Collider Physic

Collider physics aims to understand fundamental particles and their interactions by analyzing high-energy particle collisions, primarily at the Large Hadron Collider (LHC). Current research heavily utilizes machine learning, employing diverse models like neural networks (including multilayer perceptrons, convolutional autoencoders, and Kolmogorov-Arnold networks), normalizing flows, and Bayesian methods to improve data analysis tasks such as event classification, jet reconstruction, and background estimation. These advancements significantly enhance the efficiency and precision of data analysis, accelerating discoveries and refining our understanding of fundamental physics.