Nonlinear stability issues for stochastic Runge-Kutta methods

Abstract The paper provides a nonlinear stability analysis for a class of stochastic Runge-Kutta methods, applied to problems generating mean-square contractive solutions. In particular, we show how this property is inherited along the solutions generated by the stochastic perturbation of an algebraically stable deterministic Runge-Kutta method. The effectiveness of the results is also confirmed by selected numerical experiments.

[1]  Kevin Burrage,et al.  A bound on the maximum strong order of stochastic Runge-Kutta methods for stochastic ordinary differential equations , 1997 .

[2]  G. Dahlquist Error analysis for a class of methods for stiff non-linear initial value problems , 1976 .

[3]  Kevin Burrage,et al.  Structure-preserving Runge-Kutta methods for stochastic Hamiltonian equations with additive noise , 2013, Numerical Algorithms.

[4]  Desmond J. Higham,et al.  Numerical methods for nonlinear stochastic differential equations with jumps , 2005, Numerische Mathematik.

[5]  E. Hairer,et al.  Solving Ordinary Differential Equations II: Stiff and Differential-Algebraic Problems , 2010 .

[6]  Evelyn Buckwar,et al.  Stochastic Runge-Kutta methods with deterministic high order for ordinary differential equations , 2013 .

[7]  Raffaele D'Ambrosio,et al.  A-stability preserving perturbation of Runge-Kutta methods for stochastic differential equations , 2020, Appl. Math. Lett..

[8]  Kristian Debrabant,et al.  B-Series Analysis of Stochastic Runge-Kutta Methods That Use an Iterative Scheme to Compute Their Internal Stage Values , 2008, SIAM J. Numer. Anal..

[9]  Tianhai Tian,et al.  Implicit Stochastic Runge–Kutta Methods for Stochastic Differential Equations , 2004 .

[10]  Andreas Rößler,et al.  Runge–Kutta Methods for Itô Stochastic Differential Equations with Scalar Noise , 2006 .

[11]  Evelyn Buckwar,et al.  Stochastic Runge--Kutta Methods for It[o-circumflex] SODEs with Small Noise , 2010, SIAM J. Sci. Comput..

[12]  Raffaele D'Ambrosio,et al.  Drift-preserving numerical integrators for stochastic Hamiltonian systems , 2020, Adv. Comput. Math..

[13]  S. Zacks,et al.  Introduction to stochastic differential equations , 1988 .

[14]  P. Kloeden,et al.  Numerical Solution of Stochastic Differential Equations , 1992 .

[15]  Desmond J. Higham,et al.  Exponential mean square stability of numerical solutions to stochastic differential equations , 2003 .

[16]  W. Rüemelin Numerical Treatment of Stochastic Differential Equations , 1982 .

[17]  Kevin Burrage,et al.  Order Conditions of Stochastic Runge-Kutta Methods by B-Series , 2000, SIAM J. Numer. Anal..

[18]  F. Costabile,et al.  Economical Runge–Kutta methods for numerical solution of stochastic differential equations , 2008 .

[19]  Andreas Rößler,et al.  Runge-Kutta Methods for the Strong Approximation of Solutions of Stochastic Differential Equations , 2010, SIAM J. Numer. Anal..

[20]  Kevin Burrage,et al.  Low rank Runge-Kutta methods, symplecticity and stochastic Hamiltonian problems with additive noise , 2012, J. Comput. Appl. Math..

[21]  R. D'Ambrosio,et al.  On the numerical structure preservation of nonlinear damped stochastic oscillators , 2020, Numerical Algorithms.

[22]  K. Debrabant,et al.  General order conditions for stochastic partitioned Runge–Kutta methods , 2017, BIT Numerical Mathematics.