相关论文: Deep Inelastic Structure Functions in Bag-Like Mod…

Deep unrolling is an emerging deep learning-based image reconstruction methodology that bridges the gap between model-based and purely deep learning-based image reconstruction methods. Although deep unrolling methods achieve…

A theoretical approach to the investigation of spin-dependent structure functions in deep inelastic scattering of polarized leptons off polarized nuclei, based on the effective meson-nucleon theory and operator product expansion method, is…

We discuss the role of the U(1) axial anomaly in the spin structure functions of the nucleon, with particular emphasis on how one might determine its x dependence in present and future deep inelastic scattering experiments. We focus on the…

We study the proton structure functions $F_1$ and $F_2$ in the context of holography. We develop a general framework that extends previous holographic calculations of $F_1$ and $F_2$ to the case where the bulk geometry stems from bottom-up…

We present an improved method for handling off-shell effects in deep inelastic nuclear scattering. With a firm understanding of the effects of the nuclear wave function, including these off-shell corrections as well as binding and…

Soft-collinear effective theory (SCET) is used to sum Sudakov double-logarithms in the x ->1 endpoint region for the deep inelastic scattering structure function. The calculations are done in both the target rest frame and the Breit frame.…

We investigate deep inelastic scattering off the polarized "neutron" using gauge/string duality. The "neutron" corresponds to a supergravity mode of the neutral dilatino. Through introducing the Pauli interaction term into the action in…

Surface reconstruction is a vital tool in a wide range of areas of medical image analysis and clinical research. Despite the fact that many methods have proposed solutions to the reconstruction problem, most, due to their deterministic…

Density-functional theory is a formally exact description of a many-body quantum system in terms of its density; in practice, however, approximations to the universal density functional are required. In this work, a model based on deep…

Given a set of inelastic material models, a microstructure, a macroscopic structural geometry, and a set of boundary conditions, one can in principle always solve the governing equations to determine the system's mechanical response.…

Deep inelastic structure functions for the nucleon are obtained in a constituent quark model on the light cone. In the Bjorken limit the parton model is derived. Structure functions from the hadronic tensor at the scale $\mu \sim 0.25$ GeV…

Deep Learning (DL) algorithms hold great promise for applications in the field of computational biophysics. In fact, the vast amount of available molecular structures, as well as their notable complexity, constitutes an ideal context in…

The $n$-th moments of the nuclear structure function $F_2^A(x,Q^2)$ are analyzed using the off-shell kinematics appropriate to describe deep inelastic electron-nucleus scattering within the impulse approximation. It is shown that off-shell…

We introduce a novel generative formulation of deep probabilistic models implementing "soft" constraints on their function dynamics. In particular, we develop a flexible methodological framework where the modeled functions and derivatives…

Higher twist effects in the deeply inelastic scattering are studied. We start with a short review of the theoretical results on higher twists in QCD. Within the saturation model we perform a twist analysis of the nucleon structure functions…

The Bloom-Gilman local duality of the inelastic structure function of the proton, the deuteron and light complex nuclei is investigated using available experimental data in the squared four-momentum transfer range from 0.3 to 5 (GeV/c)**2.…

We study the convergence of the series expansions sometimes used in the analysis of the nuclear effects in Deep Inelastic Scattering (DIS) proccesses induced by leptons. The recent advances in statistics and quality of the data, in…

We calculate the spin dependent structure functions g1(x) and g2(x) of the proton and neutron. Our calculation uses the meson cloud model of nucleon structure and includes the effects of kinematic terms which mix transverse and longitudinal…

Structure Functions for small DIS (deep inelastic scattering) $x$ for integrable models are investigated, in particular, for the $O(N)$~$\sigma $-model and $SU(N)$ chiral Gross-Neveu model, which are asymptotically free. We get the…

Status, open questions, and future prospects of the physics of excited nucleons are discussed. Emphasis is on the study of the structure of nucleons via measurements of their electromagnetic transition form factors, the search for "missing"…