Detection and mitigation of glitches in LISA data: A machine learning approach

Niklas Houba, L. Ferraioli, Domenico Giardini

Physical review. D/Physical review. D. · 2024 · 12 citations · 33 references

Concepts

Abstract

The paper presents a neural network approach for detection, characterization, and discrimination of LISA Time Delay Interferometry transient glitch data from astrophysical signals. It thus paves the way for further addressing this critical issue in LISA data analysis.

References

33