Jet Reconstruction

Jet reconstruction in particle physics aims to identify and characterize jets—collimated sprays of particles produced in high-energy collisions—to understand fundamental particle interactions. Current research emphasizes improving reconstruction accuracy and efficiency using advanced machine learning techniques, such as graph neural networks and variational inference methods, often focusing on optimizing for specific physical quantities and handling the increasing complexity of data from high-luminosity colliders. These advancements are crucial for enhancing the precision of measurements in collider experiments, enabling more sensitive searches for new physics and improving our understanding of the Standard Model.