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Related papers: DGLAP analyses of nPDF: constraints from data

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As the current nuclear PDF analyses are mainly constrained by fixed-target Drell-Yan and deeply inelastic scattering data only the quark nuclear modifications at fairly large $x$ values are in a good control. Inclusive pion production in…

High Energy Physics - Phenomenology · Physics 2015-10-02 Ilkka Helenius , Hannu Paukkunen , Kari J. Eskola

This is the introductory part of my PhD thesis which consists of two parts, the separate introduction and four published articles. The introduction begins by a technically detailed description of the DGLAP evolution and the fast numerical…

High Energy Physics - Phenomenology · Physics 2009-06-16 Hannu Paukkunen

With the latest astronomical data including Cosmic Microwave Background (WMAP three year, CBI, ACBAR, VSA), Type Ia Supernova ("gold sample"), Galaxy Clustering (SDSS 3-D matter power, Lyman-$\alpha$ forest and Baryon Acoustic Oscillating…

Astrophysics · Physics 2010-10-27 Gong-Bo Zhao , Jun-Qing Xia , Xinmin Zhang

We discuss consistency of the nuclear effects between the electromagnetic and weak interactions. In order to study a possibility of different nuclear effects in the neutrino DIS process, double differential cross section data are compared…

High Energy Physics - Phenomenology · Physics 2016-12-21 Masanori Hirai

Global perturbative QCD analyses, based on large data sets from electron-proton and hadron collider experiments, provide tight constraints on the parton distribution function (PDF) in the proton. The extension of these analyses to nuclear…

High Energy Physics - Phenomenology · Physics 2011-07-29 Paloma Quiroga-Arias , Jose Guilherme Milhano , Urs Achim Wiedemann

In this article we present a review of the structure of the proton and the current status of our knowledge of the parton distribution functions (PDFs). The lepton-nucleon scattering experiments which provide the main constraints in PDF…

High Energy Physics - Experiment · Physics 2013-03-20 Emmanuelle Perez , Eram Rizvi

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…

High Energy Physics - Phenomenology · Physics 2020-08-31 Stefano Forte , Stefano Carrazza

We discuss the causes which can limit the accuracy of the predictions based on the conventional PDFs when including in global parton analyses the data at moderate scales $\mu$. The first is the existence of power corrections ${\cal O}…

High Energy Physics - Phenomenology · Physics 2020-07-15 A. D. Martin , M. G. Ryskin

Measurements of Deep Inelastic Scattering (DIS) provide a powerful tool to probe the fundamental structure of protons and other nuclei. The DIS cross sections can be expressed in terms of structure functions which are conventionally…

High Energy Physics - Phenomenology · Physics 2023-07-06 Tuomas Lappi , Heikki Mäntysaari , Hannu Paukkunen , Mirja Tevio

I review recent developments in the study of the low-x partonic content of protons and nuclei, with a focus on the latter, as one expects possible deviations from linear QCD evolution to be most pronounced in that case. I give examples of…

High Energy Physics - Phenomenology · Physics 2020-07-15 Thomas Peitzmann

We review progress in the global QCD analysis by the CTEQ-TEA group since the publication of CT18 parton distribution functions (PDFs) in the proton. Specifically, we discuss comparisons of CT18 NNLO predictions with the LHC 13 TeV…

In this paper, we discuss the algorithms used in the LO evolution program for nondiagonal parton distributions in the DGLAP region and discuss the stability of the code. Furthermore, we demonstrate that we can reproduce the case of the LO…

High Energy Physics - Phenomenology · Physics 2007-05-23 Andreas Freund , Vadim Guzey

In this talk, we present our recent work on next-to-leading order (NLO) nuclear parton distribution functions (nPDFs), which we call EPS09. As an extension to earlier NLO analyses, we complement the deep inelastic scattering and Drell-Yan…

High Energy Physics - Phenomenology · Physics 2009-06-17 Kari J. Eskola , Hannu Paukkunen , Carlos A. Salgado

Abundant and diverse data on medicines manufacturing and other lifecycle components has been made easily accessible in the last decades. However, a significant proportion of this information is characterised by not being tabulated and…

Information Retrieval · Computer Science 2025-05-02 Diego Alvarado-Maldonado , Blair Johnston , Cameron J. Brown

A search for the parameter constraint in the three-parameter empirical mass formula proposed recently for active neutrinos is described. Without any parameter constraint the formula is a formal transformation of three free parameters into…

High Energy Physics - Phenomenology · Physics 2007-05-23 Wojciech Krolikowski

The idea that we live in a Universe undergoing a period of acceleration is a strongly held notion in cosmology. As this can, potentially, be explained with a modification to General Relativity we look at current cosmological data with the…

Astrophysics · Physics 2010-11-11 Shaun A. Thomas , Filipe B. Abdalla , Jochen Weller

We show how the photon input parton distribution function (PDF) may be calculated with good accuracy, and used in an extended DGLAP global parton analysis in which the photon is treated as an additional point-like parton. The uncertainty of…

High Energy Physics - Phenomenology · Physics 2015-06-19 A. D. Martin , M. G. Ryskin

Natural language understanding (NLU) tasks face a non-trivial amount of ambiguous samples where veracity of their labels is debatable among annotators. NLU models should thus account for such ambiguity, but they approximate the human…

Computation and Language · Computer Science 2023-06-13 Hancheol Park , Jong C. Park

The advent of Industry 4.0 has precipitated the incorporation of Artificial Intelligence (AI) methods within industrial contexts, aiming to realize intelligent manufacturing, operation as well as maintenance, also known as industrial…

Machine Learning · Computer Science 2023-11-09 Chenwei Tang , Wenqiang Zhou , Dong Wang , Caiyang Yu , Zhenan He , Jizhe Zhou , Shudong Huang , Yi Gao , Jianming Chen , Wentao Feng , Jiancheng Lv

We examine current constraints on and the future sensitivity to the strength of couplings between quarks and neutrinos in the presence of a form factor generated from loop effects of hidden sector particles that interact with quarks via new…

High Energy Physics - Phenomenology · Physics 2019-01-17 Alakabha Datta , Bhaskar Dutta , Shu Liao , Danny Marfatia , Louis E. Strigari