Reducing polynomial degree by one for inner-stage operators affects neither stability type nor accuracy order of the Runge--Kutta discontinuous Galerkin method

TL;DR

This paper proves that reducing the polynomial degree by one in inner-stage operators of high-order Runge--Kutta DG methods does not compromise their stability or accuracy, enabling more efficient computations.

Contribution

It provides a theoretical proof that lowering polynomial degree at inner RK stages preserves stability and convergence, facilitating cost-effective DG schemes.

Findings

Maintains stability and convergence rate despite degree reduction.

Validates theoretical results with numerical examples.

Supports development of more efficient DG methods.

Abstract

The Runge--Kutta (RK) discontinuous Galerkin (DG) method is a mainstream numerical algorithm for solving hyperbolic equations. In this paper, we use the linear advection equation in one and two dimensions as a model problem to prove the following results: For an arbitrarily high-order RKDG scheme in Butcher form, as long as we use the $P^k$ approximation in the final stage, even if we drop the $k$th-order polynomial modes and use the $P^{k-1}$ approximation for the DG operators at all inner RK stages, the resulting numerical method still maintains the same type of stability and convergence rate as those of the original RKDG method. Numerical examples are provided to validate the analysis. The numerical method analyzed in this paper is a special case of the Class A RKDG method with stage-dependent polynomial spaces proposed in arXiv:2402.15150. Our analysis provides theoretical justifications for employing cost-effective and low-order spatial discretization at specific RK stages for developing more efficient DG schemes without affecting stability and accuracy of the original method.