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相关论文: Parton Distributions: Summary Report

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We provide an updated recommendation for the usage of sets of parton distribution functions (PDFs) and the assessment of PDF and PDF+$\alpha_s$ uncertainties suitable for applications at the LHC Run II. We review developments since the…

We study the cross section \sigma and Forward-Backward asymmetry A_{FB} in the process pp \to \gamma^*,Z \to \ell^+\ell^- (with \ell=e,\mu) for determinations of Parton Distribution Functions (PDFs) of the proton. We show that, once mapped…

高能物理 - 唯象学 · 物理学 2019-03-19 E. Accomando , J. Fiaschi , F. Hautmann , S. Moretti

An overwhelming number of theoretical predictions for hadron colliders require parton distribution functions (PDFs), which are an important ingredient of theory infrastructure for the next generation of high-energy experiments. This…

The detailed comprehension of momentum fraction and energy dependence of proton structure functions is among the major difficulties in high-energy physics. Perturbative quantum chromodynamics (QCD) plays as an extensive foundation for…

高能物理 - 唯象学 · 物理学 2025-09-25 Akbari Jahan , Diptimonta Neog

We present a study of the results obtained combining LO partonic matrix elements with either LO or NLO partons distributions. These are compared to the best prediction using NLO for both matrix elements and parton distributions. The aim is…

高能物理 - 唯象学 · 物理学 2008-11-26 A. Sherstnev , R. S. Thorne

I explain the current status of parton-distribution-function (PDF) studies and future experimental prospects on their determinations. First, unpolarized PDFs of the nucleon are introduced as a field of precision QCD physics including…

高能物理 - 唯象学 · 物理学 2018-09-17 S. Kumano

We review the latest progress in lattice QCD calculations of the partonic structure of hadrons. This structure is, in particular, described in terms of $x$-dependent distributions, the simplest of which are the standard parton distribution…

高能物理 - 格点 · 物理学 2021-10-18 Krzysztof Cichy

We study the uncertainties in parton distributions, determined in global fits to deep inelastic and related hard scattering data, due to so-called theoretical errors. Amongst these, we include potential errors due to the change of…

高能物理 - 唯象学 · 物理学 2009-11-10 A. D. Martin , R. G. Roberts , W. J. Stirling , R. S. Thorne

Experimental errors are now incredibly precise, and are often dominated by the systematic uncertainties. Therefore the errors obtained in the Parton Distribution Functions that are extracted from this data will also be dominated by these…

高能物理 - 唯象学 · 物理学 2024-08-26 Matthew Reader

We extract new parton distribution functions (PDFs) of the proton by global analysis of hard scattering data in the general-mass framework of perturbative quantum chromodynamics. Our analysis includes new theoretical developments together…

高能物理 - 唯象学 · 物理学 2010-10-27 Hung-Liang Lai , Marco Guzzi , Joey Huston , Zhao Li , Pavel M. Nadolsky , Jon Pumplin , C. -P. Yuan

We use the nCTEQ analysis framework to investigate nuclear Parton Distribution Functions (nPDFs) in the region of large x and intermediate-to-low $Q$, with special attention to recent JLab Deep Inelastic Scattering data on nuclear targets.…

The effect of full $7$ sets of LHC ATLAS jet cross sections data at $ \sqrt{s} = 7$ TeV on the proton parton distribution functions (PDFs) up to next-to-next-to-next-to-leading order (NNNLO or N3LO) corrections is investigated for the first…

高能物理 - 唯象学 · 物理学 2020-05-05 A. Vafaee , K. Javidan , A. B. Shokouhi

The quantum statistical parton distributions approach proposed more than one decade ago is revisited by considering a larger set of recent and accurate Deep Inelastic Scattering experimental results. It enables us to improve the description…

高能物理 - 唯象学 · 物理学 2015-12-09 Claude Bourrely , Jacques Soffer

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 a preliminary set of updated NLO parton distributions. For the first time we have a quantitative extraction of the strange quark and antiquark distributions and their uncertainties determined from CCFR and NuTeV dimuon cross…

高能物理 - 唯象学 · 物理学 2007-06-05 R. S. Thorne , A. D. Martin , W. J. Stirling , G. Watt

With the ongoing Run 3 of the LHC and its upcoming High-Luminosity upgrade, there is a growing need to study observables with high precision both experimentally and theoretically. To increase precision on the theory side, improvements of…

高能物理 - 唯象学 · 物理学 2024-04-01 Federico Silvetti

In this article, we review recent lattice calculations on the $x$-dependence of parton distributions, with the latter providing information on hadron structure. These calculations are based on matrix elements of boosted hadrons coupled to…

高能物理 - 格点 · 物理学 2021-03-17 Martha Constantinou

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 consider the effect on LHC jet cross sections on partons distribution functions (PDFs), in particular the MSTW2008 set of PDFs. We first compare the published inclusive jet data to the predictions using MSTW2008, finding a very good…

高能物理 - 唯象学 · 物理学 2014-08-05 B. J. A. Watt , P. Motylinski , R. S. Thorne

We present new parton distribution functions (PDFs) up to next-to-next-to-leading order (NNLO) from the CTEQ-TEA global analysis of quantum chromodynamics. These differ from previous CT PDFs in several respects, including the use of data…

高能物理 - 唯象学 · 物理学 2016-03-09 Sayipjamal Dulat , Tie Jiun Hou , Jun Gao , Marco Guzzi , Joey Huston , Pavel Nadolsky , Jon Pumplin , Carl Schmidt , Daniel Stump , C. P. Yuan
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