Unsupervised Learning Architecture for Classifying the Transient Noise of Interferometric Gravitational-wave Detectors

Understand

In the data obtained by laser interferometric gravitational wave detectors, transient noise with non-stationary and non-Gaussian features occurs at a high rate.

• This often results in problems such as detector instability and the hiding and/or imitation of gravitational-wave signals.
• This transient noise has various characteristics in the time--frequency representation, which is considered to be associated with environmental and instrumental origins.
• Classification of transient noise can offer clues for exploring its origin and improving the performance of the detector.