Application of the Hilbert-Huang Transform to the Search for Gravitational Waves

TL;DR

This paper explores using the Hilbert-Huang Transform, a novel adaptive time-series analysis method, to improve gravitational wave detection and instrumental analysis in LIGO and LISA data.

Contribution

It introduces the application of the Hilbert-Huang Transform to gravitational wave data analysis, offering high resolution without basis set limitations.

Findings

Enhanced time-frequency resolution for gravitational wave signals

Improved detection capabilities in LIGO and LISA data

Better instrumental characterization using the method

Abstract

We present the application of a novel method of time-series analysis, the Hilbert-Huang Transform, to the search for gravitational waves. This algorithm is adaptive and does not impose a basis set on the data, and thus the time-frequency decomposition it provides is not limited by time-frequency uncertainty spreading. Because of its high time-frequency resolution it has important applications to both signal detection and instrumental characterization. Applications to the data analysis of the ground and space based gravitational wave detectors, LIGO and LISA, are described.