Post-processing subtraction of tilt-to-length noise in LISA in the presence of gravitational wave signals
Marie-Sophie Hartig, Sarah Paczkowski, Martin Hewitson, Gerhard, Heinzel, Gudrun Wanner

TL;DR
This paper demonstrates that post-processing subtraction of tilt-to-length noise in LISA can effectively reduce noise without affecting gravitational wave signals, based on simulations across various GW types.
Contribution
It shows that TTL noise subtraction in LISA can be performed without degrading GW signals, ensuring accurate noise modeling in the presence of gravitational waves.
Findings
TTL noise subtraction does not impair GW signal integrity.
GW responses have little effect on TTL noise fitting.
Simulation results confirm effective noise reduction.
Abstract
The Laser Interferometer Space Antenna (LISA) will be the first space-based gravitational wave (GW) observatory. It will measure gravitational wave signals in the frequency regime from 0.1 mHz to 1 Hz. The success of these measurements will depend on the suppression of the various instrument noises. One important noise source in LISA will be tilt-to-length (TTL) coupling. Here, it is understood as the coupling of angular jitter, predominantly from the spacecraft, into the interferometric length readout. The current plan is to subtract this noise in-flight in post-processing as part of a noise minimization strategy. It is crucial to distinguish TTL coupling well from the GW signals in the same readout to ensure that the noise will be properly modeled. Furthermore, it is important that the subtraction of TTL noise will not degrade the GW signals. In the present manuscript, we show on…
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.
Taxonomy
TopicsGeophysics and Gravity Measurements · Pulsars and Gravitational Waves Research · Computational Physics and Python Applications
