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相关论文: xFitter 2.0.0: An Open Source QCD Fit Framework

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We explore the role of parametrizations for nonperturbative QCD functions in global analyses, with a specific application to extending a phenomenological analysis of the parton distribution functions (PDFs) in the charged pion realized in…

高能物理 - 唯象学 · 物理学 2024-04-17 Lucas Kotz , Aurore Courtoy , Pavel Nadolsky , Fredrick Olness , Maximiliano Ponce-Chavez

Recent high precision experimental data from a variety of hadronic processes opens new opportunities for determination of the collinear parton distribution functions (PDFs) of the proton. In fact, the wealth of information from experiments…

高能物理 - 唯象学 · 物理学 2018-08-24 Bo-Ting Wang , T. J. Hobbs , Sean Doyle , Jun Gao , Tie-Jiun Hou , Pavel M. Nadolsky , Fredrick I. Olness

We introduce a new parametrization for the parton distribution functions (PDFs) designed to be flexible in the small-x region. We implement it in the xFitter open-source PDF fitting tool, and compare it to the default xFitter…

高能物理 - 唯象学 · 物理学 2019-10-25 Marco Bonvini , Francesco Giuli

Sets of parton distribution functions (PDFs) of the proton are reported for the leading (LO), next-to-leading (NLO) and next-to-next-to leading order (NNLO) QCD calculations. The parton distribution functions are determined with the…

A new analysis of the modification of the hadronization process in the nuclear medium for pions is presented. The effective description is condensed in a set of medium modified fragmentation functions (nFFs) obtained at next-to-leading…

高能物理 - 唯象学 · 物理学 2021-01-05 Pía Zurita

Parton distribution functions (PDFs) often include datasets corresponding to processes whereby the theoretical predictions at next-to-next-to-leading order (NNLO) in peturbative QCD have to be approximated, and this approximation may be…

高能物理 - 唯象学 · 物理学 2024-08-21 Tanishq Sharma

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

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…

We present a new software package designed to reduce the computational burden of hadron collider measurements in Parton Distribution Function (PDF) fits. The APFELgrid package converts interpolated weight tables provided by APPLgrid files…

高能物理 - 唯象学 · 物理学 2017-01-04 Valerio Bertone , Stefano Carrazza , Nathan P. Hartland

We present recent updates in the xFitter software framework for global fits of parton distribution functions in high-energy physics. Our focus is on investigating the sensitivity to Z boson couplings using the forward-backward asymmetry in…

高能物理 - 唯象学 · 物理学 2024-08-14 Oleksandr Zenaiev

Determinations of the proton's collinear parton distribution functions (PDFs) are emerging with growing precision due to increased experimental activity at facilities like the Large Hadron Collider. While this copious information is…

高能物理 - 唯象学 · 物理学 2019-01-24 Bo-Ting Wang , T. J. Hobbs , Sean Doyle , Jun Gao , Tie-Jiun Hou , Pavel M. Nadolsky , Fredrick I. Olness

We review the current status of spin-averaged and spin-dependent parton distribution functions (PDFs) of the nucleon. After presenting the formalism used to fit PDFs in modern global data analyses, we discuss constraints placed on the PDFs…

高能物理 - 唯象学 · 物理学 2015-06-16 P. Jimenez-Delgado , W. Melnitchouk , J. F. Owens

The xPDFsuite software program is described. It is for processing and analyzing atomic pair distribution functions (PDF) from X-ray powder diffraction data. It provides a convenient GUI for SrXplanr and PDFgetX3, allowing the users to…

材料科学 · 物理学 2015-02-25 Xiaohao Yang , Pavol Juhas , Christopher L. Farrow , Simon J. L. Billinge

We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at…

高能物理 - 实验 · 物理学 2015-06-23 M. Baak , G. J. Besjes , D. Cote , A. Koutsman , J. Lorenz , D. Short

The parton distribution functions (PDFs) of the proton, a necessary input to almost all theory predictions for hadron colliders, are reviewed in this document. An introduction to the PDF determination by global analyses of the main PDF…

高能物理 - 唯象学 · 物理学 2019-08-14 Ringaile Placakyte

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

We review the current state of the art in the determination of the parton substructure of the nucleon, as expressed in terms of parton distribution functions (PDFs), and probed in high-energy lepton-hadron and hadron-hadron collisions, and…

高能物理 - 唯象学 · 物理学 2013-10-23 Stefano Forte , Graeme Watt

We present progress towards a unified framework enabling the simultaneous determination of the parton distribution functions (PDFs) of the proton, deuteron, and nuclei up to lead $(^{208}\rm{Pb})$. Our approach is based on the integration…

高能物理 - 唯象学 · 物理学 2023-07-13 Tanjona Rabemananjara

We present a first attempt to design a quantum circuit for the determination of the parton content of the proton through the estimation of parton distribution functions (PDFs), in the context of high energy physics (HEP). The growing…

高能物理 - 唯象学 · 物理学 2021-03-03 Adrián Pérez-Salinas , Juan Cruz-Martinez , Abdulla A. Alhajri , Stefano Carrazza

Fant\^omas is a C++ toolkit for exploring the parametrization dependence of parton distribution functions (PDFs) and other correlator functions in quantum chromodynamics (QCD). Fant\^omas facilitates the generation of adaptable polynomial…

高能物理 - 唯象学 · 物理学 2025-08-01 Lucas Kotz , Aurore Courtoy , T. J. Hobbs , Pavel Nadolsky , Fredrick Olness , Maximiliano Ponce-Chavez , Varada Purohit