Factorization of the soft gluon divergence from the dipole picture deep inelastic scattering cross sections at next-to-leading order
Ducloué, B., Hänninen, H., Lappi, T., & Zhu, Y. (2018). Factorization of the soft gluon divergence from the dipole picture deep inelastic scattering cross sections at next-to-leading order. In DIS 2018 : Proceedings of the XXVI International Workshop on Deep-Inelastic Scattering and Related Subjects (Article 058). Sissa. PoS : Proceedings of Science, 316. https://doi.org/10.22323/1.316.0058
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© the Author(s), 2018.
We use a factorization scheme analogous to one proposed for single inclusive forward hadron production to factorize the soft gluon divergence present in the deep inelastic scattering cross sections in the dipole picture at next-to-leading order (NLO). We show numerically that in this carefully constructed scheme it is possible to obtain meaningful results for the DIS cross sections at NLO, and so we are able to quantitatively study the recently derived NLO corrections to the DIS cross sections. We find that the NLO corrections can be significant and sensitive to the details of the factorization scheme used for the resummation of the large logarithms into the BK evolution equation. In the case of an approximative factorization scheme we observe a problematic behavior of the DIS cross sections similar to what has been seen with analogously factorized single inclusive cross sections.
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International Workshop on Deep-Inelastic Scattering and Related SubjectsIs part of publication
DIS 2018 : Proceedings of the XXVI International Workshop on Deep-Inelastic Scattering and Related SubjectsISSN Search the Publication Forum
1824-8039Publication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/28805795
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European Commission; Academy of FinlandFunding program(s)
Research costs of Academy Research Fellow, 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 has been supported by the Academy of Finland, projects 273464 and 303756 and by the European Research Council, grant ERC-2015-CoG-681707.License
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