activity
20152024
most citedParton distributions from high-precision collider data

1.6k citations · 4.2k across the 28 of their papers we have counts for

collaborators

29 papers

hep-ph2024★ 1 cited

SIMUnet: an open-source tool for simultaneous global fits of EFT Wilson coefficients and PDFs

Mark N. Costantini, Elie Hammou, Zahari Kassabov +5

We present the open-source SIMUnet code, designed to fit Standard Model Effective Field Theory (SMEFT) Wilson coefficient alongside Parton Distribution Functions (PDFs) of the prot…

hep-ph2024★ 2 cited

The Path to NLO Parton Distributions

The NNPDF Collaboration, Richard D. Ball, Andrea Barontini +16

We extend the existing leading (LO), next-to-leading (NLO), and next-to-next-to-leading order (NNLO) NNPDF4.0 sets of parton distribution functions (PDFs) to approximate next-to-ne…

hep-ph2024★ 2 cited

Determination of the theory uncertainties from missing higher orders on NNLO parton distributions with percent accuracy

The NNPDF Collaboration, Richard D. Ball, Andrea Barontini +16

We include uncertainties due to missing higher order corrections to QCD computations (MHOU) used in the determination of parton distributions (PDFs) in the recent NNPDF4.0 set of P…

hep-ph2024★ 1 cited

Photons in the proton: implications for the LHC

The NNPDF Collaboration, Richard D. Ball, Andrea Barontini +16

We construct a set of parton distribution functions (PDFs), based on the recent NNPDF4.0 PDF set, that also include a photon PDF. The photon PDF is constructed using the LuxQED for…

hep-ph2023

Hide and seek: how PDFs can conceal New Physics

Elie Hammou, Zahari Kassabov, Maeve Madigan +5

The interpretation of LHC data, and the assessment of possible hints of new physics, require the precise knowledge of the proton structure in terms of parton distribution functions…

hep-ph2023★ 1 cited

HighTEA: High energy Theory Event Analyser

Michał Czakon, Zahari Kassabov, Alexander Mitov +2

We introduce HighTEA, a new paradigm for deploying fully-differential next-to-next-to leading order (NNLO) calculations for collider observables. In principle, any infrared safe ob…

hep-ph2023★ 41 cited

The top quark legacy of the LHC Run II for PDF and SMEFT analyses

Zahari Kassabov, Maeve Madigan, Luca Mantani +4

We assess the impact of top quark production at the LHC on global analyses of parton distributions (PDFs) and of Wilson coefficients in the SMEFT, both separately and in the framew…

hep-ph2022★ 1 cited

Response to "Parton distributions need representative sampling"

The NNPDF Collaboration, Richard D. Ball, Juan Cruz-Martinez +7

We respond to the criticism raised by Courtoy et al., in which the faithfulness of the NNPDF4.0 sampling is questioned and an under-estimate of the NNPDF4.0 PDF uncertainties is im…

hep-ph2022★ 24 cited

Parton distributions with scale uncertainties: a MonteCarlo sampling approach

Zahari Kassabov, Maria Ubiali, Cameron Voisey

We present the MCscales approach for incorporating scale uncertainties in parton distribution functions (PDFs). The new methodology builds on the Monte Carlo sampling for propagati…

hep-ph2022

Regularising experimental correlations in LHC data: theory and application to a global analysis of parton distributions

Zahari Kassabov, Emanuele R. Nocera, Michael Wilson

We show how an inaccurate determination of experimental uncertainty correlations in high-precision LHC measurements may undermine the reliability of the associated . We formul…

hep-ph2021

Parton distributions in the SMEFT from high-energy Drell-Yan tails

Maeve Madigan, James Moore

We present a study of the interplay between PDF and EFT effects in high-mass Drell-Yan at the LHC. We quantify the impact of a consistent joint determination of the PDFs and Wilson…

hep-ph2021

An open-source machine learning framework for global analyses of parton distributions

Richard D. Ball, Stefano Carrazza, Juan Cruz-Martinez +14

We present the software framework underlying the NNPDF4.0 global determination of parton distribution functions (PDFs). The code is released under an open source licence and is acc…

hep-ph2021★ 429 cited

The Path to Proton Structure at One-Percent Accuracy

Richard D. Ball, Stefano Carrazza, Juan Cruz-Martinez +14

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…

hep-ph2021★ 58 cited

Parton distributions in the SMEFT from high-energy Drell-Yan tails

Admir Greljo, Shayan Iranipour, Zahari Kassabov +5

The high-energy tails of charged- and neutral-current Drell-Yan processes provide important constraints on the light quark and anti-quark parton distribution functions (PDFs) in th…

hep-ph2020★ 8 cited

Parton distribution functions

Stefano Forte, Stefano Carrazza

We discuss the determination of the parton substructure of hadrons by casting it as a peculiar form of pattern recognition problem in which the pattern is a probability distributio…

hep-ph2020★ 38 cited

Why Cannot be Determined from Hadronic Processes without Simultaneously Determining the Parton Distributions

Stefano Forte, Zahari Kassabov

We show that any determination of the strong coupling from a process which depends on parton distributions, such as hadronic processes or deep-inelastic scattering, generally…

hep-ph2019

Parton Distributions with Theory Uncertainties: General Formalism and First Phenomenological Studies

The NNPDF Collaboration, Rabah Abdul Khalek, Richard D. Ball +11

We formulate a general approach to the inclusion of theoretical uncertainties, specifically those related to the missing higher order uncertainty (MHOU), in the determination of pa…

hep-ph2019★ 1 cited

A First Determination of Parton Distributions with Theoretical Uncertainties

The NNPDF Collaboration, Rabah Abdul Khalek, Richard D. Ball +11

The parton distribution functions (PDFs) which characterize the structure of the proton are currently one of the dominant sources of uncertainty in the predictions for most process…

physics.comp-ph2018★ 30 cited

Machine Learning in High Energy Physics Community White Paper

Kim Albertsson, Piero Altoe, Dustin Anderson +125

Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by a…

hep-ph2018★ 30 cited

Les Houches 2017: Physics at TeV Colliders Standard Model Working Group Report

J. Bendavid, F. Caola, V. Ciulli +102

This Report summarizes the proceedings of the 2017 Les Houches workshop on Physics at TeV Colliders. Session 1 dealt with (I) new developments relevant for high precision Standard…

hep-ph2018

PDF dependence on parameter fits from hadronic data

Zahari Kassabov

We present a discussion on the methods for extracting a given parameter from measurements of hadronic data, with particular focus on determinations of the strong coupling constant.…

hep-ph2018★ 65 cited

Precision determination of the strong coupling constant within a global PDF analysis

Richard D. Ball, Stefano Carrazza, Luigi Del Debbio +5

We present a determination of the strong coupling constant based on the NNPDF3.1 determination of parton distributions, which for the first time includes constraints fro…

hep-ph2017★ 2 cited

The HiggsTools Handbook: Concepts and observables for deciphering the Nature of the Higgs Sector

M. Boggia, J. M. Cruz-Martinez, Hjalte Frellesvig +15

This Report summarizes some of the activities of the HiggsTools Initial Training Network working group in the period 2015-2017. The main goal of this working group was to produce a…

hep-ph2017★ 1.6k cited

Parton distributions from high-precision collider data

The NNPDF Collaboration, Richard D. Ball, Valerio Bertone +13

We present a new set of parton distributions, NNPDF3.1, which updates NNPDF3.0, the first global set of PDFs determined using a methodology validated by a closure test. The update…