3 papers
cs.LG2025
Leveraging Reinforcement Learning, Genetic Algorithms and Transformers for background determination in particle physics
Guillermo Hijano Mendizabal, Davide Lancierini, Alex Marshall +8
Experimental studies of beauty hadron decays face significant challenges due to a wide range of backgrounds arising from the numerous possible decay channels with similar final sta…
hep-ex2025
Towards replacing detector simulation with heterogeneous GNNs in flavour physics analyses
Guillermo Hijano, Davide Lancierini, Alexander Mclean Marshall +8
Driven by the increasing volume of recorded data, the demand for simulation from experiments based at the Large Hadron Collider will rise sharply in the coming years. Addressing th…
physics.data-an2025
Scalable Multi-Task Learning for Particle Collision Event Reconstruction with Heterogeneous Graph Neural Networks
William Sutcliffe, Marta Calvi, Simone Capelli +5
The growing luminosity frontier at the Large Hadron Collider is challenging the reconstruction and analysis of particle collision events. Increased particle multiplicities are stra…