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The deconvolution problem of deeply virtual Compton scattering

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arxiv 2104.03836 v1 pith:2Y4D6KNW submitted 2021-04-08 hep-ph hep-exhep-latnucl-exnucl-th

classification hep-phhep-exhep-latnucl-exnucl-th
keywords distributionsgeneralisedpartonanalysiscomptondeconvolutiondeeplymeasurements
verification ladder T0 review T1 audit T2 compute T3 formal
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Generalised parton distributions are instrumental to study both the three-dimensional structure and the energy-momentum tensor of the nucleon, and motivate numerous experimental programmes involving hard exclusive measurements. Based on a next-to-leading order analysis and a careful study of evolution effects, we exhibit non-trivial generalised parton distributions with arbitrarily small imprints on deeply virtual Compton scattering observables. This means that in practice the reconstruction of generalised parton distributions from measurements, known as the deconvolution problem, does not possess a unique solution for this channel. In this Letter we discuss the consequences on the extraction of generalised parton distributions from data and advocate for a multi-channel analysis.

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Cited by 4 Pith papers

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

  1. GUMP1.0 -- First global extraction of generalized parton distributions from experiment and lattice data with NLO accuracy

    hep-ph 2025-09 conditional novelty 6.0 of 10

    A new global extraction, GUMP1.0, fits generalized parton distributions to 2,646 experimental and lattice data points at NLO accuracy and uses them to image the proton and decompose its spin.

  2. Assessing the impact of the electron ion collider in China on Deeply Virtual Compton Scattering

    hep-ph 2025-12 conditional novelty 5.0 of 10

    Projected EicC DVCS asymmetry data would substantially reduce uncertainties on all leading-order Compton form factors, most strongly in the sea-quark region.

  3. Toward an event-level analysis of hadron structure using differential programming

    hep-ph 2025-07 conditional novelty 4.0 of 10

    LOITS is a differentiable sampling method, demonstrated in a GAN closure test, that maps sampled events back to the parameters of a target density for event-level inference.

  4. Three-dimensional imaging of hadrons with hard exclusive reactions: advances in experiment, theory, phenomenology, and lattice QCD

    hep-ph 2025-12 unverdicted novelty 2.0 of 10

    A community white paper reviewing GPD-based 3D imaging of hadrons — experiment, theory, phenomenology, lattice QCD — and the roadmap toward precision tomography at JLab, COMPASS, J-PARC, and future electron-ion colliders.

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