Coughlin, Scott, et al. “Classifying the Unknown: Discovering Novel Gravitational-Wave Detector Glitches Using Similarity Learning”. Physical Review D, vol. 99, no. 8, 2019, p. 082002, doi:10.1103/PhysRevD.99.082002.
Abstract
<p>The observation of gravitational waves from compact binary coalescences by LIGO and Virgo has begun a new era in astronomy. A critical challenge in making detections is determining whether loud transient features in the data are caused by gravitational waves or by instrumental or environmental sources. The citizen-science project Gravity Spy has been demonstrated as an efficient infrastructure for classifying known types of noise transients (glitches) through a combination of data analysis performed by both citizen volunteers and machine learning.
Year of Publication
2019
Journal
Physical Review D
Volume
99
Issue
8
Number of Pages
082002
ISSN Number
2470-0010
DOI
10.1103/PhysRevD.99.082002