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We illustrate how electron Parton Distribution Functions (PDFs) with next-to-leading collinear logarithmic accuracy must be employed in the context of perturbative predictions for high-energy $e^+e^-$-collision processes. In particular, we…

高能物理 - 唯象学 · 物理学 2022-09-23 V. Bertone , M. Cacciari , S. Frixione , G. Stagnitto , M. Zaro , X. Zhao

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

A new combined next to leading order QCD analysis of the polarized inclusive and semi-inclusive deep inelastic lepton-hadron scattering (DIS) data is presented. In contrast to previous combined analyses, the $1/Q^2$ terms (kinematic -…

高能物理 - 唯象学 · 物理学 2015-03-17 Elliot Leader , Aleksander V. Sidorov , Dimiter B. Stamenov

The parton distribution functions (PDFs) provide process-independent information about the quarks and gluons inside hadrons. Although the gluon PDF can be obtained from a global fit to experimental data, it is not constrained well in the…

高能物理 - 格点 · 物理学 2021-06-09 Zhouyou Fan , Rui Zhang , Huey-Wen Lin

We construct a set of parton distribution functions (PDFs) in which fixed-order NLO and NNLO calculations are supplemented with soft-gluon (threshold) resummation up to NLL and NNLL accuracy respectively, suitable for use in conjunction…

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

We develop in more detail our reweighting method for incorporating new datasets in parton fits based on a Monte Carlo representation of PDFs. After revisiting the derivation of the reweighting formula, we show how to construct an unweighted…

We present the results of a PDF fit to differential top quark production within the MMHT framework. We in particular consider ATLAS data in the lepton + jet and dilepton channels and CMS data in the lepton + jet channel, at 8 TeV. While the…

高能物理 - 唯象学 · 物理学 2020-06-18 Shaun Bailey , Lucian Harland-Lang

We investigate the uncertainties of the heavy-quark parton distribution functions in the variable flavor number scheme. Because the charm- and bottom-quark parton distribution functions (PDFs) are constructed predominantly from the gluon…

高能物理 - 唯象学 · 物理学 2008-11-26 Z. Sullivan , P. M. Nadolsky

In this work, we complete our CT18qed study with the neutron's photon parton distribution function (PDF), which is essential for the nucleus scattering phenomenology. Two methods, CT18lux and CT18qed, based on the LUXqed formalism and the…

高能物理 - 唯象学 · 物理学 2024-04-01 Keping Xie , Bei Zhou , T. J. Hobbs

We perform a comprehensive new Monte Carlo analysis of high-energy lepton-lepton, lepton-hadron and hadron-hadron scattering data to simultaneously determine parton distribution functions (PDFs) in the proton and parton to hadron…

高能物理 - 唯象学 · 物理学 2021-10-20 E. Moffat , W. Melnitchouk , T. C. Rogers , N. Sato

We review basic ideas and recent developments on the determination of the parton substructure of the nucleon, in view of applications to precision hadron collider physics. We review the way information on parton distributions (PDFs) is…

高能物理 - 唯象学 · 物理学 2015-03-17 Stefano Forte

The status of the global fits of nuclear parton distributions (nPDFs) is reviewed. In addition to comparing the contemporary analyses of nPDFs, difficulties and controversies posed by the neutrino-nucleus deeply inelastic scattering data is…

高能物理 - 唯象学 · 物理学 2015-06-18 Hannu Paukkunen

In our recent study we have determined two new spatially dependent nuclear PDF (nPDF) sets, EPS09s and EKS98s. With these, the hard-process cross-sections can be calculated in different centrality classes consistently with the globally…

高能物理 - 唯象学 · 物理学 2015-06-12 Ilkka Helenius , Kari J. Eskola , Heli Honkanen , Carlos A. Salgado

The quark exchange model (QEM) is reformulated for the $A=12$ and $14$ systems to obtain the constituent quark distributions of $^{12}C$ and $^{14}N$ nuclei, respectively. Afterwards, the different types of the point-like parton…

核理论 · 物理学 2021-08-09 A. Hadian , M. Modarres

We present a new set of leading twist parton distribution functions, referred to as "CJ15", which take advantage of developments in the theoretical treatment of nuclear corrections as well as new data. The analysis includes for the first…

高能物理 - 唯象学 · 物理学 2016-06-29 A. Accardi , L. T. Brady , W. Melnitchouk , J. F. Owens , N. Sato

The DGLAP analyses of the nuclear parton distribution functions (nPDF) based on the global fits to the data are reviewed, and the results from EKS98 and HKM are compared. The usefulness of measuring hard probes in $pA$ collisions, at the…

高能物理 - 唯象学 · 物理学 2007-05-23 K. J. Eskola , H. Honkanen , V. J. Kolhinen , C. A. Salgado

Nuclear parton distribution functions (NPDFs) are determined by global analyses of experimental data on structure-function ratios F_2^A/F_2^{A'} and Drell-Yan cross-section ratios \sigma_{DY}^A/\sigma_{DY}^{A'}. The analyses are done in the…

高能物理 - 唯象学 · 物理学 2008-11-26 M. Hirai , S. Kumano , T. -H. Nagai

The current analysis aims to present the results of a QCD analysis of diffractive parton distribution functions (diffractive PDFs) at next-to-leading order (NLO) accuracy in perturbative QCD. In this new determination of diffractive PDFs,…

高能物理 - 唯象学 · 物理学 2019-09-20 Atefeh Maktoubian , Hossein Mehraban , Hamzeh Khanpour , Muhammad Goharipour

The LHC has recently released precise measurements of the transverse momentum distribution of the Z-boson that provide a unique constraint on the structure of the proton. Theoretical developments now allow the prediction of these…

高能物理 - 唯象学 · 物理学 2017-09-13 Radja Boughezal , Alberto Guffanti , Frank Petriello , Maria Ubiali
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