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相关论文: HOPPET v2 release note

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This contribution describes the HOPPET Fortran~95 package for carrying out DGLAP evolution and other common manipulations of PDFs. The PDFs are represented on a grid in $x$-space so as to avoid limitations on the functional form of input…

高能物理 - 唯象学 · 物理学 2008-07-02 Gavin Salam , Juan Rojo

This document describes a Fortran 95 package for carrying out DGLAP evolution and other common manipulations of parton distribution functions (PDFs). The PDFs are represented on a grid in x-space so as to avoid limitations on the functional…

高能物理 - 唯象学 · 物理学 2010-03-25 Gavin P. Salam , Juan Rojo

We present the scheme-invariant unpolarized and polarized flavor non-singlet evolution equation to N$^3$LO for the structure functions $F_2(x,Q^2)$ and $g_1(x,Q^2)$ including the charm- and bottom quark effects in the asymptotic…

高能物理 - 唯象学 · 物理学 2021-09-15 J. Blümlein , M. Saragnese

We present the new MSHT20 set of parton distribution functions (PDFs) of the proton, determined from global analyses of the available hard scattering data. The PDFs are made available at NNLO, NLO, and LO, and supersede the MMHT14 sets.…

高能物理 - 唯象学 · 物理学 2022-08-22 S. Bailey , T. Cridge , L. A. Harland-Lang , A. D. Martin , R. S. Thorne

Quantum electrodynamics and electroweak corrections are important ingredients for many theoretical predictions at the LHC. This paper documents APFEL, a new PDF evolution package that allows for the first time to perform DGLAP evolution up…

高能物理 - 唯象学 · 物理学 2015-06-17 Valerio Bertone , Stefano Carrazza , Juan Rojo

We present our QCD analysis of the proton structure function $F_2^p(x,Q^2)$ to determine the parton distributions at the next-to-leading order (NLO). The heavy quark contributions to $F_2^i(x,Q^2)$, with $i$ = $c$, $b$ have been included in…

高能物理 - 唯象学 · 物理学 2015-06-05 H. Khanpour , Ali N. Khorramian , S. Atashbar Tehrani

The next-to-leading order (NLO) evolution of the parton distribution functions (PDF's) in QCD is the "industry standard" in the lepton-hadron and hadron-hadron collider data analysis. The standard NLO DGLAP evolution is formulated for…

高能物理 - 唯象学 · 物理学 2009-10-02 S. Jadach , M. Skrzypek

The next-to-leading order (NLO) evolution of the parton distribution functions (PDFs) in QCD is a common tool in the lepton-hadron and hadron-hadron collider data analysis. The standard NLO DGLAP evolution is formulated for inclusive…

高能物理 - 唯象学 · 物理学 2010-02-02 S. Jadach , M. Skrzypek , A. Kusina , M. Slawinska

We present recent progress on the Heavy-Flavor Non-Relativistic Evolution (HF-NRevo) framework, designed to describe leading-power fragmentation of heavy-flavored hadrons at moderate to large transverse momentum. Starting from NLO NRQCD…

高能物理 - 唯象学 · 物理学 2025-10-28 Francesco Giovanni Celiberto , Francesca Lonigro

Standard methods for higher-order calculations of QCD cross sections in hadron-induced collisions are time-consuming. The fastNLO project uses multi-dimensional interpolation techniques to convert the convolutions of perturbative…

高能物理 - 唯象学 · 物理学 2012-08-20 Daniel Britzger , Klaus Rabbertz , Fred Stober , Markus Wobisch

We have investigated the next-to-next-to-leading order (NNLO) corrections to inclusive hadron production in e^+e^- annihilation and the related parton fragmentation distributions, the `time-like' counterparts of the `space-like'…

高能物理 - 唯象学 · 物理学 2008-11-26 A. Mitov , S. Moch , A. Vogt

We present numerical solutions of the $Q^2$ evolution equations at next-to-leading order (NLO) for unpolarized and polarized parton distributions, in both the flavor non-singlet and singlet channels. The numerical method is based on a…

高能物理 - 唯象学 · 物理学 2009-10-28 T. Weigl , W. Melnitchouk

We study the next-to-next-to-leading order (NNLO) evolution of flavour singlet parton densities and structure functions in massless perturbative QCD. Present information on the corresponding three-loop splitting functions is used to derive…

高能物理 - 唯象学 · 物理学 2009-10-31 W. L. van Neerven , A. Vogt

We present a determination of the parton distributions of the nucleon from a global set of hard scattering data using the NNPDF methodology: NNPDF2.0. Experimental data include deep-inelastic scattering with the combined HERA-I dataset,…

高能物理 - 唯象学 · 物理学 2014-11-20 Richard D. Ball , Luigi Del Debbio , Stefano Forte , Alberto Guffanti , Jose I. Latorre , Juan Rojo , Maria Ubiali

We present the results of our QCD analysis for non-singlet unpolarized quark distributions and structure function $F_2(x,Q^2)$ up to N$^3$LO. In this regards 4-loop anomalous dimension can be obtain from the Pad\'e approximations. The…

高能物理 - 唯象学 · 物理学 2010-02-03 Ali N. Khorramian , H. Khanpour , S. Atashbar Tehrani

We summarize recent results on the evolution of unpolarized parton densities and deep-inelastic structure functions in massless perturbative QCD. Due to last year's extension of the integer-moment calculations of the three-loop splitting…

高能物理 - 唯象学 · 物理学 2008-11-26 W. L. van Neerven , A. Vogt

We present LO, NLO and NNLO sets of parton distribution functions (PDFs) of the proton determined from global analyses of the available hard scattering data. These MMHT2014 PDFs supersede the `MSTW2008' parton sets, but are obtained within…

高能物理 - 唯象学 · 物理学 2015-06-11 L. A. Harland-Lang , A. D. Martin , P. Motylinski , R. S. Thorne

We present sets of parton distribution functions (PDFs), based on the NNPDF3.0 family, which include the photon PDF from the NNPDF2.3QED sets, and leading-order QED contributions to the DGLAP evolution as implemented in the public code…

高能物理 - 唯象学 · 物理学 2016-06-29 V. Bertone , S. Carrazza

We present NNPDF3.0, the first set of parton distribution functions (PDFs) determined with a methodology validated by a closure test. NNPDF3.0 uses a global dataset including HERA-II deep-inelastic inclusive cross-sections, the combined…

Recently we have updated a multi-phase transport (AMPT) model with modern parton distribution functions of nuclei (nPDFs). Here we study open charm production in the updated AMPT model and compare to the experimental data from $pp$ and $AA$…

核理论 · 物理学 2020-04-17 L. Zheng , C. Zhang , S. S. Shi , Z. W. Lin
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