Maximum Likelihood Detection of Instrumental Glitches in LISA TDI Data

TL;DR

This paper presents a maximum likelihood-based method for detecting and removing glitches in LISA TDI data, aiming to improve gravitational wave detection by mitigating test mass acceleration disturbances.

Contribution

It introduces an optimization technique using maximum likelihood estimation specifically designed for glitch detection and removal in LISA data.

Findings

Effective detection of glitches demonstrated

Improved data quality for gravitational wave analysis

Potential reduction of false positives in LISA data

Abstract

The orbiting LISA instrument is designed to detect gravitational waves in the millihertz band, produced by sources including galactic binaries and extreme mass ratio inspirals, among others. The detector consists of three spacecraft, each carrying a pair of free-falling test masses. A technology-demonstration mission, LISA Pathfinder, was launched in 2015, and observed several sudden changes in test mass acceleration, referred to as "glitches." Similar glitches in the full LISA mission have the potential to contaminate the Time-Delay Interferometry outputs that are the detector's primary data product. In this paper, we describe an optimization technique using maximum likelihood estimation for detecting and removing glitches with a known waveform.