2022
DOI: 10.1007/jhep06(2022)007
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Factorization for azimuthal asymmetries in SIDIS at next-to-leading power

Abstract: Differential measurements of the semi-inclusive deep inelastic scattering (SIDIS) process with polarized beams provide important information on the three-dimensional structure of hadrons. Among the various observables are azimuthal asymmetries that start at subleading power, and which give access to novel transverse momentum dependent distributions (TMDs). Theoretical predictions for these distributions are currently based on the parton model rather than a rigorous factorization based analysis. Working under t… Show more

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Cited by 27 publications
(12 citation statements)
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“…This is a natural consequence of the NLP TMD factorization theory being at its earlier stage of development. The first convincing studies appeared only recently [6][7][8][9][10]. Further progress in this direction requires the systematization of knowledge about TMD distributions of twist-three, which we present in this paper.…”
Section: Jhep08(2022)031 1 Introductionmentioning
confidence: 90%
See 2 more Smart Citations
“…This is a natural consequence of the NLP TMD factorization theory being at its earlier stage of development. The first convincing studies appeared only recently [6][7][8][9][10]. Further progress in this direction requires the systematization of knowledge about TMD distributions of twist-three, which we present in this paper.…”
Section: Jhep08(2022)031 1 Introductionmentioning
confidence: 90%
“…The same consideration gives rise to the partonic interpretation for correlators, as the probability of emission (for x > 0) and absorption (for x < 0) of partons in the 5 In works [10,38], an alternative two-variable notation is used with x being the (positive) momentum fraction of a single parton, and ξ being imbalance of momentum fractions in the quark-gluon pair. Such as,…”
Section: Definition and Support Propertiesmentioning
confidence: 99%
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“…• The rapidity divergences of TMD operator and Ψ-functions are canceled by the soft factor S(y) (3.8). At LP and NLP the soft factor is ordinary TMD soft factor [32]. The cancellation of rapidity divergences for NLP operators has been demonstrated explicitly at NLO in ref.…”
Section: Factorization Theorem In the Physical Formmentioning
confidence: 80%
“…The first steps were made in ref. [27], but the systematic development started almost twenty years later [28][29][30][31][32][33]. Still, many aspects of the NLP TMD factorization beyond leading perturbative order (LO) are mysterious.…”
Section: Introductionmentioning
confidence: 99%