As deep learning methods and particularly Large Language Models have shown huge promise in a variety of applications, we apply a model inspired by BERT (Bidirectional Encoder Representations from Transformers), developed by Google and utilizing the multi-headed attention mechanism, to a high energy physics problem. We focus on the process of top quark-antiquark decay reconstruction and...
Fast and accurate parameter estimation of gravitational wave (GW) signals is crucial in multi-messenger astrophysics. These signals are the first to arrive, requiring prompt analysis of the merger properties. However, extracting these parameters from observed binary mergers from GW detectors remains a computational bottleneck. Current approaches, such as Markov-Chain Monte Carlo (MCMC) methods...
