articleThe European Physical Journal CMay 1, 2022DIAMOND OA

The path to proton structure at 1% accuracy

RDRichard D. BallSCStefano CarrazzaJCJuan Cruz–MartinezLDLuigi Del DebbioSFStefano Forte

University of Edinburgh · Istituto Nazionale di Fisica Nucleare, Sezione di Milano · +4 more institutions

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Abstract

Abstract We present a new set of parton distribution functions (PDFs) based on a fully global dataset and machine learning techniques: NNPDF4.0. We expand the NNPDF3.1 determination with 44 new datasets, mostly from the LHC. We derive a novel methodology through hyperparameter optimization, leading to an efficient fitting algorithm built upon stochastic gradient descent. We use NNLO QCD calculations and account for NLO electroweak corrections and nuclear uncertainties. Theoretical improvements in the PDF description include a systematic implementation of positivity constraints and integrability of sum rules. We validate our methodology by means of closure tests and “future tests” (i.e. tests of backward and…

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391
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Topics & keywords

Topics
Keywords
  • Path (computing)
  • Proton
  • Computer science
  • Physics
  • Nuclear physics
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