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Data analysis in modern science using extensive experimental andobservational facilities, such as a gravitational wave detector, is essentialin the search for novel scientific discoveries. Accordingly, various techniquesand mathematical principles have been designed and developed to date. Arecently proposed approximate correlation method based on the informationtheory is widely adopted in science and engineering. Although the maximalinformation coefficient (MIC) method remains in the phase of improving itsalgorithm, it is particularly beneficial in identifying the correlations ofmultiple noise sources in gravitational-wave detectors including non-lineareffects. This study investigates various prospects for determining MICparameters to improve the reliability of handling multi-channel time-seriesdata, reduce high computing costs, and propose a novel method of determiningoptimized parameter sets for identifying noise correlations in gravitationalwave data.

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