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Diffusion is the underlying mechanism for many complicated materials phenomena, and understanding it is basic to the discovery of novel materials with desired physical and mechanical properties. Certain groups of solid phases, such as the…

Materials Science · Physics 2023-07-06 Sara Kadkhodaei , Ali Davariashtiyani

Hydrogen diffusion is critical to the performance of metals for hydrogen storage as well as other important applications. As compared to its crystalline counterpart which follows the Arrhenius relation, hydrogen diffusion in amorphous…

Materials Science · Physics 2023-10-25 Chunguang Tang , Gang Sun , Yun Liu

We have exposed a dual-phase Liquid Argon Time Projection Chamber (LAr-TPC) to a low energy pulsed narrowband neutron beam, produced at the Notre Dame Institute for Structure and Nuclear Astrophysics to study the scintillation light yield…

Discrimination between electron and nuclear recoil events in a liquid argon scintillation detector has been demonstrated with simulations by using the differences in the scintillation photon time distribution between these classes of…

Astrophysics · Physics 2007-05-23 M. G. Boulay , A. Hime

The HARP experiment was designed to study hadron production in proton- nucleus collisions in the energy range of 1.5 GeV/c-15 GeV/c. The experiment was made of two spectrometers, a forward dipole spectrometer and a large-angle solenoid…

We perform Brownian dynamics simulations for studying the self-diffusion in two-dimensional (2D) dusty plasma liquids, in terms of both mean-square displacement and velocity autocorrelation function (VAF). Super-diffusion of charged dust…

Plasma Physics · Physics 2009-02-25 Lu-Jing Hou , Alexander Piel , P. K. Shukla

The steep computational cost of diffusion models at inference hinders their use as fast physics emulators. In the context of image and video generation, this computational drawback has been addressed by generating in the latent space of an…

Machine Learning · Computer Science 2025-11-04 François Rozet , Ruben Ohana , Michael McCabe , Gilles Louppe , François Lanusse , Shirley Ho

Despite the remarkable progress in generative modelling, current diffusion models lack a quantitative approach to assess image quality. To address this limitation, we propose to estimate the pixel-wise aleatoric uncertainty during the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Michele De Vita , Vasileios Belagiannis

We study the influence of the boundary conditions at the solid liquid interface on diffusion in a confined fluid. Using an hydrodynamic approach, we compute numerical estimates for the diffusion of a particle confined between two planes.…

Materials Science · Physics 2015-06-25 Anthony Saugey , Laurent Joly , Christophe Ybert , Jean-Louis Barrat , Lyderic Bocquet

In this paper we study the properties of the Lasso estimator of the drift component in the diffusion setting. More specifically, we consider a multivariate parametric diffusion model $X$ observed continuously over the interval $[0,T]$ and…

Statistics Theory · Mathematics 2023-03-29 Gabriela Ciolek , Dmytro Marushkevych , Mark Podolskij

LiDAR perception is severely limited by the distance-dependent sparsity of distant objects. While diffusion models can recover dense geometry, they suffer from prohibitive latency and physical hallucinations manifesting as ghost points. We…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Zeping Zhang , Robert Laganière

Liquid argon time projection chambers (LArTPCs) provide dense, high-fidelity 3D measurements of particle interactions and underpin current and future neutrino and rare-event experiments. Physics reconstruction typically relies on complex…

High Energy Physics - Experiment · Physics 2025-12-02 Samuel Young , Kazuhiro Terao

This paper reports on laser-induced multiphoton ionization at 266 nm of liquid argon in a time projection chamber (LAr TPC) detector. The electron signal produced by the laser beam is a formidable tool for the calibration and monitoring of…

Instrumentation and Detectors · Physics 2010-12-21 I. Badhrees , A. Ereditato , I. Kreslo , M. Messina , U. Moser , B. Rossi , M. S. Weber , M. Zeller , C. Altucci , S. Amoruso , R. Bruzzese , R. Velotta

Room temperature electronic diffusion is studied in 3 mum thick epitaxial p+ GaAs lift-off films using a novel circularly polarized photoluminescence microscope. The method is equivalent to using a standard optical microscope and provides a…

Mesoscale and Nanoscale Physics · Physics 2010-11-15 I. Favorskiy , D. Vu , E. Peytavit , S. Arscott , D. Paget , A. C. H. Rowe

Diffusion-driven processes are important phenomena of materials science in the field of energy conversion and transmission. During the conversion from chemical energy to electrical energy, the species diffusion is generally linked to the…

Applied Physics · Physics 2021-02-23 Jay Santoki

Medical image segmentation often involves inherent uncertainty due to variations in expert annotations. Capturing this uncertainty is an important goal and previous works have used various generative image models for the purpose of…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Jakob Lønborg Christensen , Morten Rieger Hannemose , Anders Bjorholm Dahl , Vedrana Andersen Dahl

The material dispersion of the [Ckmim][BF4] (k = 2,3,4,6,7,8,10) family of ionic liquids is measured at several temperatures over a broad spectral range from 300 nm to 1550 nm. The experimental curves are fitted to a modified…

We expand on a recent study of a lattice model of interacting particles [Phys. Rev. Lett. 111, 110601 (2013)]. The adsorption isotherm and equilibrium fluctuations in particle number are discussed as a function of the interaction. Their…

Statistical Mechanics · Physics 2014-11-20 T. Becker , K. Nelissen , B. Cleuren , B. Partoens , C. Van den Broeck

The diffusion of atoms and radicals on interstellar dust grains is a fundamental ingredient for predicting accurate molecular abundances in astronomical environments. Quantitative values of diffusivity and diffusion barriers usually rely…

Astrophysics of Galaxies · Physics 2021-12-22 Viktor Zaverkin , Germán Molpeceres , Johannes Kästner

Machine learning models are increasingly trained or fine-tuned on synthetic data. Recursively training on such data has been observed to significantly degrade performance in a wide range of tasks, often characterized by a progressive drift…

Machine Learning · Statistics 2026-02-19 Nail B. Khelifa , Richard E. Turner , Ramji Venkataramanan