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The Closest Point method, initially developed by Ruuth and Merriman, allows for the numerical solution of surface partial differential equations without the need for a parameterization of the surface itself. Surface quantities are embedded…

Computational Engineering, Finance, and Science · Computer Science 2017-06-28 Christopher J. Vogl

Many applications like subseismic fault modeling, fractured reservoir modeling and interpretation/validation of fault connectivity involve the solution to an elliptic boundary value problem in a background medium perturbed by the presence…

Optimization and Control · Mathematics 2025-01-10 Trung Hau Hoang

Eigenvalue problems are fundamental to mathematics and science. We present a simple algorithm for determining eigenvalues and eigenfunctions of the Laplace--Beltrami operator on rather general curved surfaces. Our algorithm, which is based…

Numerical Analysis · Mathematics 2011-09-13 Colin B. Macdonald , Jeremy Brandman , Steven J. Ruuth

In recent work, Li et al.\ (Comm.\ Math.\ Sci., 7:81-107, 2009) developed a diffuse-domain method (DDM) for solving partial differential equations in complex, dynamic geometries with Dirichlet, Neumann, and Robin boundary conditions. The…

Numerical Analysis · Mathematics 2015-05-18 Karl Yngve Lervåg , John Lowengrub

Immersed boundary methods are high-order accurate computational tools used to model geometrically complex problems in computational mechanics. While traditional finite element methods require the construction of high-quality boundary-fitted…

Numerical Analysis · Mathematics 2024-02-27 Jennifer E. Fromm , Nils Wunsch , Kurt Maute , John A. Evans , Jiun-Shyan Chen

Machine learning for scientific applications faces the challenge of limited data. We propose a framework that leverages a priori known physics to reduce overfitting when training on relatively small datasets. A deep neural network is…

Machine Learning · Computer Science 2019-11-22 Jonathan B. Freund , Jonathan F. MacArt , Justin Sirignano

Real-time fluid and aeroacoustic simulation on complex surfaces can have interactive applications - from globe-based weather visualizations to immersive computer games with physically accurate wind and sound. However, conventional…

Analysis of PDEs · Mathematics 2026-01-23 Madhusraba Sinha , Jan Stratmann

In this paper, we evaluate the effectiveness of deep operator networks (DeepONets) in solving both forward and inverse problems of partial differential equations (PDEs) on unknown manifolds. By unknown manifolds, we identify the manifold by…

Numerical Analysis · Mathematics 2024-07-09 Anran Jiao , Qile Yan , Jhn Harlim , Lu Lu

Partial differential equations (PDEs) have become an essential tool for modeling complex physical systems. Such equations are typically solved numerically via mesh-based methods, such as finite element methods, with solutions over the…

Methodology · Statistics 2024-02-15 Chih-Li Sung , Wenjia Wang , Liang Ding , Xingjian Wang

This paper proposes a mesh-free computational framework and machine learning theory for solving elliptic PDEs on unknown manifolds, identified with point clouds, based on diffusion maps (DM) and deep learning. The PDE solver is formulated…

Numerical Analysis · Mathematics 2024-02-28 Senwei Liang , Shixiao W. Jiang , John Harlim , Haizhao Yang

We introduce the Closest Point Heat Method (CPHM), a novel approach for solving the surface Eikonal equation on general smooth surfaces. Building on the strengths of the classical heat method, such as simplicity of implementation and…

Numerical Analysis · Mathematics 2025-09-11 Tony Wong , Shingyu Leung , Byungjoon Lee

A general method to generate a centrosymmetric matrix associated with the solving of partial differential equation (PDE) on an irreducible domain by means of a linear equation system is proposed. The method applies to any PDE for which both…

Numerical Analysis · Mathematics 2025-03-12 T. Thuillier

In this paper we generalize the Interior Point-Proximal Method of Multipliers (IP-PMM) presented in [An Interior Point-Proximal Method of Multipliers for Convex Quadratic Programming, Computational Optimization and Applications, 78,…

Optimization and Control · Mathematics 2021-09-09 Spyridon Pougkakiotis , Jacek Gondzio

We demonstrate a method for filtering images defined on curved surfaces embedded in 3D. Applications are noise removal and the creation of artistic effects. Our approach relies on in-surface diffusion: we formulate Weickert's edge/coherence…

Numerical Analysis · Mathematics 2014-04-08 Emma Naden , Thomas März , Colin B. Macdonald

The Intrinsic Surface Finite Element Method (ISFEM) was recently proposed to solve Partial Differential Equations (PDEs) on surfaces. ISFEM proceeds by writing the PDE with respect to a local coordinate system anchored to the surface and…

Numerical Analysis · Mathematics 2024-10-08 Elena Bachini , Mario Putti

The solution of partial differential equations (PDEs) on complex domains often presents a significant computational challenge by requiring the generation of fitted meshes. The Diffuse Domain Method (DDM) is an alternative which reformulates…

Numerical Analysis · Mathematics 2026-05-13 Luke Benfield , Andreas Dedner

We present a method of CutFEM type for the Poisson problem with either Dirichlet or Neumann boundary conditions. The computational mesh is obtained from a background (typically uniform Cartesian) mesh by retaining only the elements…

Numerical Analysis · Mathematics 2019-09-04 Alexei Lozinski

In this work, we propose staggered FDTD schemes based on the correction function method (CFM) to discretize Maxwell's equations with embedded perfect electric conductor (PEC) boundary conditions. The CFM uses a minimization procedure to…

Numerical Analysis · Mathematics 2021-08-02 Yann-Meing Law , Jean-Christophe Nave

The problem of solving partial differential equations (PDEs) on manifolds can be considered to be one of the most general problem formulations encountered in computational multi-physics. The required covariant forms of balance laws as well…

Numerical Analysis · Mathematics 2021-01-19 Robert L. Gates , Maximilian Bittens

Interior-point methods offer a highly versatile framework for convex optimization that is effective in theory and practice. A key notion in their theory is that of a self-concordant barrier. We give a suitable generalization of…

Optimization and Control · Mathematics 2024-06-26 Hiroshi Hirai , Harold Nieuwboer , Michael Walter