Related papers: Impact parameter model for GPD
We discuss the use of machine learning techniques in effectively nonparametric modelling of generalised parton distributions (GPDs) in view of their future extraction from experimental data. Current parameterisations of GPDs suffer from…
We give a brief overview on the theory and phenomenology of generalized parton distributions (GPDs), including the recently developed framework of single-diffractive hard exclusive process for matching GPDs to experimental observables. We…
An integral representation is suggested for generalized parton distributions which automatically satisfies the polynomiality and positivity constraints. This representation has the form of an integral of perturbative triangle diagrams over…
Results from a recent analysis of the zero-skewness generalized parton distributions (GPDs) for valence quarks are discussed. The analysis bases on a physically motivated parameterization of the GPDs with a few free parameters adjusted to…
For an unpolarized target, the generalized parton distribution $H_q(x,0,t)$ is related to the distribution of partons in impact parameter space. The transverse distortion of this distribution for a transversely polarized target is described…
An approach is proposed to calculate Generalized Parton Distributions (GPDs) in a Constituent Quark Model (CQM) scenario. These off-diagonal distributions are obtained from momentum space wave functions to be evaluated in a given non…
The operator definition of generalised transverse-momentum-dependent (GTMD) distributions is exploited to compute for the first time the full set of one-loop corrections to the off-forward matching functions. These functions allow one to…
The $t$-dependence of generalized parton distrbutions for $x\to 1$ is discussed. We argue that constituent quark models, where the $t$-dependence for $x\to 1$ is through the product $(1-x)t$, are inconsistent. Instead we suggest a leading…
We investigate the generalized parton distributions (GPDs) for u and d quarks in a proton in transverse and longitudinal position space using a recent phenomenological parametrization. We take nonzero skewness \zeta and consider the region…
Generalized parton distribution functions (GPDs) of spin-3/2 particles are defined for the first time in this paper. Eight unpolarized and eight polarized GPDs are found. In the forward limit of GPDs, the structure functions and parton…
An approach is described to calculate Generalized Parton Distributions (GPDs) in Constituent Quark Models (CQM). The GPDs are obtained from wave functions to be evaluated in a given CQM. The general relations linking the twist-two GPDs to…
Applications of perturbative QCD to deeply virtual Compton scattering and hard exclusive electroproduction processes require a generalization of the usual parton distributions for the case when long-distance information is accumulated in…
Generalized parton distributions can be used to obtain information about the dependence of parton distributions on the impact parameter. Potential consequences for T-odd single-spin asymmetries are discussed.
The isoscalar twist-two generalized parton distributions (GPDs) of the pion and the kaon are calculated in a Poincare covariant Bethe-Salpeter constituent quark model. Results are presented for several values of the parameters xi and t. The…
We propose a physically motivated parametrization for the unpolarized generalized parton distributions. At zero value of the skewness variable, $\zeta$, the parametrization is constrained by simultaneously fitting the experimental data on…
In recent years, there has been a breakthrough in lattice calculations of $x$-dependent partonic distributions. This encompasses also distributions describing the 3D structure of the nucleon, such as generalized parton distributions (GPDs).…
We present a numerical analysis of helicity independent nucleon generalized parton distributions (GPDs) using the known formalism based on inclusion of higher Fock states in the soft-wall approach of the anti-de Sitter/QCD model. We…
This paper presents foundational theoretical results on distributed parameter estimation for undirected probabilistic graphical models. It introduces a general condition on composite likelihood decompositions of these models which…
The classical approach to analyzing extreme value data is the generalized Pareto distribution (GPD). When the GPD is used to explain a target variable with the large dimension of covariates, the shape and scale function of covariates…
We present an exploration of the unpolarized isovector proton generalized parton distributions (GPDs) $H^{u-d}(x, \xi, t)$ and $E^{u-d}(x, \xi, t)$ in the pseudo-distribution formalism using distillation. Taking advantage of the large…