The Random Feature Method for Solving Interface Problems
Xurong Chi, Jingrun Chen, Zhouwang Yang

TL;DR
This paper introduces a novel mesh-free random feature method for interface problems that avoids mesh generation, handles low regularity solutions effectively, and achieves high accuracy with significantly fewer degrees of freedom.
Contribution
The study develops a new random feature-based approach that couples solutions on either side of an interface using partition of unity, improving efficiency and robustness over traditional methods.
Findings
Achieves high accuracy comparable to spectral collocation for smooth solutions.
Requires two to three orders of magnitude fewer degrees of freedom than traditional methods.
Successfully handles solutions with low regularity, including discontinuities.
Abstract
Interface problems have long been a major focus of scientific computing, leading to the development of various numerical methods. Traditional mesh-based methods often employ time-consuming body-fitted meshes with standard discretization schemes or unfitted meshes with tailored schemes to achieve controllable accuracy and convergence rate. Along another line, mesh-free methods bypass mesh generation but lack robustness in terms of convergence and accuracy due to the low regularity of solutions. In this study, we propose a novel method for solving interface problems within the framework of the random feature method. This approach utilizes random feature functions in conjunction with a partition of unity as approximation functions. It evaluates partial differential equations, boundary conditions, and interface conditions on collocation points in equal footing, and solves a linear…
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Taxonomy
TopicsComputational Geometry and Mesh Generation · Remote Sensing and LiDAR Applications
