BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Joosep Pata (National Institute of Chemical Physics and Biophysics \, Estonia) DTSTART:20220203T170000Z DTEND:20220203T180000Z DTSTAMP:20260423T003255Z UID:MPML/65 DESCRIPTION:Title: Ma chine learning for data reconstruction at the LHC\nby Joosep Pata (Nat ional Institute of Chemical Physics and Biophysics\, Estonia) as part of M athematics\, Physics and Machine Learning (IST\, Lisbon)\n\n\nAbstract\nPh ysics analyses at the CERN experiments rely on detector hits being interpr eted or reconstructed as particle candidates. The data reconstruction syst ems are built on decades of physics and detector knowledge and must operat e reliably on petabytes of data in diverse computing centers spread around the world. In the recent years\, machine learning (ML) is playing an incr easingly important role at the LHC experiments for reconstructing and inte rpreting the data\, from calibrating the detector readouts to the final in terpretation for complex signal processes. We will discuss the various asp ects of ML at the LHC experiments\, focusing on data reconstruction and pa rticle identification approaches using modern machine learning methods suc h as graph neural networks. We will bring a concrete detailed example from machine learned particle flow (MLPF)\, an R&D effort to develop a fully o ptimizable particle flow reconstruction across detector subsystems in CMS. \n LOCATION:https://researchseminars.org/talk/MPML/65/ END:VEVENT END:VCALENDAR