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Diffusion models (DMs) have emerged as powerful tools for modeling complex data distributions and generating realistic new samples. Over the years, advanced architectures and sampling methods have been developed to make these models…

Machine Learning · Computer Science 2025-12-11 Roi Benita , Michael Elad , Joseph Keshet

The goal of this study is to determine a set of diffractive parton distribution function (diffractive PDFs) from a QCD analysis of all available and up-to-date diffractive deep inelastic scattering (diffractive DIS) data sets from HERA $ep$…

High Energy Physics - Phenomenology · Physics 2019-04-02 Hamzeh Khanpour

We apply a pulsed-light interferometer to measure both the intensity and the phase of light that is transmitted through a strongly scattering disordered material. From a single set of measurements we obtain the time-resolved intensity,…

Disordered Systems and Neural Networks · Physics 2009-11-10 I. M. Vellekoop , P. Lodahl , A. Lagendijk

Predictions for deep Virtual Compton Scattering are obtained in a two-component dipole model of diffraction. The model automatically includes hard and soft components and implicitly allows for ``hadronic'' contributions via large dipoles.…

High Energy Physics - Phenomenology · Physics 2008-11-26 A Donnachie , H G Dosch

The current analysis aims to present the results of a QCD analysis of diffractive parton distribution functions (diffractive PDFs) at next-to-leading order (NLO) accuracy in perturbative QCD. In this new determination of diffractive PDFs,…

High Energy Physics - Phenomenology · Physics 2019-09-20 Atefeh Maktoubian , Hossein Mehraban , Hamzeh Khanpour , Muhammad Goharipour

Calculus and geometry are ubiquitous in the theoretical modelling of scientific phenomena, but have historically been very challenging to apply directly to real data as statistics. Diffusion geometry is a new theory that reformulates…

Differential Geometry · Mathematics 2026-02-09 Iolo Jones , David Lanners

We present a simplified model for dynamical diffraction of particles through a periodic thick perfect crystal based on repeated application of a coherent beam splitting unitary at coarse-grained lattice sites. By demanding translational…

Quantum Physics · Physics 2016-12-14 J. Nsofini , K. Ghofrani , D. Sarenac , D. G. Cory , D. A. Pushin

We consider the problem of elastic diffraction tomography, which consists in reconstructing elastic properties (i.e. mass density and elastic Lam\'e parameters) of a weakly scattering medium from full-field data of scattered waves outside…

Analysis of PDEs · Mathematics 2022-12-07 Bochra Mejri , Otmar Scherzer

A measurement is presented, using data taken with the H1 detector at HERA, of the contribution of diffractive interactions to deep-inelastic electron-proton scattering. The diffractive contribution to the proton structure function is…

High Energy Physics - Experiment · Physics 2016-08-31 H1-Collaboration

A growing number of shock compression experiments, especially those involving laser compression, are taking advantage of in situ x-ray diffraction as a tool to interrogate structure and microstructure evolution. Although these experiments…

It is argued that the breakdown of factorization observed recently in the diffractive dijet production in deep inelastic lepton induced and hadron induced processes is naturally explained in the Good-Walker picture of diffraction…

High Energy Physics - Phenomenology · Physics 2007-05-23 A. Bialas

Diffusion in a multidimensional energy surface with minima and barriers is a problem of importance in statistical mechanics and also has wide applications, such as protein folding. To understand it in such a system, we carry out theory and…

Statistical Mechanics · Physics 2022-06-29 Subhajit Acharya , Biman Bagchi

Diffraction patterns produced by fast He atoms grazingly impinging on a LiF(001) surface are investigated focusing on the influence of the beam collimation. Single- and double- slit collimating devices situated in front of the beam source…

Atomic Physics · Physics 2016-09-21 M. S. Gravielle , J. E. Miraglia

A dynamic diffraction theory is developed for describing electron diffraction by dielectric crystals in a strong electromagnetic field. It is shown that additional diffraction maxima arise in an electromagnetic field, their intensity…

Atomic Physics · Physics 2018-02-15 Yulian Shabolovski

We aim to leverage diffusion to address the challenging image matting task. However, the presence of high computational overhead and the inconsistency of noise sampling between the training and inference processes pose significant obstacles…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Yihan Hu , Yiheng Lin , Wei Wang , Yao Zhao , Yunchao Wei , Humphrey Shi

Discovering crystal structures with specific chemical properties has become an increasingly important focus in material science. However, current models are limited in their ability to generate new crystal lattices, as they only consider…

Materials Science · Physics 2024-01-12 Astrid Klipfel , Yaël Fregier , Adlane Sayede , Zied Bouraoui

The analysis of ultrafast electron diffraction (UED) data from low-symmetry single crystals of small molecules is often challenged by the difficulty of assigning unique Laue indices to the observed Bragg reflections. For a variety of…

Materials Science · Physics 2025-06-30 Alexander Marx , Sascha W. Epp

Dynamically compressed materials in longitudinal waves are described by two physical models: hydrostatic pressure, with equal, normal, principal stresses or material uniaxially strained in the wave propagation direction. These models are…

Materials Science · Physics 2025-09-01 S. J. Burns , Danae N. Polsin

This paper presents a novel Direct Integration Theorem (DIT), derived as a non-trivial corollary of the classical Central Slice Theorem (CST). The DIT provides a mathematically consistent transition from the continuous to the discrete…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Mikhail G. Mozerov

Diffusion models produce high quality images but inference is costly due to many denoising steps and heavy matrix operations. We present DiffPro, a post-training, hardware-faithful framework that works with the exact integer kernels used in…

Machine Learning · Computer Science 2025-11-17 Farhana Amin , Sabiha Afroz , Kanchon Gharami , Mona Moghadampanah , Dimitrios S. Nikolopoulos