Inferring the initial condition for the Balitsky-Kovchegov equation
Casuga, C., Karhunen, M., & Mäntysaari, H. (2024). Inferring the initial condition for the Balitsky-Kovchegov equation. Physical Review D, 109(5), Article 054018. https://doi.org/10.1103/PhysRevD.109.054018
Julkaistu sarjassa
Physical Review DPäivämäärä
2024Tekijänoikeudet
© 2024 the Authors
We apply Bayesian inference to determine the posterior likelihood distribution for the parameters describing the initial condition of the small-x Balitsky-Kovchegov evolution equation at leading logarithmic accuracy. The HERA structure function data is found to constrain most of the model parameters well. In particular, we find that the HERA data prefers an anomalous dimension γ≈1 unlike in previous fits where γ>1 which led to e.g. the unintegrated gluon distribution and the quark-target cross sections not being positive definite. The determined posterior distribution can be used to propagate the uncertainties in the non-perturbative initial condition when calculating any other observable in the Color Glass Condensate framework. We demonstrate this explicitly for the inclusive quark production cross section in proton-proton collisions and by calculating predictions for the nuclear modification factor for the F2 structure function in the EIC and LHeC/FCC-he kinematics.
Julkaisija
American Physical Society (APS)ISSN Hae Julkaisufoorumista
2470-0010Asiasanat
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/213715336
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Rahoittaja(t)
Euroopan komissio; Suomen AkatemiaRahoitusohjelmat(t)
Akatemiatutkijan tutkimuskulut, SA; Akatemiatutkija, SA
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.
Lisätietoja rahoituksesta
H. M and C. C. are supported by the Research Council of Finland, the Centre of Excellence in Quark Matter and projects 338263 and 346567. C. C. also acknowledges the support of the Vilho, Yrjö, and Kalle Väisälä Foundation. This work was also supported under the European Union’s Horizon 2020 research and innovation programme by the European Research Council (ERC, Grant Agreement No. ERC-2018-ADG-835105 YoctoLHC) and by the STRONG-2020 project (Grant Agreement No. 824093). ...Lisenssi
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