2021
DOI: 10.48550/arxiv.2108.11493
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Valence quark ratio in the proton

Zhu-Fang Cui,
Fei Gao,
Daniele Binosi
et al.

Abstract: Beginning with precise data on the ratio of structure functions in deep inelastic scattering (DIS) from 3 He and 3 H, collected on the domain 0.19 ≤ xB ≤ 0.83, where xB is the Bjorken scaling variable, we employ a robust method for extrapolating such data to arrive at a model-independent result for the xB = 1 value of the ratio of neutron and proton structure functions. Combining this with information obtained in analyses of DIS from nuclei, corrected for target-structure dependence, we arrive at a prediction … Show more

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citations
Cited by 4 publications
(5 citation statements)
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“…Consistent with the analysis in Ref. [72], the calculated result agrees well with the data, which is thus seen to strongly disfavour a proton wave function that is based solely on scalar diquark correlations, i.e., excludes pseudovector diquarks.…”
supporting
confidence: 88%
See 1 more Smart Citation
“…Consistent with the analysis in Ref. [72], the calculated result agrees well with the data, which is thus seen to strongly disfavour a proton wave function that is based solely on scalar diquark correlations, i.e., excludes pseudovector diquarks.…”
supporting
confidence: 88%
“…The r 10 range was chosen such that the band of values matches that extracted [72] from contemporary experiment [34,MARATHON] and data analyses [73]. The band in Eq.…”
mentioning
confidence: 99%
“…The ζ = ζ 3 prediction is drawn in Fig.4B: in comparison with modern data[69, MARATHON], it yields χ 2 /degree-of-freedom = 1.3. Notably, both data and calculation indicate the presence of a significant axial-vector diquark component in the proton wave function[83,84].…”
mentioning
confidence: 94%
“…[33,34] and now often described as the statistical SPM, it has been honed in hadron physics applications, especially those which require interpolation and reliable extrapolation, e.g., Refs. [48][49][50][51][52][53][54]. The SPM builds form-unbiased interpolations of data as the foundation for well constrained extrapolations.…”
mentioning
confidence: 99%