Abstract

This paper introduces a new class of numerical methods for the time integration of evolution equations set as Cauchy problems of ODEs or PDEs. The systematic design of these methods mixes the Runge–Kutta collocation formalism with collocation techniques, in such a way that the methods are linearly implicit and have high order. The fact that these methods are implicit allows to avoid CFL conditions when the large systems to integrate come from the space discretization of evolution PDEs. Moreover, these methods are expected to be efficient since they only require to solve one linear system of equations at each time step, and efficient techniques from the literature can be used to do so. After the introduction of the methods, we set suitable definitions of consistency and stability for these methods. This allows for a proof that arbitrarily high order linearly implicit methods exist and converge when applied to ODEs. Eventually, we perform numerical experiments on ODEs and PDEs that illustrate our theoretical results for ODEs, and compare our methods with standard methods for several evolution PDEs.

Highlights

  • The goal of this paper is to introduce a new class of methods for the time integration of evolution problems, set as deterministic ODEs or PDEs

  • This paper introduces a new class of methods for the time integration of evolution problems set as systems of ODEs

  • Using suitable definitions of consistency and stability, we prove that such methods are of high order for ODEs, and the proof extends to finite systems of ODEs

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Summary

Introduction

The goal of this paper is to introduce a new class of methods for the time integration of evolution problems, set as (systems of) deterministic ODEs or PDEs. The authors would like to be able to develop a stability (and convergence) analysis for stiff problems, i.e. an analysis with constants that depend only on the class of the linear part of the vector field (later referred to as L, see (2.1)) and not on that linear part itself This would allow for the numerical treatment of evolution PDE problems, as well as their space discretizations. For the approximation of evolution PDEs in 2d (see Section 3.2.2) with precise space discretization (leading to high number of unknowns), the linearly implicit methods developed in this paper manage to outperform standard methods from the literature with the same order

Linearly implicit methods of arbitrarily high order
Numerical experiments
One dimensional nonlinear Schrodinger equation
Conclusion and perspectives
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