A Least-Squares Weak Galerkin Method for Second-Order Elliptic Equations in Non-Divergence Form
This work provides a novel numerical method for solving non-divergence form elliptic equations, which is an incremental improvement over existing weak Galerkin methods.
The paper introduces a least-squares weak Galerkin method for second-order elliptic equations in non-divergence form, achieving symmetric positive definite systems on polygonal meshes with optimal-order error estimates validated by numerical experiments.
This article proposes a novel least-squares weak Galerkin (LS-WG) method for second-order elliptic equations in non-divergence form. The approach leverages a locally defined discrete weak Hessian operator constructed within the weak Galerkin framework. A key feature of the resulting algorithm is that it yields a symmetric and positive definite linear system while remaining applicable to general polygonal and polyhedral meshes. We establish optimal-order error estimates for the approximation in a discrete $H^2$-equivalent norm. Finally, comprehensive numerical experiments are presented to validate the theoretical analysis and demonstrate the efficiency and robustness of the method.