Subtraction of correlated noise in global networks of gravitational-wave interferometers
Michael W. Coughlin, Nelson L. Christensen, Rosario De Rosa, Irene, Fiori, Mark Go{\l}kowski, Melissa Guidry, Jan Harms, Jerzy Kubisz, Andrzej, Kulak, Janusz Mlynarczyk, Federico Paoletti, Eric Thrane

TL;DR
This paper demonstrates the first successful use of Wiener filtering to reduce correlated magnetic noise from Schumann resonances in global gravitational-wave detector networks, improving the detection of stochastic backgrounds.
Contribution
It introduces a novel application of Wiener filtering to mitigate intercontinental correlated noise, providing a proof-of-principle for future noise reduction efforts.
Findings
Achieved up to twofold reduction in coherence between magnetometers on different continents.
Validated the effectiveness of Wiener filtering in removing correlated magnetic noise.
Highlighted the need for dedicated magnetometer arrays for further improvements.
Abstract
The recent discovery of merging black holes suggests that a stochastic gravitational-wave background is within reach of the advanced detector network operating at design sensitivity. However, correlated magnetic noise from Schumann resonances threatens to contaminate observation of a stochastic background. In this paper, we report on the first effort to eliminate intercontinental correlated noise from Schumann resonances using Wiener filtering. Using magnetometers as proxies for gravitational-wave detectors, we demonstrate as much as a factor of two reduction in the coherence between magnetometers on different continents. While much work remains to be done, our results constitute a proof-of-principle and motivate follow-up studies with a dedicated array of magnetometers.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
