https://doi.org/10.1140/epjc/s10052-022-10328-7
Regular Article - Theoretical Physics
The path to proton structure at 1% accuracy
NNPDF Collaboration
1
The Higgs Centre for Theoretical Physics, University of Edinburgh, JCMB, KB, Mayfield Rd, EH9 3JZ, Edinburgh, Scotland, UK
2
Tif Lab, Dipartimento di Fisica, Università di Milano and INFN, Sezione di Milano, Via Celoria 16, 20133, Milan, Italy
3
DAMTP, University of Cambridge, Wilberforce Road, CB3 0WA, Cambridge, UK
4
Quantum Research Centre, Technology Innovation Institute, Abu Dhabi, United Arab Emirates
5
Center for Quantum Technologies, National University of Singapore, Singapore, Singapore
6
Qilimanjaro Quantum Tech, Barcelona, Spain
7
Department of Physics and Astronomy, Vrije Universiteit, 1081 HV, Amsterdam, The Netherlands
8
Nikhef Theory Group, Science Park 105, 1098 XG, Amsterdam, The Netherlands
9
Cavendish Laboratory, University of Cambridge, CB3 0HE, Cambridge, UK
Received:
17
September
2021
Accepted:
14
April
2022
Published online:
11
May
2022
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 forward data compatibility), and assess its stability, specifically upon changes of PDF parametrization basis. We study the internal compatibility of our dataset, and investigate the dependence of results both upon the choice of input dataset and of fitting methodology. We perform a first study of the phenomenological implications of NNPDF4.0 on representative LHC processes. The software framework used to produce NNPDF4.0 is made available as an open-source package together with documentation and examples.
© The Author(s) 2022
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Funded by SCOAP3
