Wavelet-based tools to analyze, filter, and reconstruct transient gravitational-wave signals
Andrea Virtuoso, Edoardo Milotti

TL;DR
This paper introduces wavelet-based tools, including the wavelet Q-transform and its extension, for analyzing, filtering, and reconstructing transient gravitational-wave signals with improved efficiency and invertibility.
Contribution
The paper develops invertible wavelet transforms tailored for gravitational-wave analysis, enabling efficient filtering and accurate signal reconstruction, especially for chirping signals from binary coalescences.
Findings
Effective noise filtering and clean signal reconstructions achieved.
Transform methods are invertible and computationally efficient.
Potential for precise tests of General Relativity using GW signals.
Abstract
The analysis of gravitational-wave (GW) signals is one of the most challenging application areas of signal processing. Wavelet transforms are specially helpful in detecting and analyzing GW transients and several analysis pipelines are based on these transforms, both continuous and discrete. While discrete wavelet transforms have distinct advantages in terms of computing efficiency, continuous wavelet transforms (CWT) produce smooth and visually stunning time-frequency maps. In addition to wavelets the Q-transform is also used, which is a Morlet wavelet-like transform where the width of the Gaussian envelope is parameterized by a parameter denoted by Q. To date, the use of CWTs in GW data analysis has been limited by the higher computational load when compared with discrete wavelets, and also by the lack of an inversion formula for wavelet families that do not satisfy the admissibility…
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.
