Approximate compositions of a near identity map by multi-revolution Runge-Kutta methods

Summary.The so-called multi-revolution methods were introduced in celestial mechanics as an efficient tool for the long-term numerical integration of nearly periodic orbits of artificial satellites around the Earth. A multi-revolution method is an algorithm that approximates the map φTN of N near-periods T in terms of the one near-period map φT evaluated at few s << N selected points. More generally, multi-revolution methods aim at approximating the composition φN of a near identity map φ. In this paper we give a general presentation and analysis of multi-revolution Runge-Kutta (MRRK) methods similar to the one developed by Butcher for standard Runge-Kutta methods applied to ordinary differential equations. Order conditions, simplifying assumptions, and order estimates of MRRK methods are given. MRRK methods preserving constant Poisson/symplectic structures and reversibility properties are characterized. The construction of high order MRRK methods is described based on some families of orthogonal polynomials.

[1]  Ernst Hairer,et al.  Solving Ordinary Differential Equations I: Nonstiff Problems , 2009 .

[2]  L. H. Thomas,et al.  An extrapolation formula for stepping the calculation of the orbit of an artificial satellite several revolutions time , 1960 .

[3]  Jacob K. White,et al.  Efficient AC and noise analysis of two-tone RF circuits , 1996, DAC '96.

[4]  Jacob K. White,et al.  An envelope-following approach to switching power converter simulation , 1991 .

[5]  E. Hairer,et al.  Geometric Numerical Integration , 2022, Oberwolfach Reports.

[6]  L. Petzold An Efficient Numerical Method for Highly Oscillatory Ordinary Differential Equations , 1978 .

[7]  J. Butcher Implicit Runge-Kutta processes , 1964 .

[8]  Laurent O. Jay,et al.  Structure Preservation for Constrained Dynamics with Super Partitioned Additive Runge-Kutta Methods , 1998, SIAM J. Sci. Comput..

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

[10]  J. Butcher The Numerical Analysis of Ordinary Di erential Equa-tions , 1986 .

[11]  Alberto L. Sangiovanni-Vincentelli,et al.  An envelope-following method for the efficient transient simulation of switching power and filter circuits , 1988, [1988] IEEE International Conference on Computer-Aided Design (ICCAD-89) Digest of Technical Papers.

[12]  Robert P. K. Chan,et al.  On symmetric Runge-Kutta methods of high order , 1991, Computing.

[13]  J. Marsden,et al.  Introduction to mechanics and symmetry , 1994 .

[14]  J. M. Sanz-Serna,et al.  Numerical Hamiltonian Problems , 1994 .

[15]  Linda R. Petzold,et al.  Numerical solution of highly oscillatory ordinary differential equations , 1997, Acta Numerica.

[16]  G. Szegö,et al.  Concerning sets of polynomials orthogonal simultaneously on several circles , 1939 .

[17]  Multirevolution methods for orbit integration , 1974 .

[18]  D. G. Bettis,et al.  Modified multirevolution integration methods for satellite orbit computation , 1975 .

[19]  E. Hairer,et al.  Solving Ordinary ,Differential Equations I, Nonstiff problems/E. Hairer, S. P. Norsett, G. Wanner, Second Revised Edition with 135 Figures, Vol.: 1 , 2000 .

[20]  J. Butcher The numerical analysis of ordinary differential equations: Runge-Kutta and general linear methods , 1987 .

[21]  Manuel Palacios,et al.  A new approach to the construction of multirevolution methods and their implementation , 1997 .

[22]  Rene F. Swarttouw,et al.  Orthogonal polynomials , 2020, NIST Handbook of Mathematical Functions.

[23]  F. Krogh,et al.  Solving Ordinary Differential Equations , 2019, Programming for Computations - Python.

[24]  G. P. Taratynova Numerical Solution of Equations of Finite Differences and Their Application to the Calculation of Orbits of Artificial Earth Satellites , 1961 .