One-leg variable-coefficient formulas for ordinary differential equations and local–global step size control

In this paper we discuss a class of numerical algorithms termed one-leg methods. This concept was introduced by Dahlquist in 1975 with the purpose of studying nonlinear stability properties of multistep methods for ordinary differential equations. Later, it was found out that these methods are themselves suitable for numerical integration because of good stability. Here, we investigate one-leg formulas on nonuniform grids. We prove that there exist zero-stable one-leg variable-coefficient methods at least up to order 11 and give examples of two-step methods of orders 2 and 3. In this paper we also develop local and global error estimation techniques for one-leg methods and implement them with the local–global step size selection suggested by Kulikov and Shindin in 1999. The goal of this error control is to obtain automatically numerical solutions for any reasonable accuracy set by the user. We show that the error control is more complicated in one-leg methods, especially when applied to stiff problems. Thus, we adapt our local–global step size selection strategy to one-leg methods.     

刚性延迟积分微分方程单支方法的B-收敛性

本文研究刚性延迟积分微分方程单支方法的B-收敛性,结果表明：A-稳定的单支方法是B-收敛的,其B-收敛阶等于其经典相容阶．最后的数值试验验证了上述理论结果．     

PARALLEL ALGORITHMS OF ONE-LEG METHOD AND ITERATED DEFECT CORRECTION METHODS

The parallel algorithms of iterated defect correction methods (PIDeCM's) are constructed, which are of efficiency and high order B-convergence for general nonlinear stiff systems in ODE'S. As the basis of constructing and discussing PIDeCM's. a class of parallel one-leg methods is also investigated, which are of particular efficiency for linear systems.     

A family of A-stable Runge Kutta collocation methods of higher order for initial-value problems

^{We consider the construction of a special family of Runge–Kutta(RK) collocation methods based on intra-step nodal points ofChebyshev–Gauss–Lobatto type, with A-stability andstiffly accurate characteristics. This feature with its inherentimplicitness makes them suitable for solving stiff initial-valueproblems. In fact, the two simplest cases consist in the well-knowntrapezoidal rule and the fourth-order Runge–Kutta–LobattoIIIA method. We will present here the coefficients up to eighthorder, but we provide the formulas to obtain methods of higherorder. When the number of stages is odd, we have considereda new strategy for changing the step size based on the use ofa pair of methods: the given RK method and a linear multistepone. Some numerical experiments are considered in order to checkthe behaviour of the methods when applied to a variety of initial-valueproblems.}     

Precisely A(α)-Stable One-Leg Multistep Methods

One-Leg Multistep (OLM) methods for initial value problems in ODEs use a nonlinear multistep formula to compute the solution at the next integration point. This paper shows that there exists an evaluation point t ^* which gives an OLM formula more precise than BDF's and (almost) precisely A()-stable for a k-step method (k6), and whose stability angle is essentially similar to BDF's. The stability region can be further improved by applying the corrector idea of Klopfenstein.This revised version was published online in October 2005 with corrections to the Cover Date.     

Rational Runge-Kutta methods are not suitable for stiff systems of ODEs

The present paper shows that rational RK-methods are not very appropriate to solve stiff differential equations. The CA₀-stability (i.e. componentwise contractivity) is defined and the non-existence of CA₀-stable rational RK-methods is demonstrated. Furthermore it is shown that the stepsizes which can be expected when solving a stiff differential system with a rational or with an explicit linear RK-method are of the same order of magnitude.     

Error of One-leg Methods for Singular Perturbation Problems with Delays

This paper is concerned with the error behaviour of one-leg methods applied to some classes of one-parameter multiple stiff singularly perturbed problems with delays. We derive the global error estimates of A-stable one-leg methods with linear interpolation procedure.     

Convergence of one-leg methods for singular perturbation problems with delays

This paper is concerned with the error behaviour of one-leg methods applied to some classes of one-parameter multiple stiff singularly perturbed problems with delays. We obtain convergence results of A-stable one-leg methods with linear interpolation procedure. Numerical experiments further confirm our theoretical analysis.     

Runge-Kutta Methods for the Numerical Solution of Stiff Semilinear Systems

This paper studies the stability and convergence properties of general Runge-Kutta methods when they are applied to stiff semilinear systems y(t) = J(t)y(t) + g(t, y(t)) with the stiffness contained in the variable coefficient linear part.We consider two assumptions on the relative variation of the matrix J(t) and show that for each of them there is a family of implicit Runge-Kutta methods that is suitable for the numerical integration of the corresponding stiff semilinear systems, i.e. the methods of the family are stable, convergent and the stage equations possess a unique solution. The conditions on the coefficients of a method to belong to these families turn out to be essentially weaker than the usual algebraic stability condition which appears in connection with the B-stability and convergence for stiff nonlinear systems. Thus there are important RK methods which are not algebraically stable but, according to our theory, they are suitable for the numerical integration of semilinear problems.This paper also extends previous results of Burrage, Hundsdorfer and Verwer on the optimal convergence of implicit Runge-Kutta methods for stiff semilinear systems with a constant coefficients linear part.     

