High-order numerical methods for 2D parabolic problems in single and composite domains
Gustav Ludvigsson, Kyle R. Steffen, Simon Sticko, Siyang Wang, Qing, Xia, Yekaterina Epshteyn, Gunilla Kreiss

TL;DR
This paper compares three high-order numerical methods—Cut Finite Element, Difference Potentials, and summation-by-parts Finite Difference—for solving 2D parabolic diffusion problems in single and composite domains, focusing on accuracy and convergence.
Contribution
It provides a comparative analysis and benchmark tests of three advanced numerical methods for 2D parabolic problems with discontinuities at interfaces.
Findings
All methods achieve high accuracy and convergence.
Differences in handling interface discontinuities are highlighted.
Benchmark results guide method selection for specific problem types.
Abstract
In this work, we discuss and compare three methods for the numerical approximation of constant- and variable-coefficient diffusion equations in both single and composite domains with possible discontinuity in the solution/flux at interfaces, considering (i) the Cut Finite Element Method; (ii) the Difference Potentials Method; and (iii) the summation-by-parts Finite Difference Method. First we give a brief introduction for each of the three methods. Next, we propose benchmark problems, and consider numerical tests-with respect to accuracy and convergence-for linear parabolic problems on a single domain, and continue with similar tests for linear parabolic problems on a composite domain (with the interface defined either explicitly or implicitly). Lastly, a comparative discussion of the methods and numerical results will be given.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Numerical Methods in Computational Mathematics · Advanced Mathematical Modeling in Engineering · Differential Equations and Numerical Methods
