Survey of Novel Deep Learning Architectures for Denoising Gravitational-wave Signals

arXiv:2609.13272 · gr-qc, astro-ph.HE, astro-ph.IM, cs.LG, cs.NE · Submitted 2026-09-07 · Read on arXiv

gr-qc, astro-ph.HE, astro-ph.IM, cs.LG, cs.NE

Submitted: 2026-09-07

Updated: 2026-09-07

Comments: Submitted to "Machine Learning: Science and Technology", 52 pages, 35 Figures, 8 Tables

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 1× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Fidelity — 1× in this paper · explained in 2 episodes

Related papers

• Tests of General Relativity with Einstein Telescope
• Unitary quantum matter-bounce in a universe with a positive cosmological constant
• Quasi-pole quintessential inflation in metric-affine gravity
• Dynamical tidal response of neutron stars: From effective field theory to gravitational waveforms
• Limits of the Rastall--Einstein Equivalence: Matter-Action Compatibility, FLRW Dynamics, and Exceptional Sectors
• Boson star-black hole binaries: initial data and head-on collisions