A semi-lagrangian numerical method for geometric optics type problems

Linear multistep methods (LMMs) are written as irreducible general linear methods (GLMs). A-stable LMMs are shown to be algebraically stable GLMs for strictly positive definite G-matrices. Optimal order error bounds, independent of stiffness, are derived for A-stable methods, without considering one-leg methods (OLMs). As a GLM, the OLM is shown to be the transpose of the LMM. For A-stable methods, the LMM G-matrix is the inverse of the OLM G-matrix. Examples of G-symplectic LMMs are given. AMS subject classification (2000) 65L20     

SERK2v2: A new second‐order stabilized explicit Runge‐Kutta method for stiff problems

Traditionally, explicit numerical algorithms have not been used with stiff ordinary differential equations (ODEs) due to their stability. Implicit schemes are usually very expensive when used to solve systems of ODEs with very large dimension. Stabilized Runge‐Kutta methods (also called Runge–Kutta–Chebyshev methods) were proposed to try to avoid these difficulties. The Runge–Kutta methods are explicit methods with extended stability domains, usually along the negative real axis. They can easily be applied to large problem classes with low memory demand, they do not require algebra routines or the solution of large and complicated systems of nonlinear equations, and they are especially suited for discretizations using the method of lines of two and three dimensional parabolic partial differential equations. In Martín‐Vaquero and Janssen [Comput Phys Commun 180 (2009), 1802–1810], we showed that previous codes based on stabilized Runge–Kutta algorithms have some difficulties in solving problems with very large eigenvalues and we derived a new code, SERK2, based on sixth‐order polynomials. Here, we develop a new method based on second‐order polynomials with up to 250 stages and good stability properties. These methods are efficient numerical integrators of very stiff ODEs. Numerical experiments with both smooth and nonsmooth data support the efficiency and accuracy of the new algorithms when compared to other well‐known second‐order methods such as RKC and ROCK2. © 2012 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 2013     

Positivity for explicit two-step methods in linear multistep and one-leg form

Positivity results are derived for explicit two-step methods in linear multistep form and in one-leg form. It turns out that, using the forward Euler starting procedure, the latter form allows a slightly larger step size with respect to positivity. AMS subject classification (2000) 65L06     

Multi-Implicit Peer Two-Step W-Methods for Parallel Time Integration

Peer two-step W-methods are designed for integration of stiff initial value problems with parallelism across the method. The essential feature is that in each time step s ‘peer’ approximations are employed having similar properties. In fact, no primary solution variable is distinguished. Parallel implementation of these stages is easy since information from one previous time step is used only and the different linear systems may be solved simultaneously. This paper introduces a subclass having order s−1 where optimal damping for stiff problems is obtained by using different system parameters in different stages. Favourable properties of this subclass are uniform stability for realistic stepsize sequences and a superconvergence property which is proved using a polynomial collocation formulation. Numerical tests on a shared memory computer of a matrix-free implementation with Krylov methods are included. AMS subject classification (2000) 65L06, 65Y05.Received June 2004. Revised January 2005. Communicated by Timo Eirola.Helmut Podhaisky: The work of this author was supported by the German Academic Exchange Service, DAAD.     

非线性刚性变延迟微分方程单支方法的数值稳定性

现有文献中对于非线性延迟微分方程渐近稳定性及其数值方法的稳定性研究大都局限于常延迟的情形,例如可参见匡蛟勋[1-3],黄乘明[4],Torelli[5]等人的大量工作.1994年A.Iserles[6] 首次研究了比例延迟微分方程数值方法的线性稳定性,随后有相当多的文献对比例延迟微分方程的各种数值方法的线性稳定性进行了讨论.1997年Zennaro[7]首次研究了非线性刚性变延迟微分方程的渐近稳定性,但该文中对于延迟量的限制十分苛刻,同时该文也首次研究了非线性刚性变延迟微分方程Runge-Kutta方法的非线性稳定性. 本文目的是试图在上述基础上进一步研究非线性刚性变延迟微分方程的渐近稳定性及其数值方法的稳定性.首先在第二节我们给出了非线性刚性变延迟微分方程模型问题（2.1）渐     

