# Glitch systematics on the observation of massive black-hole binaries with LISA

**Authors:** Alice Spadaro, Riccardo Buscicchio, Daniele Vetrugno, Antoine Klein, Davide Gerosa, Stefano Vitale, Rita Dolesi, William Joseph Weber, Monica Colpi  
**arXiv:** [2306.03923](https://arxiv.org/abs/2306.03923)  
**Date:** 2023-06-06  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2306.03923v2/

## Key points

- LISA faces a significant data-analysis challenge in detecting and characterizing thousands of gravitational-wave signals
- Researchers introduced a novel approach for jointly reconstructing short-lived astrophysical signals and noise artifacts inspired by glitches observed during the LISA Pathfinder mission
- Utilizing full Bayesian inference techniques with LISA time-delay interferometric data and gravitational waveforms describing mergers of massive black holes
- The study focuses on a specific binary system with a detector-frame total mass of $6 \times 10^7 M_\odot$ at redshift 5, producing a signal lasting approximately 30 hours within the LISA sensitivity band
- Two different glitch models were explored – a fixed parametric family and a shapelet decomposition – to address varying levels of flexibility in modeling transient artifacts
- Ignoring glitches can lead to a complete loss of the gravitational-wave signal, while even modest glitches can introduce biases in estimating parameters related to black-hole properties
- Employing a joint inference approach effectively cleanses the reconstruction process, ensuring accurate representation of both astrophysical signals and glitch artifacts
- Researchers demonstrate their ability to correctly identify different transient models by injecting various glitch morphologies in isolation without superimposed gravitational signals

## Summary

The Laser Interferometer Space Antenna (LISA) faces a significant data-analysis challenge in detecting and characterizing thousands of gravitational-wave signals. These signals can potentially be impacted by transient artifacts, known as "glitches", with diverse morphologies in the data. In a groundbreaking study, researchers have introduced a novel approach for jointly reconstructing short-lived astrophysical signals and noise artifacts inspired by glitches observed during the LISA Pathfinder mission. Utilizing full Bayesian inference techniques with LISA time-delay interferometric data and gravitational waveforms describing mergers of massive black holes, the study focuses on a specific binary system with a detector-frame total mass of $6 \times 10^7 M_\odot$ at redshift 5. This binary system produces a signal lasting approximately 30 hours within the LISA sensitivity band. The analysis explores two different glitch models – a fixed parametric family and a shapelet decomposition – to address varying levels of flexibility in modeling these transient artifacts. The most challenging scenario highlighted in this research reveals that ignoring glitches can lead to a complete loss of the gravitational-wave signal. Even more modest glitches can introduce biases in estimating parameters related to black-hole properties. However, employing a joint inference approach effectively cleanses the reconstruction process, ensuring accurate representation of both astrophysical signals and glitch artifacts. Furthermore, by injecting various glitch morphologies in isolation without superimposed gravitational signals, researchers demonstrate their ability to correctly identify different transient models. This comprehensive analysis serves as an essential stepping stone towards developing realistic strategies for handling LISA data within the context of achieving a highly sought-after "global fit". Authored by Alice Spadaro, Riccardo Buscicchio, Daniele Vetrugno, Antoine Klein, Davide Gerosa, Stefano Vitale, Rita Dolesi, William Joseph Weber, and Monica Colpi; this research has been published in Physical Review D (108:123029) with DOI: 10.1103/PhysRevD.108.123029.