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arxiv: 2410.23469 · v2 · pith:IS4BWP5N · submitted 2024-10-30 · hep-ph

Likelihood and Correlation Analysis of Compton Form Factors for Deeply Virtual Exclusive Scattering on the Nucleon

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classification hep-ph
keywords comptondeeplylikelihoodunpolarizedvirtualanalysisfactorsform
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A likelihood analysis of the observables in deeply virtual exclusive photoproduction off a proton target, $ep \rightarrow e' p' \gamma'$, is presented. Two processes contribute to the reaction: deeply virtual Compton scattering, where the photon is produced at the proton vertex, and the Bether-Heitler process, where the photon is radiated from the electron. We consider the unpolarized process for which the largest amount of data with all the kinematic dependences are available from corresponding datasets with unpolarized beams and unpolarized targets from Jefferson Lab. We provide and use a method which derives a joint likelihood of the Compton form factors, which parametrize the deeply virtual Compton scattering amplitude in QCD, for each observed combination of the kinematic variables defining the reaction. The unpolarized twist-two cross section likelihood fully constrains only three of the Compton form factors (CFFs). The impact of the twist-three corrections to the analysis is also explored. The derived likelihoods are explored using Markov chain Monte Carlo (MCMC) methods. Using our proposed method we derive CFF error bars and covariances. Additionally, we explore methods which may reduce the magnitude of error bars/contours in the future.

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Cited by 2 Pith papers

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

  1. Constraining DVCS Compton Form Factors Using Lattice QCD informed Neural Network

    hep-ph 2026-06 unverdicted novelty 5.0

    A neural network framework informed by lattice QCD uses all-order dispersion relations to significantly constrain both real and imaginary parts of Compton Form Factors extracted from DVCS proton data.

  2. Markov chain Monte Carlo (MCMC) based Likelihood Extraction of Chiral-Odd Compton Form Factors from Deeply Virtual Exclusive Experiments

    hep-ph 2026-05 unverdicted novelty 4.0

    MCMC-based joint likelihood extraction constrains chiral-odd CFFs from DVMP cross-sections and asymmetries.