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We present a novel immersed boundary method that implements acoustic perturbation theory to model an acoustically levitated droplet. Instead of resolving sound waves numerically, our hybrid method solves acoustic scattering…

Soft Condensed Matter · Physics 2024-03-22 Jacqueline B. Sustiel , David G. Grier

Wasserstein gradient and Hamiltonian flows have emerged as essential tools for modeling complex dynamics in the natural sciences, with applications ranging from partial differential equations (PDEs) and optimal transport to quantum…

Numerical Analysis · Mathematics 2025-11-11 Jianyu Hu , Juan-Pablo Ortega , Daiying Yin

We introduce a novel quadrature strategy for Isogeometric Analysis (IgA) boundary element discretizations, specifically tailored to collocation methods. Thanks to the dimensionality reduction and the natural handling of unbounded domains,…

Numerical Analysis · Mathematics 2025-11-25 Cesare Bracco , Francesco Patrizi , Alessandra Sestini

We propose a boundary neuron method with random features (BNM-RF) for solving partial differential equations. The method approximates the unknown boundary function by a shallow network within the boundary integral formulation. With randomly…

Numerical Analysis · Mathematics 2026-03-30 Ye Lin , Wentao Liu , Young Ju Lee , Jiwei Jia

The immersed boundary method (IBM) of Peskin (J. Comput. Phys., 1977), and derived forms such as the projection method of Taira and Colonius (J. Comput. Phys., 2007), have been useful for simulating flow physics in problems with moving…

Fluid Dynamics · Physics 2021-10-01 Jeff D. Eldredge

Kernel Bayesian inference is a principled approach to nonparametric inference in probabilistic graphical models, where probabilistic relationships between variables are learned from data in a nonparametric manner. Various algorithms of…

Machine Learning · Statistics 2019-04-18 Yu Nishiyama , Motonobu Kanagawa , Arthur Gretton , Kenji Fukumizu

The immersed boundary (IB) method is a mathematical framework for fluid-structure interaction problems (FSI) that was originally developed to simulate flows around heart valves. Direct comparison of FSI simulations around heart valves…

Modern Bayesian optimization and adaptive sampling methods increasingly rely on nonlinear parametric models, yet theoretical guarantees for such models under adaptive data collection remain limited. Existing analyses largely focus on…

Machine Learning · Statistics 2026-05-14 Rafael Oliveira

Immersed boundary-lattice Boltzmann method (IB-LBM) has been widely used for simulation of particle-laden flows recently. However, it was limited to small-scale simulations with no more than O(103) particles. Here, we expand IB-LBM for…

Computational Physics · Physics 2020-02-21 Maoqiang Jiang , Jing Li , Zhaohui Liu

A kernelization is an efficient algorithm that given an instance of a parameterized problem returns an equivalent instance of size bounded by some function of the input parameter value. It is quite well understood which problems do or…

Data Structures and Algorithms · Computer Science 2025-10-02 Leonid Antipov , Stefan Kratsch

The modelling of data on a spherical surface requires the consideration of directional probability distributions. To model asymmetrically distributed data on a three-dimensional sphere, Kent distributions are often used. The moment…

Machine Learning · Computer Science 2015-06-29 Parthan Kasarapu

Inspired by the numerical immersed boundary method, we introduce regularized Stokes immersed boundary problems in two dimensions to describe regularized motion of a 1-D closed elastic string in a 2-D Stokes flow, in which a regularized…

Analysis of PDEs · Mathematics 2019-04-23 Jiajun Tong

This paper presents an improved immersed moving boundary model (IBM) for solving complex fluid-particle interactions in a coupled lattice Boltzmann method (LBM) and an adhesive discrete element method (DEM), using the "partially saturated…

Soft Condensed Matter · Physics 2020-10-21 Wenwei Liu , Chuan-Yu Wu

The Immersed Boundary method is a simple, efficient, and robust numerical scheme for solving PDE in general domains, yet for fluid problems it only achieves first-order spatial accuracy near embedded boundaries for the velocity field and…

Numerical Analysis · Mathematics 2017-03-08 David B. Stein , Robert D. Guy , Becca Thomases

In most adaptive signal processing applications, system linearity is assumed and adaptive linear filters are thus used. The traditional class of supervised adaptive filters rely on error-correction learning for their adaptive capability.…

Machine Learning · Computer Science 2015-08-31 Songlin Zhao

Iteratively Re-weighted Least Squares (IRLS) is a method for solving minimization problems involving non-quadratic cost functions, perhaps non-convex and non-smooth, which however can be described as the infimum over a family of quadratic…

Numerical Analysis · Mathematics 2016-02-24 Massimo Fornasier , Steffen Peter , Holger Rauhut , Stephan Worm

Cable subsystems characterized by long, slender, and flexible structural elements are featured in numerous engineering systems. In each of them, interaction between an individual cable and the surrounding fluid is inevitable. Such a…

Computational Engineering, Finance, and Science · Computer Science 2019-11-11 Daniel Z. Huang , Philip Avery , Charbel Farhat

We present an implementation of a fully variational formulation of an immersed method for fluid-structure interaction problems based on the finite element method. While typical implementation of immersed methods are characterized by the use…

Numerical Analysis · Mathematics 2015-04-10 Saswati Roy , Luca Heltai , Francesco Costanzo

Immersed boundary methods for computing confined fluid and plasma flows in complex geometries are reviewed. The mathematical principle of the volume penalization technique is described and simple examples for imposing Dirichlet and Neumann…

Plasma Physics · Physics 2015-10-07 Kai Schneider

The ever-increasing parameter counts of deep learning models necessitate effective compression techniques for deployment on resource-constrained devices. This paper explores the application of information geometry, the study of…

Machine Learning · Computer Science 2025-07-15 Zakhar Shumaylov , Vasileios Tsiaras , Yannis Stylianou
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