A locally-conservative proximal Galerkin method for pointwise bound constraints

We introduce the first-order system proximal Galerkin (FOSPG) method, a locally mass-conserving, hybridizable finite element method for solving heterogeneous anisotropic diffusion and obstacle problems. Like other proximal Galerkin methods, FOSPG finds solutions by solving a recursive sequence of smooth, discretized, nonlinear subproblems. We establish the well-posedness and convergence of these nonlinear subproblems along with stability and error estimates under low regularity assumptions for the linearized equations obtained by solving each subproblem using Newton’s method. The FOSPG method exhibits several advantages, including high-order accuracy, discrete maximum principle or bound-preserving discrete solutions, and local mass conservation. It also achieves prescribed solution accuracy within asymptotically mesh-independent numbers of subproblems and linear solves per subproblem iteration. Numerical experiments on benchmarks for anisotropic diffusion and obstacle problems confirm these attributes. Furthermore, an open-source implementation of the method is provided to facilitate broader adoption and reproducibility.

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Publication Details

Journal
Mathematics of Computation
Published
2026-07-27
DOI
https://doi.org/10.1090/mcom/4218
Citations
1
Primary Topic
Advanced Numerical Methods in Computational Mathematics
Type
article
Field-Weighted Citation Impact
0.00

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article

A locally-conservative proximal Galerkin method for pointwise bound constraints

Guosheng Fu, Brendan Keith, Rami Masri
1 citations
Mathematics of Computation
Advanced Numerical Methods in Computational Mathematics
article

A locally-conservative proximal Galerkin method for pointwise bound constraints

Guosheng Fu, Brendan Keith, Rami Masri
article en
1 citations

Abstract

We introduce the first-order system proximal Galerkin (FOSPG) method, a locally mass-conserving, hybridizable finite element method for solving heterogeneous anisotropic diffusion and obstacle problems. Like other proximal Galerkin methods, FOSPG finds solutions by solving a recursive sequence of smooth, discretized, nonlinear subproblems. We establish the well-posedness and convergence of these nonlinear subproblems along with stability and error estimates under low regularity assumptions for the linearized equations obtained by solving each subproblem using Newton’s method. The FOSPG method exhibits several advantages, including high-order accuracy, discrete maximum principle or bound-preserving discrete solutions, and local mass conservation. It also achieves prescribed solution accuracy within asymptotically mesh-independent numbers of subproblems and linear solves per subproblem iteration. Numerical experiments on benchmarks for anisotropic diffusion and obstacle problems confirm these attributes. Furthermore, an open-source implementation of the method is provided to facilitate broader adoption and reproducibility.

Mathematics of Computation
National Science Foundation, U.S. Department of Energy, Alfred P. Sloan Foundation, Office of Science, National Nuclear Security Administration
Openalex Percentile: Top 99%
Advanced Numerical Methods in Computational Mathematics
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