does this make it difficult to concurrently analyse more than one gravitational-wave signal, it also makes it challenging to rapidly produce parameter estimates for possible electromagnetic follow-up campaigns. simple-pe was recently developed to produce rapid parameter estimates for gravitational-wave signals observed with ground-based gravitational-wave detectors. In this work, we extend simple-pe to produce rapid parameter estimates for LISA sources, including the effects of higher order multipole moments. We show that simple-pe infers the source properties of massive black hole binaries in zero-noise at least $\sim 100\times$ faster than existing techniques; $\sim 12$ hours on a single CPU. We further demonstrate that simple-pe can be applied before existing Bayesian techniques to mitigate biases in multi-modal parameter estimation analyses of MBHBs.