parton distributions
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2022 ◽  
Vol 105 (1) ◽  
Author(s):  
A. Hannaford-Gunn ◽  
K. U. Can ◽  
R. Horsley ◽  
Y. Nakamura ◽  
H. Perlt ◽  
...  

2021 ◽  
Vol 104 (11) ◽  
Author(s):  
Lekha Adhikari ◽  
Chandan Mondal ◽  
Sreeraj Nair ◽  
Siqi Xu ◽  
Shaoyang Jia ◽  
...  

2021 ◽  
Vol 127 (23) ◽  
Author(s):  
P. C. Barry ◽  
Chueng-Ryong Ji ◽  
N. Sato ◽  
W. Melnitchouk ◽  

2021 ◽  
Vol 81 (11) ◽  
Author(s):  
M. Diehl ◽  
J. R. Gaunt ◽  
P. Pichini ◽  
P. Plößl

AbstractWe investigate the positivity of double parton distributions with a non-trivial dependence on the parton colour. It turns out that positivity is not preserved by leading-order evolution from lower to higher scales, in contrast to the case in which parton colour is summed over. We also study the positivity properties of the distributions at small distance between the two partons, where they can be computed in terms of perturbative splitting kernels and ordinary parton densities.


2021 ◽  
Vol 81 (11) ◽  
Author(s):  
Richard D. Ball ◽  
Stefano Forte ◽  
Roy Stegeman

AbstractWe study the correlation between different sets of parton distributions (PDFs). Specifically, viewing different PDF sets as distinct determinations, generally correlated, of the same underlying physical quantity, we examine the extent to which the correlation between them is due to the underlying data. We do this both for pairs of PDF sets determined using a given fixed methodology, and between sets determined using different methodologies. We show that correlations have a sizable component that is not due to the underlying data, because the data do not determine the PDFs uniquely. We show that the data-driven correlations can be used to assess the efficiency of methodologies used for PDF determination. We also show that the use of data-driven correlations for the combination of different PDFs into a joint set can lead to inconsistent results, and thus that the statistical combination used in constructing the widely used PDF4LHC15 PDF set remains the most reliable method.


2021 ◽  
Vol 2021 (11) ◽  
Author(s):  
K.B. Chen ◽  
J.P. Ma ◽  
X.B. Tong

Abstract In the target fragmentation region of Semi-Inclusive Deep Inelastic Scattering, the diffractively produced hadron has small transverse momentum. If it is at order of ΛQCD, it prevents to make predictions with the standard collinear factorization. However, in this case, differential cross-sections can be predicted by the factorization with fracture functions, diffractive parton distributions. If the transverse momentum is much larger than ΛQCD but much smaller than Q which is the virtuality of the virtual photon, both factorizations apply. In this case, fracture functions can be factorized with collinear parton distributions and fragmentation functions. We study the factorization up to twist-3 level and obtain gauge invariant results. They will be helpful for modeling fracture functions and useful for resummation of large logarithm of the transverse momentum appearing in collinear factorization.


2021 ◽  
Vol 121 ◽  
pp. 103908
Author(s):  
Martha Constantinou ◽  
Aurore Courtoy ◽  
Markus A. Ebert ◽  
Michael Engelhardt ◽  
Tommaso Giani ◽  
...  

2021 ◽  
Vol 2021 (11) ◽  
Author(s):  
Tianbo Liu ◽  
W. Melnitchouk ◽  
Jian-Wei Qiu ◽  
N. Sato

Abstract We present the details of a new factorized approach to semi-inclusive deep-inelastic scattering which treats QED and QCD radiation on equal footing, and provides a systematically improvable approximation to the extraction of transverse momentum dependent parton distributions. We demonstrate how the QED contributions can be well approximated by collinear factorization, and illustrate the application of the factorized approach to QED radiation in inclusive scattering. For semi-inclusive processes, we show how radiation effects prevent a well-defined “photon-nucleon” frame, forcing one to use a two-step process to account for the radiation. We illustrate the utility of the new method by explicit application to the spin-dependent Sivers and Collins asymmetries.


2021 ◽  
Vol 104 (7) ◽  
Author(s):  
Bheemsehan Gurjar ◽  
Dipankar Chakrabarti ◽  
Poonam Choudhary ◽  
Asmita Mukherjee ◽  
Pulak Talukdar

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