Gravitational Wave Data

Gravitational wave data analysis focuses on detecting and characterizing signals from cataclysmic astrophysical events like binary black hole and neutron star mergers within noisy detector data. Current research heavily utilizes deep learning, employing convolutional neural networks (CNNs), graph neural networks (GNNs), and generative adversarial networks (GANs) to improve signal detection efficiency, accuracy, and robustness against noise and glitches. These advanced techniques are enhancing the sensitivity of gravitational wave searches, leading to more precise measurements of astrophysical parameters and a deeper understanding of the universe's most energetic phenomena.