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In this study, a fast and stable machine-learned hybrid algorithm implemented in TensorFlow for the integration of stiff chemical kinetics is introduced. Numerical solutions to differential equations are at the core of computational fluid…

Computational Physics · Physics 2019-06-25 Kyle Buchheit , Opeoluwa Owoyele , Terry Jordan , Dirk Van Essendelft

This paper discusses a fast direct solver using boundary integral equations for Helmholtz transmission problems involving multiple inclusions in two dimensions. Efficiently addressing scattering problems in the presence of numerous…

Numerical Analysis · Mathematics 2026-04-06 Yasuhiro Matsumoto

This paper proposes a frequency/time hybrid integral-equation method for the time dependent wave equation in two and three-dimensional spatial domains. Relying on Fourier Transformation in time, the method utilizes a fixed…

Numerical Analysis · Mathematics 2020-04-30 Thomas G. Anderson , Oscar P. Bruno , Mark Lyon

This study presents an efficient algebraic scheme known as MULES for sharp interface advection, verified against various schemes including first-order upwind, second-order central, van Leer flux limiter, and Geometric Volume-of-Fluid (VOF).…

Fluid Dynamics · Physics 2024-10-23 Mehran Sharifi

A deep learning scheme is proposed to solve the electromagnetic (EM) scattering problems where the profile of the dielectric scatterer of interest is incomplete. As a compensation, a limited amount of scattering data is provided, which is…

Computational Engineering, Finance, and Science · Computer Science 2025-05-06 Ji-Yuan Wang , Xin-Yue Lou , Liang Zhang , Yun-Chuan Wang , Xiao-Min Pan

This paper concerns the fast evaluation of the matvec $g=Kf$ for $K\in \mathbb{C}^{N\times N}$, which is the discretization of the oscillatory integral transform $g(x) = \int K(x,\xi) f(\xi)d\xi$ with a kernel function…

Numerical Analysis · Mathematics 2019-05-01 Haizhao Yang

Scattering by an isolated defect embedded in a dielectric medium of two dimensional periodicity is of interest in many sub-fields of electrodynamics. Present approaches to compute this scattering rely either on the Born approximation and…

Mesoscale and Nanoscale Physics · Physics 2021-05-10 Kuljit S. Virk

We propose a new fast algorithm optimized for full-wave electromagnetic (EM) scattering analysis of a large-scale cloud of chaffs with arbitrary orientation, spatial distribution, and length. By leveraging the unique EM scattering…

Computational Physics · Physics 2024-10-07 Chung Hyun Lee , Dong-Kook Kang , Kyoung Il Kwon , Kyung-Tae Kim , Dong-Yeop Na

An approach is presented for implicit time integration in computations of red blood cell flow by a spectral boundary integral method. The flow of a red cell in ambient fluid is represented as a boundary integral equation (BIE), whose…

Numerical Analysis · Mathematics 2021-09-29 Pei Chuan Chao , Ali Gürbüz , Frederick Sachs , M. V. Sivaselvan

In this work we propose an efficient and accurate multi-scale optical simulation algorithm by applying a numerical version of slowly varying envelope approximation in FEM. Specifically, we employ the fast iterative method to quickly compute…

Optics · Physics 2024-12-03 Fan Xiao , Jingwei Wang , Zhongfei Xiong , Yuntian Chen

Coupled nonlinear system of reaction-diffusion equations describing multi-component (species) interactions with heterogeneous coefficients is considered. Finite volume method based approximation for the space is used to construct…

Numerical Analysis · Mathematics 2022-09-13 Maria Vasilyeva , Alexey Sadovski , D. Palaniappan

An Integral Equation (IE) based field solver to compute the scattered fields from spatially dispersive metasurfaces is proposed and numerically confirmed using various examples involving physical unit cells. The work is a continuation of…

Applied Physics · Physics 2021-09-21 Tom J. Smy , João G. Nizer Rahmeier , Jordan Dugan , Shulabh Gupta

This study aims to develop a simulation framework for rotating detonation engines (RDEs) using multicomponentFluid solver in OpenFOAM v12 and to demonstrate reducing the computational costs by adaptive mesh refinement (AMR) and dynamic load…

Computational Physics · Physics 2025-08-25 Keunjae Kwak , Hyoungwoo Kim , Je Ir Ryu , Donh-Hyuk Shin

This work presents a fast direct solver strategy for electromagnetic integral equations in the high-frequency regime. The new scheme relies on a suitably preconditioned combined field formulation and results in a single skeleton form plus…

Deploying sparse Mixture of Experts(MoE) Vision Transformers remains a challenge due to linear expert memory scaling. Linear memory scaling stores $N$ independent expert weight matrices requiring $\mathcal{O}(N_E \cdot d^2)$ memory, which…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Aryan Karmore

In this paper, we propose high order numerical methods to solve a 2D advection diffusion equation, in the highly oscillatory regime. We use an integrator strategy that allows the construction of arbitrary high-order schemes {leading} to an…

Numerical Analysis · Mathematics 2024-11-11 Clarissa Astuto

The central object in wave turbulence theory is the wave kinetic equation (WKE), which is an evolution equation for wave action density and acts as the wave analog of the Boltzmann kinetic equations for particle interactions. Despite recent…

Numerical Analysis · Mathematics 2026-04-21 Kunlun Qi , Lian Shen , Li Wang

We investigate integral formulations and fast algorithms for the steady-state radiative transfer equation with isotropic and anisotropic scattering. When the scattering term is a smooth convolution on the unit sphere, a model reduction step…

Numerical Analysis · Mathematics 2019-02-20 Yuwei Fan , Jing An , Lexing Ying

We introduce a novel variational autoencoder (VAE) architecture that can generate realistic and diverse high energy physics events. The model we propose utilizes several techniques from VAE literature in order to simulate high fidelity jet…

High Energy Physics - Phenomenology · Physics 2020-09-11 Kosei Dohi

We introduce an end-to-end deep learning architecture called the wide-band butterfly network (WideBNet) for approximating the inverse scattering map from wide-band scattering data. This architecture incorporates tools from computational…

Machine Learning · Computer Science 2021-11-01 Matthew Li , Laurent Demanet , Leonardo Zepeda-Núñez