# Extraction of gravitational wave signals in realistic LISA data

**Authors:** Eleonora Castelli, Quentin Baghi, John G. Baker, Jacob Slutsky, Jérôme Bobin, Nikolaos Karnesis, Antoine Petiteau, Orion Sauter, Peter Wass, William J. Weber  
**arXiv:** [2411.13402](https://arxiv.org/abs/2411.13402)  
**Date:** 2024-11-20  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2411.13402v1/

## Key points

- The LISA mission has reached the Mission Adoption milestone, leading to more detailed models of instruments and noise performance.
- Efforts are being made to replace unrealistic assumptions with physically motivated data simulations and adapted data analysis methods.
- The LISA Data Challenges have generated datasets with time-varying constellation armlengths and measurement artifacts like interruptions and transients.
- Researchers assessed the impact of data artifacts on inferring Galactic Binary and Massive Black Hole properties, highlighting the importance of addressing noise transients and gaps for accurate parameter estimation.
- Mitigation techniques can effectively suppress artifacts but may still impact scientific outcomes.
- Strategies are needed to handle planned interruptions in data collection as well as unpredictable long-duration gaps.

## Summary

The Laser Interferometer Space Antenna (LISA) mission, a joint effort between ESA and NASA, has reached the Mission Adoption milestone, leading to more detailed models of instruments and noise performance. Efforts are being made to replace unrealistic assumptions such as Gaussianity, Stationarity, and continuous data continuity with physically motivated data simulations and adapted data analysis methods. The LISA Data Challenges have generated datasets with time-varying constellation armlengths and measurement artifacts like interruptions and transients. In a recent study titled "Extraction of gravitational wave signals in realistic LISA data," researchers Eleonora Castelli, Quentin Baghi, John G. Baker, Jacob Slutsky, Jérôme Bobin, Nikolaos Karnesis, Antoine Petiteau, Orion Sauter, Peter Wass, and William J. Weber assessed the impact of these data artifacts on inferring Galactic Binary and Massive Black Hole properties. Their analysis revealed that addressing noise transients and gaps is crucial for accurate parameter estimation. The study demonstrated that straightforward mitigation techniques can effectively suppress artifacts but may still have a noticeable impact on scientific outcomes. The researchers highlighted the need for strategies to handle planned interruptions in data collection as well as unpredictable long-duration gaps. By adopting a threefold approach in their analysis strategy involving prototyping new algorithms for handling interruptions and incorporating realistic scenarios into their simulations, the team aims to improve the accuracy of gravitational wave signal extraction from LISA's complex dataset.