The proximal Galerkin method for non-symmetric variational inequalities

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Authors: Guosheng Fu, Brendan Keith, Dohyun Kim, Rami Masri, Will Pazner
Cited by: 0

Abstract

We introduce the proximal Galerkin (PG) method for non-symmetric variational inequalities. The proposed approach is asymptotically mesh-independent and yields constraint-preserving approximations. We present both a conforming PG formulation and a hybrid mixed first-order system variant (FOSPG). We establish optimal a priori error estimates for each variant, which are verified numerically. We conclude by applying the method to American option pricing, free boundary problems in porous media, advection-diffusion with a semipermeable boundary, and the enforcement of discrete maximum principles.

Fields of Study & Subjects

Advanced Numerical Methods in Computational Mathematics Contact Mechanics and Variational Inequalities Matrix Theory and Algorithms

Publication details

Journal / source
arXiv (Cornell University)
Publication date
16 February 2026
Language
EN
Document type
Preprint