Machine learning and the physical sciences

G Carleo, I Cirac, K Cranmer, L Daudet, M Schuld… - Reviews of Modern …, 2019 - APS
Machine learning (ML) encompasses a broad range of algorithms and modeling tools used
for a vast array of data processing tasks, which has entered most scientific disciplines in …

Heavy-flavour and quarkonium production in the LHC era: from proton–proton to heavy-ion collisions

A Andronic, F Arleo, R Arnaldi, A Beraudo… - The European Physical …, 2016 - Springer
This report reviews the study of open heavy-flavour and quarkonium production in high-
energy hadronic collisions, as tools to investigate fundamental aspects of Quantum …

Parton distributions for the LHC Run II

RD Ball, V Bertone, S Carrazza, CS Deans… - Journal of High Energy …, 2015 - Springer
A bstract We present NNPDF3. 0, the first set of parton distribution functions (PDFs)
determined with a methodology validated by a closure test. NNPDF3. 0 uses a global …

The path to proton structure at 1% accuracy: NNPDF Collaboration

RD Ball, S Carrazza, J Cruz-Martinez… - The European Physical …, 2022 - Springer
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 …

Parton distributions with LHC data

RD Ball, V Bertone, S Carrazza, CS Deans… - Nuclear Physics B, 2013 - Elsevier
We present the first determination of parton distributions of the nucleon at NLO and NNLO
based on a global data set which includes LHC data: NNPDF2. 3. Our data set includes …

[PDF][PDF] The path to proton structure at 1% accuracy

N Collaboration, RD Ball, S Carrazza, J Cruz-Martinez… - Eur. Phys. J. C, 2022 - Springer
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 …

Exploring QCD matter in extreme conditions with Machine Learning

K Zhou, L Wang, LG Pang, S Shi - Progress in Particle and Nuclear Physics, 2024 - Elsevier
In recent years, machine learning has emerged as a powerful computational tool and novel
problem-solving perspective for physics, offering new avenues for studying strongly …

[HTML][HTML] 50 Years of quantum chromodynamics: Introduction and Review

F Gross, E Klempt, SJ Brodsky, AJ Buras… - The European Physical …, 2023 - Springer
Quantum Chromodynamics, the theory of quarks and gluons, whose interactions can be
described by a local SU (3) gauge symmetry with charges called “color quantum numbers” …

Impact of heavy quark masses on parton distributions and LHC phenomenology

RD Ball, V Bertone, F Cerutti, L Del Debbio, S Forte… - Nuclear Physics B, 2011 - Elsevier
We present a determination of the parton distributions of the nucleon from a global set of
hard scattering data using the NNPDF methodology including heavy quark mass effects …

Snowmass 2021 whitepaper: Proton structure at the precision frontier

S Amoroso, A Apyan, N Armesto, RD Ball… - arxiv preprint arxiv …, 2022 - arxiv.org
An overwhelming number of theoretical predictions for hadron colliders require parton
distribution functions (PDFs), which are an important ingredient of theory infrastructure for …