High Order Edge Sensors with $\ell^1$ Regularization for Enhanced Discontinuous Galerkin Methods
For computational scientists using DG methods, this work offers a targeted approach to handle discontinuities without degrading performance in smooth regions, though it is an incremental improvement over existing shock-capturing techniques.
This paper introduces a method combining high-order edge sensors with ℓ1 regularization to detect and treat troubled elements in discontinuous Galerkin (DG) simulations of hyperbolic conservation laws, achieving accurate and efficient solutions by applying regularization only where needed.
This paper investigates the use of $\ell^1$ regularization for solving hyperbolic conservation laws based on high order discontinuous Galerkin (DG) approximations. We first use the polynomial annihilation method to construct a high order edge sensor which enables us to flag troubled elements. The DG approximation is enhanced in these troubled regions by activating $\ell^1$ regularization to promote sparsity in the corresponding jump function of the numerical solution. The resulting $\ell^1$ optimization problem is efficiently implemented using the alternating direction method of multipliers. By enacting $\ell^1$ regularization only in troubled cells, our method remains accurate and efficient, as no additional regularization or expensive iterative procedures are needed in smooth regions. We present results for the inviscid Burgers' equation as well as a nonlinear system of conservation laws using a nodal collocation-type DG method as a solver.