A CLASS OF r-POINT (r+1)ST-ORDER A-STABLE ONE-BLOCK METHODS WITH DAMPING AT THE INFINITE POINT

1　ＩｎｔｒｏｄｕｃｔｉｏｎＦｏｒｓｏｌｖｉｎｇｓｔｉｆｆｉｎｉｔｉａｌｖａｌｕｅｐｒｏｂｌｅｍｓｆｏｒｓｙｓｔｅｍｓｏｆＯＤＥｓｙ′=ｆ(ｙ) ,ｙ(ｔ0 ) =ｙ0 ,ｔ0 <ｔ≤Ｔ ,ｙ0 ,ｙ∈Ｒｍ,ｆ :Ω Ｒｍ →Ｒｍ (1 .1 )ｍａｎｙｐａｒｔｉｃｕｌａｒｏｎｅ ｂｌｏｃｋｍｅｔｈｏｄｓｏｆｔｈｅｆｏｒｍＹｎ+1= ＡＹｎ+ｈ( Ｂ0 Ｆ(Ｙｎ) + Ｂ1Ｆ(Ｙｎ+1) ) , Ａ =Ａ Ｉｍ, Ｂｉ=Ｂｉ Ｉｍ,Ａ ,Ｂｉ∈Ｒｒ×ｒ,Ｙｎ =(ＹＴｎｒ,… ,ｙＴ(ｎ+1)ｒ- 1) Ｔ,Ｆ(Ｙｎ) =(ｆＴ(ｙｎｒ) ,… ,ｆＴ(ｙ(ｎ+1)ｒ- 1) ) Ｔ,ｙｊ≈ ｙ(ｔｊ) ,…     

Four-stage symplectic and P-stable SDIRKN methods with dispersion of high order

New SDIRKN methods specially adapted to the numerical integration of second-order stiff ODE systems with periodic solutions are obtained. Our interest is focused on the dispersion (phase errors) of the dominant components in the numerical oscillations when these methods are applied to the homogeneous linear test model. Based on this homogeneous test model we derive the dispersion and P-stability conditions for SDIRKN methods which are assumed to be zero dissipative. Two four-stage symplectic and P-stable methods with algebraic order 4 and high order of dispersion are obtained. One of the methods is symmetric and sixth-order dispersive whereas the other method is nonsymmetric and eighth-order dispersive. These methods have been applied to a number of test problems (linear as well as nonlinear) and some numerical results are presented to show their efficiency when they are compared with other methods derived by Sharp et al. [IMA J. Numer. Anal. 10 (1990) 489–504].     

Choice of strategies for extrapolation with symmetrization in the constant stepsize setting

Symmetrization has been shown to be efficient in solving stiff problems. In the constant stepsize setting, we study four ways of applying extrapolation with symmetrization. We observe that for stiff linear problems the symmetrized Gauss methods are more efficient than the symmetrized Lobatto IIIA methods of the same order. However, for two-dimensional nonlinear problems, the symmetrized 4-stage Lobatto IIIA method is more efficient. In all cases, we observe numerically that passive symmetrization with passive extrapolation is more efficient than active symmetrization with active extrapolation.     

Dahlquist’s classical papers on stability theory

This text, which is based on the author’s talk in honour of G. Dahlquist at the SciCade05 meeting in Nagoya, describes the two classical papers from 1956 and 1963 of Dahlquist and their enormous impact on the research of decades to come; it also allows the author to present a personal testimony of his never ending admiration for the scientific and personal qualities of this great man.In memory of Germund Dahlquist (1925–2005).AMS subject classification (2000) 65F05, 65F07     

Fourth-Order Symmetric DIRK Methods for Periodic Stiff Problems

New symmetric DIRK methods specially adapted to the numerical integration of first-order stiff ODE systems with periodic solutions are obtained. Our interest is focused on the dispersion (phase errors) of the dominant components in the numerical oscillations when these methods are applied to the homogeneous linear test model. Based on this homogeneous test model we derive the dispersion conditions for symmetric DIRK methods as well as symmetric stability functions with real poles and maximal dispersion order. Two new fourth-order symmetric methods with four and five stages are obtained. One of the methods is fourth-order dispersive whereas the other method is symplectic and sixth-order dispersive. These methods have been applied to a number of test problems (linear as well as nonlinear) and some numerical results are presented to show their efficiency when they are compared with the symplectic DIRK method derived by Sanz-Serna and Abia (SIAM J. Numer. Anal. 28 (1991) 1081–1096).     

求解刚性Volterra延迟积分微分方程的隐显单支方法的稳定性与误差分析

本文主要研究用隐显单支方法求解一类刚性Volterra延迟积分微分方程初值问题时的稳定性与误差分析.我们获得并证明了结论:若隐显单支方法满足2阶相容条件,且其中的隐式单支方法是A-稳定的,则隐显单支方法是2阶收敛且关于初值扰动是稳定的.最后,由数值算例验证了相关结论.