Optimizing Parameters of Information-Theoretic Correlation Measurement for Multi-Channel Time-Series Datasets in Gravitational Wave Detectors

TL;DR

This paper enhances the maximal information coefficient (MIC) method for analyzing multi-channel time-series data in gravitational wave detectors by optimizing parameters to improve reliability and reduce computational costs.

Contribution

It introduces a novel approach for selecting MIC parameters tailored to gravitational wave data, improving correlation detection accuracy and efficiency.

Findings

Optimized MIC parameters improve noise correlation detection.

Reduced computational costs in multi-channel data analysis.

Enhanced reliability in gravitational wave signal analysis.

Abstract

Data analysis in modern science using extensive experimental and observational facilities, such as a gravitational wave detector, is essential in the search for novel scientific discoveries. Accordingly, various techniques and mathematical principles have been designed and developed to date. A recently proposed approximate correlation method based on the information theory is widely adopted in science and engineering. Although the maximal information coefficient (MIC) method remains in the phase of improving its algorithm, it is particularly beneficial in identifying the correlations of multiple noise sources in gravitational-wave detectors including non-linear effects. This study investigates various prospects for determining MIC parameters to improve the reliability of handling multi-channel time-series data, reduce high computing costs, and propose a novel method of determining optimized parameter sets for identifying noise correlations in gravitational wave data.