Mackenzie, E., Berry, C. P. L., Niklasch, G., Téglás, B., Unsworth, C., Crowston, K., Davis, D., & Katsaggelos, A. (2026). Hunting for New Glitches in LIGO Data Using Community Science. 24th International Conference on General Relativity and Gravitation (GR24) and 16th Edoardo Amaldi Conference on Gravitational Waves (Amaldi16). Journal of Physics: Conference Series, 3177, Article 1. https://doi.org/10.1088/1742-6596/3177/1/012083
Abstract
Data from ground-based gravitational-wave detectors like LIGO contain many types of noise. Glitches are short bursts of non-Gaussian noise that may hinder our ability to identify or analyse gravitational-wave signals. They may have instrumental or environmental origins, and new types of glitches may appear following detector changes. The Gravity Spy project studies glitches and their origins, combining insights from volunteers on the community-science Zooniverse platform with machine learning.
Year of Publication
2026
Journal
24th International Conference on General Relativity and Gravitation (GR24) and 16th Edoardo Amaldi Conference on Gravitational Waves (Amaldi16). Journal of Physics: Conference Series
Volume
3177
Number of Pages
012083
Date Published
02/2026
ISSN Number
1742-6588, 1742-6596
URL
https://doi.org/10.1088/1742-6596/3177/1/012083
DOI
10.1088/1742-6596/3177/1/012083