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Bayesian inference of the fluctuating proton shape

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arxiv 2202.01998 v1 pith:KNLSFYTJ submitted 2022-02-04 hep-ph nucl-th

classification hep-phnucl-th
keywords datafluctuatingstructurealongbayesiancollisionsconstrainexperimental
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

Using Bayesian inference, we determine probabilistic constraints on the parameters describing the fluctuating structure of protons at high energy. We employ the color glass condensate framework supplemented with a model for the spatial structure of the proton, along with experimental data from the ZEUS and H1 Collaborations on coherent and incoherent diffractive $\mathrm{J}/\psi$ production in e+p collisions at HERA. This data is found to constrain most model parameters well. This work sets the stage for future global analyses, including experimental data from e+p, p+p, and p+A collisions, to constrain the fluctuating structure of nucleons along with properties of the final state.

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Forward citations

Cited by 5 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

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  3. Exclusive $\mathrm{J}/\psi$ production off a dilute proton within a refined hotspot description

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    A hot-spot model with saturation-scale and hotspot-number fluctuations plus a relativistic wave-function correction reproduces HERA exclusive J/psi data, with saturation-scale fluctuations dominating.

  4. Bayesian analysis of properties of nuclear matter with the FOPI experimental data

    nucl-th 2025-09 conditional novelty 6.0 of 10

    Bayesian fits to FOPI Au+Au flow and stopping data yield m*/m0 around 0.78-0.88 and F around 0.75-0.88, while K0 remains unconstrained.

  5. Collision energy dependence in heavy ion collisions from nonlinear QCD evolution

    nucl-th 2025-02 conditional novelty 6.0 of 10

    JIMWLK evolution of the nuclear initial state flattens the centrality dependence of multiplicity and lowers mean transverse momentum, improving data agreement at LHC energies.

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