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We present preliminary results on the determination of spin-dependent, or polarised, Parton Distribution Functions (PDFs) from all relevant inclusive polarised DIS data. The analysis is performed within the NNPDF approach, which provides a…

高能物理 - 唯象学 · 物理学 2012-06-26 Emanuele R. Nocera , Stefano Forte , Giovanni Ridolfi , Juan Rojo

We present NNPDFpol2.0, a new set of collinear helicity parton distribution functions (PDFs) of the proton based on legacy measurements of structure functions in inclusive neutral-current longitudinally polarised deep-inelastic scattering…

We present the MCscales approach for incorporating scale uncertainties in parton distribution functions (PDFs). The new methodology builds on the Monte Carlo sampling for propagating experimental uncertainties into the PDF space that…

高能物理 - 唯象学 · 物理学 2023-03-27 Zahari Kassabov , Maria Ubiali , Cameron Voisey

Parton distributions functions (PDFs), which are essential to the interpretation of data from high energy colliders, are measured by representing them as functional forms containing many parameters. Those parameters are determined by…

高能物理 - 唯象学 · 物理学 2015-03-13 Jon Pumplin

I review recent progress in the NNPDF global analyses of parton distributions (PDFs) focusing on developments contributing to its new upcoming release: NNPDF4.0. The NNPDF4.0 determination represents unprecedented progress in three main…

高能物理 - 唯象学 · 物理学 2021-04-20 Juan Rojo

We present a determination of the strong coupling $\alpha_s(m_Z)$ from a global dataset including both fixed-target and collider data from deep-inelastic scattering and a variety of hadronic processes, with a simultaneous determination of…

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

This paper investigates the crucial role of parton distribution functions (PDFs) in high-energy physics, particularly their impact on the extraction of generalized parton distributions (GPDs) at zero skewness. To this aim, we perform six…

高能物理 - 唯象学 · 物理学 2026-03-23 The MMGPDs Collaboration , Fatemeh Irani , Muhammad Goharipour , K. Azizi

We present a new public code, FPPDF, to perform global fits of parton distribution functions (PDFs). The fitting methodology follows that implemented by the MSHT collaboration, namely applying a fixed polynomial parameterisation of the PDFs…

高能物理 - 唯象学 · 物理学 2026-02-10 J. M. Cruz-Martinez , T. Giani , L. A. Harland-Lang

Using QCD calculations of the cross section of inclusive dijet photoproduction in Pb-Pb ultraperipheral collisions in the LHC kinematics as pseudo-data, we study the effect of including these data using the Bayesian reweighting technique on…

高能物理 - 唯象学 · 物理学 2019-05-22 V. Guzey , M. Klasen

A thorough understanding of PDFs and their uncertainties is important for the LHC and for future collider experiments. The recently released NNPDF3.0 set was presented alongside results from closure tests, where PDF fits were performed on…

高能物理 - 唯象学 · 物理学 2015-06-25 Christopher S. Deans

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 distribution, and we present the way this problem has been tackled and…

高能物理 - 唯象学 · 物理学 2020-08-31 Stefano Forte , Stefano Carrazza

In this article we obtain a new set of nuclear parton distribution functions (nuclear PDFs) at next-to-leading order and next-to-next-to-leading order accuracy in perturbative QCD. The common nuclear deep-inelastic scattering (DIS) data…

高能物理 - 唯象学 · 物理学 2021-08-17 Hamzeh Khanpour , Maryam Soleymaninia , S. Atashbar Tehrani , Hubert Spiesberger , Vadim Guzey

We compare predictions of nCTEQ15 nuclear parton distribution functions with proton-lead vector boson production data from the LHC. We select data sets that are most sensitive to nuclear PDFs and have potential to constrain them. We…

高能物理 - 唯象学 · 物理学 2017-08-02 A. Kusina , F. Lyonnet , D. B. Clark , E. Godat , T. Jezo , K. Kovarik , F. I. Olness , I. Schienbein , J. Y. Yu

We present MAPPDFpol1.0, a new determination of the helicity-dependent parton distribution functions (PDFs) of the proton from a set of longitudinally polarised inclusive and semi-inclusive deep-inelastic scattering data. The determination…

高能物理 - 唯象学 · 物理学 2025-04-23 MAP , Collaboration , : , Valerio Bertone , Amedeo Chiefa , Emanuele R. Nocera

We apply the Lagrange Multiplier method to study the uncertainties of physical predictions due to the uncertainties of parton distribution functions (PDFs), using the cross section for W production at a hadron collider as an archetypal…

高能物理 - 唯象学 · 物理学 2009-09-25 D. Stump , J. Pumplin , R. Brock , D. Casey , J. Huston , J. Kalk , H. L. Lai , W. K. Tung

We present a new method, based on Gaussian process regression, for reconstructing the continuous $x$-dependence of parton distribution functions (PDFs) from quasi-PDFs computed using lattice QCD. We examine the origin of the unphysical…

高能物理 - 格点 · 物理学 2020-11-25 Constantia Alexandrou , Giovanni Iannelli , Karl Jansen , Floriano Manigrasso

Recently a new set of Parton Distribution Functions (NNPDF1.2) has been produced and released by the NNPDF Collaboration. The inclusion of dimuon data in the analysis allows a determination of the strange content of the proton with faithful…

高能物理 - 唯象学 · 物理学 2009-07-28 Alberto Guffanti , Juan Rojo , Maria Ubiali

We perform a next-to-next-to-leading order (NNLO) analysis of nuclear parton distribution functions (nPDFs) using neutral current charged-lepton ($\ell ^\pm$ + nucleus) deeply inelastic scattering (DIS) data and Drell-Yan (DY) cross-section…

高能物理 - 唯象学 · 物理学 2016-01-29 Hamzeh Khanpour , S. Atashbar Tehrani

We present the determination of a set of parton distributions of the nucleon, at next-to-leading order, from a global set of deep-inelastic scattering data: NNPDF1.0. The determination is based on a Monte Carlo approach, with neural…