1961
DOI: 10.1007/bf01386037
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Numerical integration of ordinary differential equations based on trigonometric polynomials

Abstract: There are many numerical methods available for the step-by-step integration of ordinary differential equations. Only few of them, however, take advantage of special properties of the solution that may be known in advance. Examples of such methods are those developed by BROCK and MURRAY [9], and by DENNIS Eg], for exponential type solutions, and a method by URABE and MISE [b~ designed for solutions in whose Taylor expansion the most significant terms are of relatively high order. The present paper is concerned … Show more

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Cited by 388 publications
(236 citation statements)
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“…Approximating the nonlinear force f (y) over a time step by a suitable constant vector leads to a scheme whose origins for scalar equations can be traced back to [10]:…”
Section: Newtonian Equations Of Motionmentioning
confidence: 99%
“…Approximating the nonlinear force f (y) over a time step by a suitable constant vector leads to a scheme whose origins for scalar equations can be traced back to [10]:…”
Section: Newtonian Equations Of Motionmentioning
confidence: 99%
“…In the present paper, we propose a new variant of the Gautschi-type integrator, see [20] and further developments in [19], for reducing the number of time steps when solving a nonlinear wave equation. In order to reduce the number of spatial grid points, we introduce a physically motivated quasi-envelope approach (QEA).…”
Section: Introductionmentioning
confidence: 99%
“…15 Conversely, it can be shown that a system is locally Hamiltonian if its flow is symplectic. 16 Moreover, the set of all Hamiltonian systems is closed under transformations of coordinates with symplectic functions, and every function which maps a Hamiltonian system to a Hamiltonian system is symplectic. 17 Therefore, the notions of canonical transformations (i.e.…”
Section: Appendix B Hamiltonian Systems and Symplecticitymentioning
confidence: 99%
“…This paper tackles this long-standing issue, and proposes the use of a semianalytical integrator derived from [16,11] to reliably produce three orders of magnitude larger time steps in MD than regular integrators [60], for a resulting 30-fold speedup on average. We demonstrate the efficiency and scalability of our explicit, structure-preserving, and easily parallelizable approach on various typical MD simulation runs, varying from DNA unfolding and protein folding to nanotube resonators.…”
Section: Introductionmentioning
confidence: 99%
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