Researchers describe AgentRivet, a system that automatically generates Rivet analysis routines from published journal articles. Rivet is a C++ toolkit used in collider physics to compare new theoretical models against preserved experimental measurements. The work aims to reduce the manual effort of encoding published analyses into reusable software.
A new arXiv preprint examines ways to improve the ACTS software suite's handling of configuration parameters used in track seeding for charged-particle reconstruction. Because those settings strongly influence both reconstruction quality and computing cost, they are typically adjusted by hand through expert judgement and repeated testing. The work proposes new directions for reducing that manual tuning burden.
A new preprint applies self-supervised learning to build representations of beauty and charm hadron decays in LHCb data. These decays serve as sensitive probes of physics beyond the standard model, including channels with invisible particles that leave no detector signature. The technique is designed to extract structure from the collider's large heavy-flavour datasets.