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Representing the parton distribution functions (PDFs) of the proton and other hadrons through flexible, high-fidelity parametrizations has been a long-standing goal of particle physics phenomenology. This is particularly true since the…

高能物理 - 唯象学 · 物理学 2024-06-21 Brandon Kriesten , T. J. Hobbs

A robust uncertainty estimate in global analyses of Parton Distribution Functions (PDFs) is essential at the Large Hadron Collider (LHC), especially in view of the high-precision data anticipated by experimentalists in the High-Luminosity…

高能物理 - 唯象学 · 物理学 2026-04-14 Mark N. Costantini , Luca Mantani , James M. Moore , Maria Ubiali

Parton Distribution Functions (PDFs) model the parton content of the proton. Among the many collaborations which focus on PDF determination, NNPDF pioneered the use of Neural Networks to model the probability of finding partons (quarks and…

计算物理 · 物理学 2020-07-21 Juan M Cruz-Martinez , Stefano Carrazza , Roy Stegeman

Perturbative quantum chromodynamics (QCD) ceases to be applicable at low interaction energies due to the rapid increase of the strong coupling. In that limit, the non-perturbative regime determines the properties of quarks and gluons…

高能物理 - 唯象学 · 物理学 2021-10-06 Rabah Abdul Khalek

In this contribution we present a status report on the recent progress towards an analysis of nuclear parton distribution functions (nPDFs) using the NNPDF methodology. We discuss how the NNPDF fitting approach can be extended to account…

高能物理 - 唯象学 · 物理学 2018-11-15 Rabah Abdul Khalek , Jacob J. Ethier , Juan Rojo

Accurate Standard Model predictions of proton-proton collisions are essential for interpreting the current and forthcoming experimental measurements from high-energy colliders. The quest for physics beyond the Standard Model is in fact…

高能物理 - 唯象学 · 物理学 2025-04-09 Giacomo Magni

Traditional Bayesian approaches for model uncertainty quantification rely on notoriously difficult processes of marginalization over each network parameter to estimate its probability density function (PDF). Our hypothesis is that internal…

机器学习 · 计算机科学 2021-03-03 Rishabh Singh , Jose C. Principe

We present a new regression model for the determination of parton distribution functions (PDF) using techniques inspired from deep learning projects. In the context of the NNPDF methodology, we implement a new efficient computing framework…

高能物理 - 唯象学 · 物理学 2019-09-04 Stefano Carrazza , Juan Cruz-Martinez

We critically assess the robustness of uncertainties on parton distribution functions (PDFs) determined using neural networks from global sets of experimental data collected from multiple experiments. We view the determination of PDFs as an…

高能物理 - 唯象学 · 物理学 2025-03-25 Andrea Barontini , Mark N. Costantini , Giovanni De Crescenzo , Stefano Forte , Maria Ubiali

A determination of Parton Distribution Functions (PDFs) from a global fit to a dataset including measurements from the LHC has been performed. The determinations have been carried out according to the NNPDF methodology, leading to a fit…

高能物理 - 唯象学 · 物理学 2014-11-04 Nathan Hartland

Parton Distribution Functions (PDFs) contribute significantly to the uncertainty on the determination of the top-quark pole mass and other precision measurements at the Large Hadron Collider (LHC). It is crucial to understand these…

高能物理 - 唯象学 · 物理学 2024-01-25 Jason P. Gombas , Reinhard Schwienhorst , Binbin Dong , Jarrett Fein

We present a model-independent determination of the nuclear parton distribution functions (nPDFs) using machine learning methods and Monte Carlo techniques based on the NNPDF framework. The neutral-current deep-inelastic nuclear structure…

高能物理 - 唯象学 · 物理学 2020-10-28 Rabah Abdul Khalek , Jacob J. Ethier , Juan Rojo , Gijs van Weelden

Parton Distribution Functions (PDFs) are a key ingredient in theoretical predictions for Large Hadron Collider (LHC) observables and play a central role in the extraction of precision Standard Model (SM) and Beyond the SM (BSM) parameters…

We present a determination of the parton distributions of the nucleon from a global set of hard scattering data using the NNPDF methodology at LO and NNLO in perturbative QCD, thereby generalizing to these orders the NNPDF2.1 NLO parton…

We review various methods used to estimate uncertainties in quantum correlation functions, such as parton distribution functions (PDFs). Using a toy model of a PDF, we compare the uncertainty estimates yielded by the traditional Hessian and…

高能物理 - 唯象学 · 物理学 2022-08-17 N. T. Hunt-Smith , A. Accardi , W. Melnitchouk , N. Sato , A. W. Thomas , M. J. White

A clear understanding of nuclear parton distribution functions (nPDFs) plays a crucial role in the interpretation of collider data taken at the Relativistic Heavy Ion Collider (RHIC), the Large Hadron Collider (LHC) and in the near future…

高能物理 - 唯象学 · 物理学 2022-07-13 P. Duwentäster , T. Ježo , M. Klasen , K. Kovařík , A. Kusina , K. F. Muzakka , F. I. Olness , R. Ruiz , I. Schienbein , J. Y. Yu

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…

We review recent progress in the determination of the parton distribution functions (PDFs) of the proton, with emphasis on the applications for precision phenomenology at the Large Hadron Collider (LHC). First of all, we introduce the…

高能物理 - 唯象学 · 物理学 2018-05-23 Jun Gao , Lucian Harland-Lang , Juan Rojo

The interest into parton distribution functions (PDFs) and fragmentation functions (FFs) in current high energy physics research is twofold. On the one hand, they are fundamental objects to conduct precision phenomenology studies, e.g. at…

高能物理 - 唯象学 · 物理学 2025-09-22 Tanishq Sharma

The choice of data that enters a global QCD analysis can have a substantial impact on the resulting parton distributions and their predictions for collider observables. One of the main reasons for this has to do with the possible presence…

高能物理 - 唯象学 · 物理学 2014-09-11 Juan Rojo
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