CERN Accelerating science

Preprint
Report number	CERN-TH-2024-127 ; arXiv:2408.00832
Title	Leveraging Time-Dependent Instrumental Noise for LISA SGWB Analysis
Author(s)	Alvey, James (U. Amsterdam, GRAPPA) ; Bhardwaj, Uddipta (U. Amsterdam, GRAPPA ; U. Amsterdam, IHEF) ; Domcke, Valerie (CERN) ; Pieroni, Mauro (CERN) ; Weniger, Christoph (U. Amsterdam, GRAPPA)
Imprint	2024-08-01
Number of pages	15
Note	12 pages, 5 figures. saqqara available at https://github.com/peregrine-gw/saqqara, GW_response available at https://github.com/Mauropieroni/GW_response
Subject category	hep-ph ; Particle Physics - Phenomenology ; astro-ph.IM ; Astrophysics and Astronomy ; astro-ph.CO ; Astrophysics and Astronomy ; gr-qc ; General Relativity and Cosmology
Abstract	Variations in the instrumental noise of the Laser Interferometer Space Antenna (LISA) over time are expected as a result of e.g. scheduled satellite operations or unscheduled glitches. We demonstrate that these fluctuations can be leveraged to improve the sensitivity to stochastic gravitational wave backgrounds (SGWBs) compared to the stationary noise scenario. This requires optimal use of data segments with downward noise fluctuations, and thus a data analysis pipeline capable of analysing and combining shorter time segments of mission data. We propose that simulation based inference is well suited for this challenge. In an approximate, but state-of-the-art, modeling setup, we show by comparison with Fisher Information Matrix estimates that the optimal information gain can be achieved in practice.
Other source	Inspire
Copyright/License	preprint: (License: CC BY 4.0)