Factorization of the soft gluon divergence from the dipole picture deep inelastic scattering cross sections at next-to-leading order
Ducloue, B.; Hänninen, H.; Lappi, T.; Zhu, Y. (2019). Factorization of the soft gluon divergence from the dipole picture deep inelastic scattering cross sections at next-to-leading order. In Hard Probes 2018 : Proceedings of the 9th International Conference on Hard and Electromagnetic Probes of High-Energy Nuclear Collisions, PoS : Proceedings of Science, 345. Sissa. DOI: 10.22323/1.345.0116
Published inPoS : Proceedings of Science
© the author(s) 2019
We use a factorization scheme, analogous to the one proposed for single inclusive forward hadron production in hadronic collisions, to regularize the soft gluon divergence present in the deep inelastic scattering (DIS) 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 Balitsky-Kovchegov (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 in hadronic collisions.
ConferenceInternational Conference on Hard and Electromagnetic Probes of High Energy Nuclear Collisions
Is part of publicationHard Probes 2018 : Proceedings of the 9th International Conference on Hard and Electromagnetic Probes of High-Energy Nuclear Collisions
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Related funder(s)Academy of Finland; European Commission
Funding 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 fundingThis work has been supported by the Academy of Finland, projects 273464 and 303756 and by the European Research Council, grant ERC-2015-CoG-681707.
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