In this paper we present a novel class of methods for high order accurate integration of multirate systems of ordinary differential equation initial-value problems. Following from recent work on multirate exponential Runge--Kutta (MERK) methods, that construct multirate schemes by approximating the action of matrix $\varphi$-functions within explicit exponential Runge--Kutta methods, the proposed methods similarly build off of explicit exponential Rosenbrock (ExpRB) methods. By leveraging the exponential Rosenbrock structure, the proposed Multirate Exponential Rosenbrock (MERB) methods consist of the solution to a sequence of modified ``fast'' initial-value problems, that may themselves be approximated through subcycling any desired IVP solver. In addition to proving how to construct MERB methods from certain classes of ExpRB methods, we provide rigorous convergence analysis of the resulting schemes, and present candidate MERB schemes of orders two through six. We then present numerical simulations to confirm these theoretical convergence rates, and to compare the efficiency of MERB methods against recently-introduced multirate MERK and MRI-GARK methods.
翻译:在本文中,我们提出了一套对普通差分方程初步价值问题进行高顺序、高精确整合的新型方法。根据最近关于多率指数龙格-库塔(MERK)方法的工作,通过在明显指数龙格-库塔方法中近似矩阵 $\ varphipe$ 函数作用的行动来构建多率计划,拟议方法也以明确的指数罗森布罗克(Extrab)方法为基础。通过利用指数罗森布罗克结构,拟议的多率市价罗森布罗克(MERB)方法包括解决经修改的“快速”初始价值问题序列,这些问题本身可以通过任何理想的IVP求解决器进行亚周期化。除了证明如何从某些类别的ExTRB方法中构建MERB方法外,我们还对由此产生的计划进行了严格的趋同分析,并提出了第二至六级命令候选的MERB计划。我们随后提出数字模拟,以证实这些理论趋同率,并将MERB方法的效率与最近引入的多率的MERK和MRI-GARK方法进行比较。