Dipole model at Next-to-Leading Order meets HERA data
Beuf, G., Hänninen, H., Lappi, T., & Mäntysaari, H. (2021). Dipole model at Next-to-Leading Order meets HERA data. In HardProbes2020 : 10th International Conference on Hard and Electromagnetic Probes of High-Energy Nuclear Collisions (Article 101). Sissa Medialab. POS Proceedings of Science, 387. https://doi.org/10.22323/1.387.0101
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2021Copyright
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Deep inelastic scattering (DIS) total cross section data at small-x as measured by the HERA experiments is well described by Balitsky-Kovchegov (BK) evolution in the leading order dipole picture. Recently the full Next-to-Leading Order (NLO) dipole picture total cross sections have become available for DIS, and a working factorization scheme has been devised which subtracts the soft gluon divergence present at NLO.
We report our recently published work in which we make the first comparisons of the NLO DIS total cross sections to HERA data. The non-perturbative initial condition to BK evolution is fixed by fitting the HERA reduced cross section data. As the NLO results for the DIS total cross section are currently available only in the massless quark limit, we also fit a light-quark-only cross section constructed with a parametrization of published total and heavy quark data. We find an excellent description of the HERA data. Since the full NLO BK equation is computationally expensive, we use a number of beyond LO prescriptions for the evolution that include most important higher order corrections enhanced by large transverse logarithms, including the recent version of the equation formulated in terms of the target momentum fraction.
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Sissa MedialabConference
International Conference on Hard and Electromagnetic Probes of High-Energy Nuclear CollisionsIs part of publication
HardProbes2020 : 10th International Conference on Hard and Electromagnetic Probes of High-Energy Nuclear CollisionsISSN Search the Publication Forum
1824-8039Keywords
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https://converis.jyu.fi/converis/portal/detail/Publication/101765391
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Academy of Finland; European CommissionFunding program(s)
Postdoctoral Researcher, AoF; Academy Project, AoF


The content of the publication reflects only the author’s view. The funder is not responsible for any use that may be made of the information it contains.
Additional information about funding
This work was supported by the Academy of Finland, projects 314764 (H.M) and 321840 (T.L). G.B, H.H and T.L are supported by the European Research Council grant ERC-2015-CoG-681707. Computing resources from CSC – IT Center for Science in Espoo, Finland and from the FGCI (persistent identifier urn:nbn:fi:research-infras-2016072533) were used.License
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