Singular value decomposition applied to compact binary coalescence gravitational-wave signals

TL;DR

This paper demonstrates that applying truncated singular value decomposition to gravitational-wave data analysis of compact binary coalescence signals significantly reduces computational requirements while maintaining high accuracy, and provides an analytic expression for signal loss.

Contribution

The study introduces a novel application of truncated singular value decomposition to gravitational-wave data analysis, reducing filter count and quantifying signal loss analytically.

Findings

Filter count reduced by an order of magnitude

High reconstruction accuracy maintained

Analytic expression for signal loss derived

Abstract

We investigate the application of the singular value decomposition to compact-binary, gravitational-wave data-analysis. We find that the truncated singular value decomposition reduces the number of filters required to analyze a given region of parameter space of compact binary coalescence waveforms by an order of magnitude with high reconstruction accuracy. We also compute an analytic expression for the expected signal-loss due to the singular value decomposition truncation.