Unbiased determination of DVCS Compton form factors

Moutarde, H.; Sznajder, P.; Wagner, J.

doi:10.1140/epjc/s10052-019-7117-5

Cited by 65 publications

(63 citation statements)

References 53 publications

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“…[108] canvassed in Refs. [109,110], profiles analogous to Fig. 4 -upper panel for neutron stars indicate r 0 pressures therein of roughly 0.1 GeV/fm [111]; hence, the core pressures in the pion and neutron stars are commensurate.…”

Section: Vector Gpd: Imagesmentioning

confidence: 76%

Contact interaction analysis of pion GTMDs

et al. 2021

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A contact interaction is used to calculate an array of pion twist-two, -three and -four generalised transverse light-front momentum dependent parton distribution functions (GTMDs). Despite the interaction’s simplicity, many of the results are physically relevant, amongst them a statement that GTMD size and shape are largely prescribed by the scale of emergent hadronic mass. Moreover, proceeding from GTMDs to generalised parton distributions, it is found that the pion’s mass distribution form factor is harder than its electromagnetic form factor, which is harder than the gravitational pressure distribution form factor; the pressure in the neighbourhood of the pion’s core is commensurate with that at the centre of a neutron star; the shear pressure is maximal when confinement forces become dominant within the pion; and the spatial distribution of transversely polarised quarks within the pion is asymmetric. Regarding transverse momentum dependent distribution functions, their magnitude and domain of material support decrease with increasing twist. The simplest Wigner distribution associated with the pion’s twist-two dressed-quark GTMD is sharply peaked on the kinematic domain associated with valence-quark dominance; has a domain of negative support; and broadens as the transverse position variable increases in magnitude.

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Section: Vector Gpd: Imagesmentioning

confidence: 76%

Contact interaction analysis of pion GTMDs

et al. 2021

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“…In Ref. [52], 30 distinct DVCS observables spread over 2500 kinematic configurations and collected over 17 years were jointly analysed in terms of CFFs relying on a neural network approach. In this study the real and imaginary parts of each CFF were independently described and simultaneously fitted to experimental data.…”

Section: Input From Global Fits To Dvcs Datamentioning

confidence: 99%

“…Here, each replica is a function of the three variables ξ , t and Q 2 , and represents a single neural network built of (i) three input neurons receiving the values of ξ , t and Q 2 , (ii) one hidden layer with six neurons, and (iii) one output neuron returning either the real or imaginary part of the CFF H. The parameters of this function, which are weights and biases "trained" to the experimental data, are real numbers (for details see Ref. [52]). Those numbers are not intuitive in the sense that they do not carry any physical meaningthey are not "human readable" or interpretable.…”

Section: Input From Global Fits To Dvcs Datamentioning

confidence: 99%

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Phenomenological assessment of proton mechanical properties from deeply virtual Compton scattering

et al. 2021

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A unique feature of generalised parton distributions is their relation to the QCD energy–momentum tensor. In particular, they provide access to the mechanical properties of the proton i.e. the distributions of pressure and shear stress induced by its quark and gluon structure. In principle the pressure distribution can be experimentally determined in a model-independent way from a dispersive analysis of deeply virtual Compton scattering data through the measurement of the subtraction constant. In practice the kinematic coverage and accuracy of existing experimental data make this endeavour a challenge. Elaborating on recent global fits of deeply virtual Compton scattering measurements using artificial neural networks, our analysis presents the current knowledge on this subtraction constant and assesses the impact of the most frequent systematic assumptions made in this field of research. This study will pave the way for future works when more precise data will become available, e.g. obtained in the foreseen electron-ion colliders EIC and EIcC.

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“…The extensive global effort to measure DVCS in various kinematic domains and for various combinations of charges and polarizations of beams and targets, gave so far about 30 observables collected over more than 2500 kinematic configurations. All these data, which were published over 17 years, were recently used in state-of-the-art global fits [15,16] based on the open-source PARTONS framework [17], which provides a homogeneous computational environment for all kind of GPD studies.…”

Section: Introductionmentioning

confidence: 99%

Data-driven study of timelike Compton scattering

et al. 2020

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In the framework of collinear QCD factorization, the leading twist scattering amplitudes for deeply virtual Compton scattering (DVCS) and timelike Compton scattering (TCS) are intimately related thanks to analytic properties of leading and next-to-leading order amplitudes. We exploit this welcome feature to make datadriven predictions for TCS observables to be measured in near future experiments. Using a recent extraction of DVCS Compton form factors from most of the existing experimental data for that process, we derive TCS amplitudes and calculate TCS observables only assuming leading-twist dominance. Artificial neural network techniques are used for an essential reduction of model dependency, while a careful propagation of experimental uncertainties is achieved with replica methods. Our analysis allows for stringent tests of the leading twist dominance of DVCS and TCS amplitudes. Moreover, this study helps to understand quantitatively the complementarity of DVCS and TCS measurements to test the universality of generalized parton distributions, which is crucial e.g. to perform the nucleon tomography.

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Unbiased determination of DVCS Compton form factors

Cited by 65 publications

References 53 publications

Contact interaction analysis of pion GTMDs

Contact interaction analysis of pion GTMDs

Phenomenological assessment of proton mechanical properties from deeply virtual Compton scattering

Data-driven study of timelike Compton scattering

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