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SUMMARY:Rediscovering the Standard Model of Particle Physics with AI - Pel
 legrino Piantadosi (NYU Abu Dhabi)
DTSTART:20251120T113000Z
DTEND:20251120T123000Z
UID:TALK240652@talks.cam.ac.uk
DESCRIPTION:In this talk\, I explore whether artificial intelligence can a
 utonomously recover known structures of the Standard Model of particle phy
 sics using only experimental data and no theoretical input. By applying un
 supervised machine learning techniques&mdash\;such as dimensionality reduc
 tion and clustering&mdash\;to intrinsic particle properties and decay mode
 s\, we find that key features of particle physics emerge directly from the
  data. These include the relative strength of interactions\, the distincti
 on between baryons and mesons\, and conserved quantities such as baryon nu
 mber\, strangeness\, and charm. The analysis also reveals the isospin stru
 cture\, the Eightfold Way multiplets\, and signatures of Regge trajectorie
 s in baryon excitations. I will also discuss how these approaches can be e
 xtended to capture deeper symmetry patterns and internal structures.
LOCATION:Seminar Room 1\, Newton Institute
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