Cosmic Swarms: A search for Supermassive Black Holes in the LISA data stream with a Hybrid Evolutionary Algorithm

TL;DR

This paper introduces a hybrid evolutionary algorithm capable of detecting multiple supermassive black hole binaries in LISA gravitational wave data, effectively handling complex sky solution modes and providing accurate parameter estimations.

Contribution

The paper presents a novel hybrid evolutionary algorithm that simultaneously searches for multiple SMBHB inspirals and explores bi-modal sky solutions in LISA data analysis.

Findings

Successfully detects multiple SMBHBs in simulated LISA data.

Accurately estimates parameters within 5 sigma of true values.

Effectively explores bi-modal sky solutions.

Abstract

We describe a hybrid evolutionary algorithm that can simultaneously search for multiple supermassive black hole binary (SMBHB) inspirals in LISA data. The algorithm mixes evolutionary computation, Metropolis-Hastings methods and Nested Sampling. The inspiral of SMBHBs presents an interesting problem for gravitational wave data analysis since, due to the LISA response function, the sources have a bi-modal sky solution. We show here that it is possible not only to detect multiple SMBHBs in the data stream, but also to investigate simultaneously all the various modes of the global solution. In all cases, the algorithm returns parameter determinations within $5\sigma$ (as estimated from the Fisher Matrix) of the true answer, for both the actual and antipodal sky solutions.