Implicit-Explicit Multirate Infinitesimal Stage-Restart Methods

TL;DR

This paper introduces a new class of high-order implicit-explicit multirate methods, called IMEX-MRI-SR, for efficiently solving multirate initial-value problems with partitioned slow and fast dynamics, improving accuracy and performance.

Contribution

The paper develops IMEX-MRI-SR methods that extend existing multirate IMEX approaches, achieving higher order accuracy and better computational efficiency for multirate IVPs.

Findings

Methods achieve up to fourth-order accuracy.

Numerical simulations confirm convergence rates.

Demonstrated improved computational performance.

Abstract

Implicit-Explicit (IMEX) methods are flexible numerical time integration methods which solve an initial-value problem (IVP) that is partitioned into stiff and nonstiff processes with the goal of lower computational costs than a purely implicit or explicit approach. A complementary form of flexible IVP solvers are multirate infinitesimal methods for problems partitioned into fast- and slow-changing dynamics, that solve a multirate IVP by evolving a sequence of ``fast'' IVPs using any suitably accurate algorithm. This article introduces a new class of high-order implicit-explicit multirate methods that are designed for multirate IVPs in which the slow-changing dynamics are further partitioned in an IMEX fashion. This new class, which we call implicit-explicit multirate stage-restart (IMEX-MRI-SR), both improves upon the previous implicit-explicit multirate generalized-structure additive Runge Kutta (IMEX-MRI-GARK) methods, and extends multirate exponential Runge Kutta (MERK) methods into the IMEX context. We leverage GARK theory to derive conditions guaranteeing orders of accuracy up to four. We provide second-, third-, and fourth-order accurate example methods and perform numerical simulations demonstrating convergence rates and computational performance in both fixed-step and adaptive-step settings.