Gravitational Wave

Gravitational wave research focuses on detecting and analyzing these ripples in spacetime, primarily from merging compact objects like black holes and neutron stars. Current research heavily utilizes machine learning, employing diverse architectures such as convolutional neural networks (CNNs), recurrent neural networks (RNNs, including LSTMs), transformers, and generative adversarial networks (GANs) for tasks ranging from signal detection and classification to parameter estimation and waveform modeling. These advancements significantly improve the speed and accuracy of data analysis, enabling faster alerts for multi-messenger astronomy and more detailed studies of gravitational wave sources and their properties.