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PreprintCC BY-NC-ND 4.0arXiv

CGC Fit to HERA DIS and Forward Hadron Production in p+p Collisions

Abstract

Many experiments have provided possible hints of gluon saturation, including geometric scaling in deep inelastic scattering (DIS) at HERA, the suppression of forward particle yields in d+Au collisions relative to p+p collisions at RHIC, and the suppression of away-side peaks in di-hadron correlations at forward rapidities in proton-nucleus collisions at RHIC and the LHC. Previous studies within the Color Glass Condensate (CGC) framework have primarily focused on fits to HERA deep inelastic scattering data, using the resulting dipole amplitudes to predict hadronic observables in proton-nucleus and proton-proton collisions. A simultaneous fit of DIS and forward particle production data, and a systematic study of their interplay, has so far been absent. In the work presented here, we focus on two processes: inclusive DIS and forward single inclusive hadron production in p+p collisions, incorporating data from HERA, RHIC, and the LHC. We solve the Balitsky-Kovchegov (BK) small-x evolution equation and perform a global fit to the combined datasets. Our analysis accounts for uncertainties in fragmentation functions and provides final uncertainties for the fitted parameters. The outcomes demonstrate the potential of the CGC formalism to provide a universal description of these diverse processes at the level of the dipole amplitude. In these proceedings, after very briefly summarizing the setup and our results, we highlight one particular aspect of the analysis, namely the complete uncertainty treatment. We validated the final uncertainties with two independent methods: the Hessian method and the Bayesian inference method, finding very good agreement.

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BibTeX
@misc{korcyl2026hera,
  title = {{CGC Fit to HERA DIS and Forward Hadron Production in p+p Collisions}},
  author = {Piotr Korcyl and Truong My Hau Le and Farid Salazar and Tomasz Stebel},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.37370},
  eprint = {2609.37370},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.37370},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - UNPB
TI  - CGC Fit to HERA DIS and Forward Hadron Production in p+p Collisions
AU  - Piotr Korcyl
AU  - Truong My Hau Le
AU  - Farid Salazar
AU  - Tomasz Stebel
PY  - 2026
DA  - 2026/09/29
PB  - arXiv
DO  - 10.48550/arxiv.2609.37370
UR  - https://arxiv.org/abs/2609.37370
AB  - Many experiments have provided possible hints of gluon saturation, including geometric scaling in deep inelastic scattering (DIS) at HERA, the suppression of forward particle yields in d+Au collisions relative to p+p collisions at RHIC, and the suppression of away-side peaks in di-hadron correlations at forward rapidities in proton-nucleus collisions at RHIC and the LHC. Previous studies within the Color Glass Condensate (CGC) framework have primarily focused on fits to HERA deep inelastic scattering data, using the resulting dipole amplitudes to predict hadronic observables in proton-nucleus and proton-proton collisions. A simultaneous fit of DIS and forward particle production data, and a systematic study of their interplay, has so far been absent. In the work presented here, we focus on two processes: inclusive DIS and forward single inclusive hadron production in p+p collisions, incorporating data from HERA, RHIC, and the LHC. We solve the Balitsky-Kovchegov (BK) small-x evolution equation and perform a global fit to the combined datasets. Our analysis accounts for uncertainties in fragmentation functions and provides final uncertainties for the fitted parameters. The outcomes demonstrate the potential of the CGC formalism to provide a universal description of these diverse processes at the level of the dipole amplitude. In these proceedings, after very briefly summarizing the setup and our results, we highlight one particular aspect of the analysis, namely the complete uncertainty treatment. We validated the final uncertainties with two independent methods: the Hessian method and the Bayesian inference method, finding very good agreement.
ER  -