Time-frequency clustering for burst gravitational waves search in TAMA300 data

TL;DR

This paper introduces a time-frequency clustering method to detect burst gravitational waves in TAMA data, effectively distinguishing signals from noise and improving detection efficiency and noise reduction.

Contribution

The paper presents a novel time-frequency clustering technique for gravitational wave detection that enhances signal identification and noise suppression in TAMA data analysis.

Findings

Achieved roughly 50% detection efficiency for injected waveforms.

Reduced spike noise impact by over an order of magnitude for high SNR signals.

Effectively distinguished short-duration signals from detector noise.

Abstract

We have developed a method 'time-frequency (TF) clustering' to find the burst gravitational waves for TAMA data analysis. TF clustering method on sonogram (spectrogram) shows some characteristics of short duration signal. Using parameters which represent the cluster shape, we can efficiently identify some predicted gravitational wave forms and can exclude typical unstable spike like noises due to detector instruments. The requirement of some parameters of cluster achieved roughly 50% average efficiency for injected DFM waveforms of $h_{rss}\sim 2 \times 10^{-19}$ for type I burst. Also the reduction for signal by spike noises are more than one order improvement for the SNR$>$100.