Stability radius of polynomials occurring in the numerical solution of initial value problems

This paper deals with polynomial approximations(x) to the exponential function exp(x) related to numerical procedures for solving initial value problems. Motivated by stability requirements, we present a numerical study of the largest diskD()={z C: |z+|} that is contained in the stability regionS()={z C: |(z)|1}. The radius of this largest disk is denoted byr(), the stability radius. On the basis of our numerical study, several conjectures are made concerningr _m,p=sup {r(): _m,p}. Here _{m, p} (1pm; p, m integers) is the class of all polynomials(x) with real coefficients and degree m for which(x)=exp(x)+O(x ^p+1) (forx 0).     

Absolute monotonicity of polynomials occurring in the numerical solution of initial value problems

Summary This paper deals with polynomial approximations ø(x) to the exponential function exp(x) related to numerical procedures for solving initial value problems. Motivated by positivity and contractivity requirements imposed on these numerical procedures we study the smallest negative argument, denoted by –R(ø), at which ø is absolutely monotonic. For given integersp1,m1 we determine the maximum ofR(ø) when ø varies over the class of all polynomials of a degree m with (forx0).     

Norm bounds for rational matrix functions

Summary If the field of values of a matrixA is contained in the left complex halfplaneH and a functionf mapsH into the unit disc then f(A)₂1 by a theorem of J.v. Neumann. We prove a theorem of this type, only the field of values ofA is used for functions which are absolutely bounded by one in only part ofH. An extension can be used to show norm-stability of single step methods for stiff differential equations. The results are applicable among others to several subdiagonal Padé approximations which are notA-stable.     

Stability analysis of numerical methods for delay differential equations

Summary This paper deals with the stability analysis of step-by-step methods for the numerical solution of delay differential equations. We focus on the behaviour of such methods when they are applied to the linear testproblemU(t)=U(t)+U(t–) with >0 and , complex. A general theorem is presented which can be used to obtain complete characterizations of the stability regions of these methods.     

The asymptotic stability of one-parameter methods for neutral differential equations

This paper deals with the asymptotic stability of theoretical solutions and numerical methods for systems of neutral differential equationsx=Ax(t–)+Bx(t)+Cx(t–), whereA, B, andC are constant complexN ×N matrices, and >0. A necessary and sufficient condition such that the differential equations are asymptotically stable is derived. We also focus on the numerical stability properties of adaptations of one-parameter methods. Further, we investigate carefully the characterization of the stability region.     

Absolute monotonicity of rational functions occurring in the numerical solution of initial value problems

Summary This paper deals with rational functions ø(z) approximating the exponential function exp(z) related to numerical procedures for solving initial value problems. Motivated by positivity and contractivity requirements imposed on these numerical procedures we study the greatest nonnegative numberR, denoted byR(ø), such that ø is absolutely monotonic on (–R, 0]. An algorithm for the computation ofR(ø) is presented. Application of this algorithm yields the valueR(ø) for the well-known Padé approximations to exp(z). For some specific values ofm, n andp we determine the maximum ofR(ø) when ø varies over the class of all rational functions ø with degree of the numerator m, degree of the denominator n and ø(z)=exp(z)+(z ^p+1 ) (forz0).     

Variable step size destabilizes the Störmer/leapfrog/verlet method

For fixed step-sizeh the Störmer method is stable for the standard test equationÿ= ² y,>0, if and only ifh<2. We show that for variable step sizeh _n there does not exist a (positive) limit onh which ensures stability. Nor can we guarantee stability if, in addition, we limit the step size ratioh _n/h _n–1.This work was supported in part by National Science Foundation Grant DMS 90 15533.     

Stability properties of collocation methods

Lower bounds for are given for which equidistant s-point collocation methods areA()-stable for arbitrarys.     

Contractivity preserving explicit linear multistep methods

Summary We investigate contractivity properties of explicit linear multistep methods in the numerical solution of ordinary differential equations. The emphasis is on the general test-equation , whereA is a square matrix of arbitrary orders1. The contractivity is analysed with respect to arbitrary norms in thes-dimensional space (which are not necessarily generated by an inner product). For given order and stepnumber we construct optimal multistep methods allowing the use of a maximal stepsize.This research has been supported by the Netherlands organisation for scientific research (NWO)     

A note on contractivity in the numerical solution of initial value problems

This paper concerns the stability analysis of numerical methods for approximating the solutions to (stiff) initial value problems. Our analysis includes the case of (nonlinear) systems of differential equations that are essentially more general than the classical test equationU=U, with a complex constant.We explore the relation between two stability concepts, viz. the concepts of contractivity and weak contractivity.General Runge-Kutta methods, one-stage Rosenbrock methods and a notable rational Runge-Kutta method are analysed in some detail.     

