Classifying Non-Gaussian Transient Noise in LIGO

Using computer vision to analyse gravitational waves can provide valuable information about previously obscured information.

Space exploration methods have never been as diverse and thorough as it is in today’s time. New techniques that span far beyond the conventional method of using electromagnetic radiation to identify and study astronomical evidence have been discovered and are now amplified using machine learning technology. One such technique is using interferometers to record gravitational waves released from astronomical events. Using computer vision to analyse gravitational waves can provide valuable information about previously obscured information. Also, gravitational waves are fundamentally unrelated to electromagnetic radiation thereby providing us with information that is entirely different from what we previously could access. This has consequentially opened an altogether new avenue for research and further exploration. The contrastive model for machine learning-based detection and classification performed the best.

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