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SUMMARY:From Quarks to Neural Networks: Mapping the Proton with Machine Le
 arning
DTSTART:20251119T140000Z
DTEND:20251119T150000Z
DTSTAMP:20260720T072200Z
UID:indico-event-141@indico.dsf.unica.it
DESCRIPTION:Speakers: Emanuele Roberto Nocera (University of Turin)\n\nThe
  proton\, one of the fundamental building blocks of visible matter\, conce
 als a complex structure in which quarks and gluons interact through the st
 rong force described by Quantum Chromodynamics (QCD). Revealing this struc
 ture is essential for understanding high-energy particle scattering\, as c
 an be studied at colliders\, for testing the boundaries of the Standard Mo
 del\, and for discovering New Physics signatures. In this colloquium\, I w
 ill show how we can reconstruct the proton’s internal landscape through 
 global analyses of parton distribution functions (PDFs)\, which connect co
 llider data to the underlying dynamics of QCD. I will specifically focus o
 n how modern machine learning techniques - neural networks\, stochastic op
 timization\, and robust statistical validation - allow us to extract this 
 information with unprecedented precision and accuracy.The resulting pictur
 e exemplifies how physics and artificial intelligence can work together to
  deepen our understanding of nature at its most fundamental scale.\n\nhttp
 s://indico.dsf.unica.it/event/141/
LOCATION:Dipartimento/1-1 - Sala Consiglio (Dipartimento)
URL:https://indico.dsf.unica.it/event/141/
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