Abstract. We consider canonical partitioned Runge-Kutta methods for separable Hamiltonians H = T(ß) + Viq) and canonical Runge-Kutta-Nyström methods for Hamiltonians of the form H = ^pTM~lp + Viq) with M a diagonal matrix. We show that for explicit methods there is great simplification in their structure. Canonical methods of orders one through four are constructed. Numerical experiments indicate the suitability of canonical numerical schemes for long-time integrations.
We consider canonical partitioned Runge-Kutta methods for separable Hamiltonians H = T(ß) + Viq) and canonical Runge-Kutta-Nyström methods for Hamiltonians of the form H = ^pTM~lp + Viq) with M a diagonal matrix. We show that for explicit methods there is great simplification in their structure. Canonical methods of orders one through four are constructed. Numerical experiments indicate the suitability of canonical numerical schemes for long-time integrations.
Symplectic numerical integrators, such as the Störmer–Verlet method, are useful in preserving properties that are not preserved by conventional numerical integrators. This paper analyzes the Störmer–Verlet method as applied to the simple harmonic model, whose generalization is an important model for molecular dynamics simulations. Restricting our attention to the one -dimensional case, both the exact solution and the Störmer–Verlet solution to this model are expressed as functions of the number of time steps taken, and then both of these functions are interpreted geometrically. The paper shows the existence of an upper bound on the error from the Störmer–Verlet method, and then an example is worked to demonstrate the closeness of this bound.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.