Stability of backward Euler multirate methods and convergence of waveform relaxation

For a large class of traditional backward Euler multirate methods we show that stability is preserved when the methods are applied to certain stable (but not necessarily monotonic) non-linear systems. Methods which utilize waveform relaxation sweeps are shown to be stable and converge for certain monotonic systems.     

On convergence conditions of waveform relaxation methods for linear differential-algebraic equations

For linear constant-coefficient differential-algebraic equations, we study the waveform relaxation methods without demanding the boundedness of the solutions based on infinite time interval. In particular, we derive explicit expression and obtain asymptotic convergence rate of this class of iteration schemes under weaker assumptions, which may have wider and more useful application extent. Numerical simulations demonstrate the validity of the theory.     

Explicit methods for mildly stiff oscillatory systems

We discuss error control for explicit methods when the stepsize is bounded by stability on the imaginary axis. Our main result is a formulation of a condition on the estimator of the local error which prevents the fast components to exceed the prescribed error tolerance. A PECE Adams method of 4th order accuracy is proposed for mildly stiff oscillatory systems. For comparison we also discuss embedded Runga-Kutta methods.Partially supported by the Office of Naval Research N00014-90-J-1382     

Convergence of linear multistep and one-leg methods for stiff nonlinear initial value problems

To prove convergence of numerical methods for stiff initial value problems, stability is needed but also estimates for the local errors which are not affected by stiffness. In this paper global error bounds are derived for one-leg and linear multistep methods applied to classes of arbitrarily stiff, nonlinear initial value problems. It will be shown that under suitable stability assumptions the multistep methods are convergent for stiff problems with the same order of convergence as for nonstiff problems, provided that the stepsize variation is sufficiently regular.     

Energy-preserving methods for Poisson systems

We present and analyze energy-conserving methods for the numerical integration of IVPs of Poisson type that are able to preserve some Casimirs. Their derivation and analysis is done following the ideas of Hamiltonian BVMs (HBVMs) (see Brugnano et al. [10] and references therein). It is seen that the proposed approach allows us to obtain the methods recently derived in Cohen and Hairer (2011) [17], giving an alternative derivation of such methods and a new proof of their order. Sufficient conditions that ensure the existence of a unique solution of the implicit equations defining the formulae are given. A study of the implementation of the methods is provided. In particular, order and preservation properties when the involved integrals are approximated by means of a quadrature formula, are derived.     

Half-explicit Runge-Kutta methods with explicit stages for differential-algebraic systems of index 2

Usually the straightforward generalization of explicit Runge-Kutta methods for ordinary differential equations to half-explicit methods for differential-algebraic systems of index 2 results in methods of orderq≤2. The construction of higher order methods is simplified substantially by a slight modification of the method combined with an improved strategy for the computation of the algebraic solution components. We give order conditions up to orderq=5 and study the convergence of these methods. Based on the fifth order method of Dormand and Prince the fifth order half-explicit Runge-Kutta method HEDOP5 is constructed that requires the solution of 6 systems of nonlinear equations per step of integration.     

Convergence and stability of implicit runge-kutta methods for systems with multiplicative noise

A class ofimplicit Runge-Kutta schemes for stochastic differential equations affected bymultiplicative Gaussian white noise is shown to be optimal with respect to global order of convergence in quadratic mean. A test equation is proposed in order to investigate the stability of discretization methods for systems of this kind. Herestability is intended in a truly probabilistic sense, as opposed to the recently introduced extension of A-stability to the stochastic context, given for systems with additive noise. Stability regions for the optimal class are also given.Partially supported by the Italian Consiglio Nazionale delle Ricerche.     

A stability property ofA-stable natural Runge-Kutta methods for systems of delay differential equations

A natural Runge-Kutta method is a special type of Runge-Kutta method for delay differential equations (DDEs); it is known that any one-step collocation method is equivalent to one of such methods. In this paper, we consider a linear constant-coefficient system of DDEs with a constant delay, and discuss the application of natural Runge-Kutta methods to the system. We show that anA-stable method preserves the asymptotic stability property of the analytical solutions of the system.     

