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Proton strucure for discovery at the Large Hadron Collider

Total Cost €


EC-Contrib. €






Project "NNNPDF" data sheet

The following table provides information about the project.


Organization address
address: Via Festa Del Perdono 7
city: MILANO
postcode: 20122

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Italy [IT]
 Project website
 Total cost 1˙602˙862 €
 EC max contribution 1˙602˙862 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2016-ADG
 Funding Scheme ERC-ADG
 Starting year 2017
 Duration (year-month-day) from 2017-10-01   to  2022-09-30


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITA DEGLI STUDI DI MILANO IT (MILANO) coordinator 1˙602˙862.00


 Project objective

'The objective of this project is to revolutionize the way the structure of the proton is accessed, determined, and used in the computation of physical processes at hadron colliders such as the Large Hadron Collider (LHC) of CERN. At a hadron accelerator, predictions require a precise, detailed, and accurate description and understanding of the structure of the colliding protons, as encoded in parton distributions (PDFs) - the distributions of quarks and gluons. At the LHC, PDFs are at present the major source of uncertainty, and in the near future they will be the main hurdle for discovery. The vision of this project is to remove this hurdle by attacking the problem using recent results from artificial intelligence (AI). I will lead a research team of two staff scientists, four postdocs and three PhD students, who will apply to PDF determination the recent methods of deep reinforcement learning and Q-learning, which will be coupled with deep residual networks to achieve a fully parameter- and bias-free understanding of proton structure. I will bring into high-energy physics a methodology so far used for object recognition in self-driving cars and automatic game playing, leading both to new physics, and new computational techniques. The application of these techniques to PDFs will enable me to reach two secondary goals. The first is theoretical: the full use for PDF determination of recent high perturbative order (next-to-next-to leading order or NNLO) computations, which will be integrated by means of a new approximation method which relies on combining known exact results with all-order information in various kinematic limits to extend the scope of the former to a more detailed ('more exclusive') description of the final state.The second is phenomenological: the integration in PDF determination of the Monte-Carlo event generators which are used to turn field theoretical prediction into a realistic description which may be directly compared to experimental data. '


List of deliverables.
Data Management Plan Open Research Data Pilot 2019-05-31 11:53:30

Take a look to the deliverables list in detail:  detailed list of NNNPDF deliverables.


year authors and title journal last update
List of publications.
2018 Stefano Carrazza, Nathan P. Hartland
Minimisation strategies for the determination of parton density functions
published pages: 52007, ISSN: 1742-6588, DOI: 10.1088/1742-6596/1085/5/052007
Journal of Physics: Conference Series 1085 2019-06-06
2018 Forte, Stefano; Napoletano, Davide; Ubiali, Maria
Z boson production in bottom-quark fusion: a study of b-mass effects beyond leading order.
published pages: , ISSN: 1434-6052, DOI: 10.17863/CAM.24995
European Physical Journal C: Particles and Fields, Vol 78, Iss 11, Pp 1-11 (2018) 2 2019-06-06
2018 Richard D. Ball, Stefano Carrazza, Luigi Del Debbio, Stefano Forte, Zahari Kassabov, Juan Rojo, Emma Slade, Maria Ubiali
Precision determination of the strong coupling constant within a global PDF analysis
published pages: , ISSN: 1434-6044, DOI: 10.1140/epjc/s10052-018-5897-7
The European Physical Journal C 78/5 2019-06-06
2018 Valerio Bertone, Stefano Carrazza, Nathan Hartland, Juan Rojo
Illuminating the photon content of the proton within a global PDF analysis
published pages: , ISSN: 2542-4653, DOI: 10.21468/SciPostPhys.5.1.008
SciPost Physics 5/1 2019-06-06
2018 Emanuele Bagnaschi, Fabio Maltoni, Alessandro Vicini, Marco Zaro
Lepton-pair production in association with a bb¯$$ boverline{b} $$ pair and the determination of the W boson mass
published pages: , ISSN: 1029-8479, DOI: 10.1007/JHEP07(2018)101
Journal of High Energy Physics 2018/7 2019-06-06
2018 Stefano Carrazza
Machine learning challenges in theoretical HEP
published pages: 22003, ISSN: 1742-6588, DOI: 10.1088/1742-6596/1085/2/022003
Journal of Physics: Conference Series 1085 2019-06-06
2017 Richard D. Ball, Valerio Bertone, Stefano Carrazza, Luigi Del Debbio, Stefano Forte, Patrick Groth-Merrild, Alberto Guffanti, Nathan P. Hartland, Zahari Kassabov, José I. Latorre, Emanuele R. Nocera, Juan Rojo, Luca Rottoli, Emma Slade, Maria Ubiali
Parton distributions from high-precision collider data
published pages: , ISSN: 1434-6044, DOI: 10.1140/epjc/s10052-017-5199-5
The European Physical Journal C 77/10 2019-06-11

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