Convergence properties of the Runge-Kutta-Chebyshev method

Summary The Runge-Kutta-Chebyshev method is ans-stage Runge-Kutta method designed for the explicit integration of stiff systems of ordinary differential equations originating from spatial discretization of parabolic partial differential equations (method of lines). The method possesses an extended real stability interval with a length proportional tos ². The method can be applied withs arbitrarily large, which is an attractive feature due to the proportionality of withs ². The involved stability property here is internal stability. Internal stability has to do with the propagation of errors over the stages within one single integration step. This internal stability property plays an important role in our examination of full convergence properties of a class of 1st and 2nd order schemes. Full convergence means convergence of the fully discrete solution to the solution of the partial differential equation upon simultaneous space-time grid refinement. For a model class of linear problems we prove convergence under the sole condition that the necessary time-step restriction for stability is satisfied. These error bounds are valid for anys and independent of the stiffness of the problem. Numerical examples are given to illustrate the theoretical results.Dedicated to Peter van der Houwen for his numerous contributions in the field of numerical integration of differential equations.Paper presented at the symposium Construction of Stable Numerical Methods for Differential and Integral Equations, held at CWI, March 29, 1989, in honor of Prof. Dr. P.J. van der Houwen to celebrate the twenty-fifth anniversary of his stay at CWI     

A-stable spline-collocation methods of multivalue type

In this paper the general classV of spline-collocation methods presented by Mülthei is investigated. The methods ofV approximate solutions of first order initial value problems. ClassV contains as subclass the methods of so-called multivalue type, and in particular contains the generalized singly-implicit methods treated by Butcher.Any multivalue type representativeU V yields a matrix valued function corresponding toU, which characterizes the region of absolute stability ofU. If a sequence (U()) of multivalue type representatives ofV tending to some singlevalue type representative V is considered, it can easily be seen by the structure of , that the sequence of the greatest eigenvalues of the (.,) tends to the stability function corresponding to . This fact allows one to construct one-parameter families of A-stable methods of multivalue type.     

A new interpolation procedure for adapting Runge-Kutta methods to delay differential equations

This paper deals with adapting Runge-Kutta methods to differential equations with a lagging argument. A new interpolation procedure is introduced which leads to numerical processes that satisfy an important asymptotic stability condition related to the class of testproblemsU(t)=U(t)+U(t–) with , C, Re()<–||, and >0. Ifc _i denotes theith abscissa of a given Runge-Kutta method, then in thenth stept _n–1t _n :=t _n–1+h of the numerical process our interpolation procedure computes an approximation toU(t _n–1+c _i h–) from approximations that have already been generated by the process at pointst _j–1+c _i h(j=1,2,3,...). For two of these new processes and a standard process we shall consider the convergence behaviour in an actual application to a given, stiff problem.     

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.     

On the relation between algebraic stability andB-convergence for Runge-Kutta methods

Summary This paper is concerned with the numerical solution of stiff initial value problems for systems of ordinary differential equations using Runge-Kutta methods. For these and other methods Frank, Schneid and Ueberhuber [7] introduced the important concept ofB-convergence, i.e. convergence with error bounds only depending on the stepsizes, the smoothness of the exact solution and the so-called one-sided Lipschitz constant . Spijker [19] proved for the case <0 thatB-convergence follows from algebraic stability, the well-known criterion for contractivity (cf. [1, 2]). We show that the order ofB-convergence in this case is generally equal to the stage-order, improving by one half the order obtained in [19]. Further it is proved that algebraic stability is not only sufficient but also necessary forB-convergence.This study was completed while this author was visiting the Oxford University Computing Laboratory with a stipend from the Netherlands Organization for Scientific Research (N.W.O.)     

Stability of implicit Runge-Kutta methods for nonlinear stiff differential equations

Under the assumption that an implicit Runge-Kutta method satisfies a certain stability estimate for linear systems with constant coefficientsl ₂-stability for nonlinear systems is proved. This assumption is weaker than algebraic stability since it is satisfied for many methods which are not evenA-stable. Some local smoothness in the right hand side of the differential equation is needed, but it may have a Jacobian and higher derivatives with large norms. The result is applied to a system derived from a strongly nonlinear parabolic equation by the method of lines.     

Monotonicity and boundedness in implicit Runge-Kutta methods

Summary This paper concerns the analysis of implicit Runge-Kutta methods for approximating the solutions to stiff initial value problems. The analysis includes the case of (nonlinear) systems of differential equations that are essentially more general than the classical test equationU=U (with a complex constant). The properties of monotonicity and boundedness of a method refer to specific moderate rates of growth of the approximations during the numerical calculations. This paper provides necessary conditions for these properties by using the important concept of algebraic stability (introduced by Burrage, Butcher and by Crouzeix). These properties will also be related to the concept of contractivity (B-stability) and to a weakened version of contractivity.     

A- andB-stability for Runge-Kutta methods-characterizations and equivalence

Summary Using a special representation of Runge-Kutta methods (W-transformation), simple characterizations ofA-stability andB-stability have been obtained in [9, 8, 7]. In this article we will make this representation and their conclusions more transparent by considering the exact Runge-Kutta method. Finally we demonstrate by a numerical example that for difficult problemsB-stable methods are superior to methods which are onlyA-stable.Talk, presented at the conference on the occasion of the 25th anniversary of the founding ofNumerische Mathematik, TU Munich, March 19–21, 1984     

On the stability of backward differentiation methods

Summary The approximation of linear systemsy=–A(t)y+b(t) by backward differentiation methods up to order 5 is considered. It is proved that the error does not increase if the real symmetric matrixA(t) is positive definite andA(t) is negative semi-definite.