Constrained least squares methods for linear timevarying DAE systems

Summary This paper presents a family of methods for accurate solution of higher index linear variable DAE systems, . These methods use the DAE system and some of its first derivatives as constraints to a least squares problem that corresponds to a Taylor series ofy, or an approximative equality derived from a Pade' approximation of the exponential function. Accuracy results for systems transformable to standard canonical form are given. Advantages, disadvantages, stability properties and implementation of these methods are discussed and two numerical examples are given, where we compare our results with results from more traditional methods.     

On the Convergence of LMF-type Methods for SODEs

In a previous paper [3], some numerical methods for stochastic ordinary differential equations (SODEs), based on Linear Multistep Formulae (LMF), were proposed. Nevertheless, a formal proof for the convergence of such methods is still lacking. We here provide such a proof, based on a matrix formulation of the discrete problem, which allows some more insight in the structure of LMF-type methods for SODEs.     

On the solvability of the systems of equations arising in implicit Runge-Kutta methods

In this paper we present a new condition under which the systems of equations arising in the application of an implicit Runge-Kutta method to a stiff initial value problem, has unique solutions. We show that our condition is weaker than related conditions presented previously. It is proved that the Lobatto IIIC methods fulfil the new condition.     

A parareal waveform relaxation algorithm for semi-linear parabolic partial differential equations

We report a new parallel iterative algorithm for semi-linear parabolic partial differential equations (PDEs) by combining a kind of waveform relaxation (WR) techniques into the classical parareal algorithm. The parallelism can be simultaneously exploited by WR and parareal in different directions. We provide sharp error estimations for the new algorithm on bounded time domain and on unbounded time domain, respectively. The iterations of the parareal and the WR are balanced to optimize the performance of the algorithm. Furthermore, the speedup and the parallel efficiency of the new approach are analyzed. Numerical experiments are carried out to verify the effectiveness of the theoretic work.     

Discrete-time waveform relaxation Volterra-Runge-Kutta methods: Convergence analysis

The discrete-time relaxation methods based on Volterra-Runge-Kutta methods for solving large system of second-kind Volterra integral equations are proposed. Convergence of the discrete-time iteration process with particular attention to parallel methods is investigated.     

Adams methods for neutral functional differential equations

Summary In this paper Adams type methods for the special case of neutral functional differential equations are examined. It is shown thatk-step methods maintain orderk+1 for sufficiently small step size in a sufficiently smooth situation. However, when these methods are applied to an equation with a non-smooth solution the order of convergence is only one. Some computational considerations are given and numerical experiments are presented.     

Parallel frontal methods for ODE's

This paper concerns parallel frontal predictor-corrector methods. Order and stability of these methods are investigated, when the corrector is solved both by the fixed point iteration method and by the Newton method.This work has been partially supported by the Italian C.N.R. within the Finalized Project Sistemi Informatici e Calcolo Parallelo.     

On symmetrizers for Gauss methods

Summary In this paper the maximum attainable order of a special class of symmetrizers for Gauss methods is studied. In particular, it is shown that a symmetrizer of this type for thes-stage Gauss method can attain order 2s-1 only for 1 s 3, and that these symmetrizers areL-stable. A classification of the maximum attainable order of symmetrizers for some higher stages is presented. AnL-stable symmetrizer is also shown to exist for each of the methods studied.     

Convergence of general linear methods on differential-algebraic systems of index 3

Many numerical methods used to solve ordinary differential equations or differential-algebraic equations can be written as general linear methods. The purpose of this paper is to extend the known convergence results for Runge-Kutta and linear multistep methods to a large class of new promising numerical schemes. The theoretical results are illustrated by some numerical experiments.