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Multi-source stationary computed tomography (MSS-CT) offers significant advantages in medical and industrial applications due to its gantry-less scan architecture and/or capability of simultaneous multi-source emission. However, the lack of…

Medical Physics · Physics 2025-01-20 Yingxian Xia , Zhiqiang Chen , Li Zhang , Yuxiang Xing , Hewei Gao

We address the question of interpolation of the virtual Compton scattering process off a polarized nucleon target between the deeply virtual regime for the initial-state photon and its near on-shell kinematics making use of the photon…

High Energy Physics - Phenomenology · Physics 2014-01-30 Andrei V. Belitsky , Dieter Mueller , Yao Ji

Deep learning has emerged as a technique of choice for rapid feature extraction across imaging disciplines, allowing rapid conversion of the data streams to spatial or spatiotemporal arrays of features of interest. However, applications of…

Data Analysis, Statistics and Probability · Physics 2021-01-25 Ayana Ghosh , Bobby G. Sumpter , Ondrej Dyck , Sergei V. Kalinin , Maxim Ziatdinov

This work is directed to uncertainty quantification of homogenized effective properties for composite materials with complex, three dimensional microstructure. The uncertainties arise in the material parameters of the single constituents as…

Machine Learning · Computer Science 2021-10-27 Alexander Henkes , Ismail Caylak , Rolf Mahnken

Disentangling coherent and incoherent effects in the photoemission spectra of strongly correlated materials is generally a challenging problem due to the involvement of numerous parameters. In this study, we employ machine learning…

Superconductivity · Physics 2024-12-17 K. H. Bohachov , A. A. Kordyuk

The key reactions to study the Generalised Parton Distributions are Deeply Virtual Compton Scattering (DVCS) and Deeply Virtual Meson Production (DVMP). At COMPASS, these processes are investigated using a high intensity muon beam with a…

High Energy Physics - Experiment · Physics 2017-02-22 P. Joerg

We carry out the first complete calculation of kinematic power corrections $\sim t/Q^2$ and $\sim m^2/Q^2$ to several key observables in Deeply Virtual Compton Scattering. The issue of convention dependence of the leading twist…

High Energy Physics - Phenomenology · Physics 2014-04-23 Vladimir M. Braun , Alexander N. Manashov , Dieter Mueller , Bjoern M. Pirnay

Recent results on the Deeply Virtual Compton Scattering (DVCS) and prompt photon productions from H1 and ZEUS experiments on the $ep$ collider HERA are presented. A new DVCS cross section measurements of the H1 Collaboration, for photon…

High Energy Physics - Experiment · Physics 2007-05-23 L. Favart

We introduce the study of neutrino scattering off protons in the deeply virtual kinematics, which describes under a unified formalism elastic and deep inelastic neutrino scattering. A real final state photon and a recoiling nucleon are…

High Energy Physics - Phenomenology · Physics 2008-11-26 Paolo Amore , Claudio Coriano' , Marco Guzzi

We propose a novel study of generating unseen arbitrary viewpoints for infrared imagery in the non-linear feature subspace . Current methods use synthetic images and often result in blurry and distorted outputs. Our approach on the contrary…

Computer Vision and Pattern Recognition · Computer Science 2020-08-19 Maliha Arif , Abhijit Mahalanobis

After about 10 years of growing interest for Generalized Parton Distributions come the first results from dedicated experiments, using the golden Deeply Virtual Compton Scattering process. After a short introduction, we will explain the…

Nuclear Experiment · Physics 2009-09-24 F. Sabatie

The extraction of Compton Form Factors (CFFs) in a global analysis of almost all Deeply Virtual Compton Scattering (DVCS) proton data is presented. The extracted quantities are DVCS sub-amplitudes and the most basic observables which are…

High Energy Physics - Phenomenology · Physics 2019-07-25 H. Moutarde , P. Sznajder , J. Wagner

The interpretability of neural networks has recently received extensive attention. Previous prototype-based explainable networks involved prototype activation in both reasoning and interpretation processes, requiring specific explainable…

Computer Vision and Pattern Recognition · Computer Science 2022-11-22 Yitao Peng , Yihang Liu , Longzhen Yang , Lianghua He

Nowadays, deep learning methods, especially the convolutional neural networks (CNNs), have shown impressive performance on extracting abstract and high-level features from the hyperspectral image. However, general training process of CNNs…

Computer Vision and Pattern Recognition · Computer Science 2020-03-12 Zhiqiang Gong , Ping Zhong , Weidong Hu

Over the past two decades, intense experimental efforts have focused on measuring observables that contribute to a three-dimensional description of the nucleon. Generalized Parton Distributions provide complementary insights into the…

Nuclear Experiment · Physics 2025-09-24 L. Calero Diaz , D. Keller

Insufficient overlap between the melt pools produced during Laser Powder Bed Fusion (L-PBF) can lead to lack-of-fusion defects and deteriorated mechanical and fatigue performance. In-situ monitoring of the melt pool subsurface morphology…

At the extreme energies of the Large Hadron Collider, massive particles can be produced at such high velocities that their hadronic decays are collimated and the resulting jets overlap. Deducing whether the substructure of an observed jet…

High Energy Physics - Experiment · Physics 2016-06-01 Pierre Baldi , Kevin Bauer , Clara Eng , Peter Sadowski , Daniel Whiteson

We investigate the extension of the deeply virtual Compton scattering process into the weak interaction sector.

High Energy Physics - Phenomenology · Physics 2014-11-18 Ales Psaker

Many phenomena taking place in the solar photosphere are controlled by plasma motions. Although the line-of-sight component of the velocity can be estimated using the Doppler effect, we do not have direct spectroscopic access to the…

Solar and Stellar Astrophysics · Physics 2017-08-02 A. Asensio Ramos , I. S. Requerey , N. Vitas

Explainable Artificial Intelligence (xAI) has the potential to enhance the transparency and trust of AI-based systems. Although accurate predictions can be made using Deep Neural Networks (DNNs), the process used to arrive at such…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Bhushan Atote , Victor Sanchez