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The numerical simulation of physical processes in the underground frequently entails challenges related to the geometry and/or data. The former are mainly due to the shape of sedimentary layers and the presence of fractures and faults,…

Numerical Analysis · Mathematics 2020-02-28 Alessio Fumagalli , Anna Scotti , Luca Formaggia

High-performance learned image compression codecs require flexible probability models to fit latent representations. Gaussian Mixture Models (GMMs) were proposed to satisfy this demand, but suffer from a significant runtime performance…

Image and Video Processing · Electrical Eng. & Systems 2025-09-24 Shimon Murai , Fangzheng Lin , Jiro Katto

Numerical codes using the Lattice Boltzmann Methods (LBM) for simulating one- or two-phase flows are widely compiled and run on graphical process units. However, those computational units necessitate to re-write the program by using a…

Computational Physics · Physics 2020-08-26 Werner Verdier , Pierre Kestener , Alain Cartalade

We present solidfmm, a highly optimised C++ library for the solid harmonics as they are needed in fast multipole methods. The library provides efficient, vectorised implementations of the translation operations M2M, M2L, and L2L, and is…

Mathematical Software · Computer Science 2022-02-08 Matthias Kirchhart

The fast multipole method (FMM) has received growing attention in the beam physics simulation. In this study, we formulate an interpolation-based FMM for the computation of the relativistic space-charge field. Different to the…

Computational Physics · Physics 2023-07-19 Yi-Kai Kan , Franz X. Kärtner , Sabine Le Borne , Jens-Peter M. Zemke

We introduce and analyze a virtual element method (VEM) for the Helmholtz problem with approximating spaces made of products of low order VEM functions and plane waves. We restrict ourselves to the 2D Helmholtz equation with impedance…

Numerical Analysis · Mathematics 2015-05-20 Ilaria Perugia , Paola Pietra , Alessandro Russo

The birth of the lattice Boltzmann method (LBM) fulfils a dream that simple arithmetic calculations can simulate complex fluid flows without solving complicated partial differential flow equations. Its power and potential of resolving more…

Computational Engineering, Finance, and Science · Computer Science 2019-01-10 Jian Guo Zhou

Computation of vorticity in conjunction with the strain rate tensor, plays an important role in fluid mechanics in vortical structure identification and in the modeling of various complex fluids. For the simulation of flows accompanied by…

Fluid Dynamics · Physics 2019-08-20 Farzaneh Hajabdollahi , Kannan N. Premnath

Quantum algorithms have been identified as a potential means to accelerate computational fluid dynamics (CFD) simulations, with the lattice Boltzmann method (LBM) being a promising candidate for realizing quantum speedups. Here, we extend…

Although Lattice Boltzmann Method (LBM) is relatively straightforward, it demands a well-crafted framework to handle the complex partial differential equations involved in multiphase flow simulations. For the first time to our knowledge,…

Numerical Analysis · Mathematics 2026-04-02 Matteo Maria Piredda , Pietro Asinari

We have performed a detailed analysis of the fast multipole method (FMM) in the adaptive case, in which the depth of the FMM tree is non-uniform. Previous works in this area have focused mostly on special types of adaptive distributions,…

Numerical Analysis · Mathematics 2015-08-12 Hadi Pouransari , Eric Darve

We analyze a volumetric formulation of lattice Boltzmann for compressible thermal fluid flows. The velocity set is chosen with the desired accuracy, based on the Gauss-Hermite quadrature procedure, and tested against controlled problems in…

Soft Condensed Matter · Physics 2015-05-18 M. Sbragaglia , K. Sugiyama

It is proposed a dimensional Lattice Boltzmann Method (LBM) of wide application for simulating fluid flow and heat transfer problems. The proposed LBM consists in the numerical solution of the discrete lattice Boltzmann equation (LBE) using…

Fluid Dynamics · Physics 2024-05-14 Ivan Talão Martins , Pablo Fariñas Alvariño , Luben Cabezas-Gómez

In order to explore the influence of combustion-induced thermal expansion on turbulence, a new research method is introduced. The method consists in jointly applying Helmholtz-Hodge decomposition and conditioned structure functions to…

Chaotic free surface flows are challenging problems to simulate numerically, mainly due to the significant changes in geometry and frequent topological changes. Methods that track the evolution of the fluid in a Lagrangian formulation are a…

Fluid Dynamics · Physics 2025-12-24 Thomas Leyssens , Jonathan Lambrechts , Jean-François Remacle

An advance in experimental plasma diagnostics is presented and used to make the first measurement of a plasma velocity-space cross-correlation matrix. The velocity space correlation function can detect collective fluctuations of plasmas…

Plasma Physics · Physics 2018-08-13 Sean Mattingly , Fred Skiff

This paper introduces Force Matching (ForM), a novel framework for generative modeling that represents an initial exploration into leveraging special relativistic mechanics to enhance the stability of the sampling process. By incorporating…

Machine Learning · Computer Science 2025-02-13 Yang Cao , Bo Chen , Xiaoyu Li , Yingyu Liang , Zhizhou Sha , Zhenmei Shi , Zhao Song , Mingda Wan

We develop convergence acceleration procedures that enable a gradient descent-type iteration method to efficiently simulate Hartree--Fock equations for atoms interacting both with each other and with an external potential. Our development…

Computational Physics · Physics 2025-03-03 Y. Ohno , A. Del Maestro , T. I. Lakoba

In the present study, quantitative feasibility tests of the hydrodynamic description of a two-dimensional fluid at the molecular level are performed, both with respect to length and time scales. Using high-resolution fluid velocity data…

Fluid Dynamics · Physics 2018-01-17 Kyeong Hwan Han , Changho Kim , Peter Talkner , George Em Karniadakis , Eok Kyun Lee

Large Language Diffusion Models (LLDMs) benefit from a flexible decoding mechanism that enables parallelized inference and controllable generations over autoregressive models. Yet such flexibility introduces a critical challenge: inference…

Machine Learning · Computer Science 2025-12-05 Yichuan Mo , Quan Chen , Mingjie Li , Zeming Wei , Yisen Wang
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