We revisit an algorithm by Skeel et al. [5,16] for computing the modified, or shadow, energy associated with symplectic discretizations of Hamiltonian systems. We amend the algorithm to use Richardson extrapolation in order to obtain arbitrarily high order of accuracy. Error estimates show that the new method captures the exponentially small drift associated with such discretizations. Several numerical examples illustrate the theory
For Hamiltonian systems, simulation algorithms that exactly conserve numerical energy or pseudo-ener...
Machine learning methods are widely used in the natural sciences to model and predict physical syste...
In this paper we apply some higher order symplectic numerical methods to analyze the dynamics of 3-s...
Abstract. We revisit an algorithm by Skeel et al. [5, 16] for computing the modified, or shadow, ene...
We conduct a systematic comparison of spectral methods with some symplectic methods in solving Hamil...
In long-time numerical integration of Hamiltonian systems, and especially in molecular dynamics simu...
In molecular dynamics Hamiltonian systems of dierential equations are numerically integrated using t...
Full-text article is free to read on the publisher website. In this paper we extend the ideas of Bru...
In long-time numerical integration of Hamiltonian systems, and especially in molecular dynamics simu...
We reconsider the problem of the Hamiltonian interpolation of symplectic mappings. Following Moser's...
Many force–gradient explicit symplectic integration algorithms have been designed for the Hamiltonia...
Several symplectic splitting methods of orders four and six are presented for the step-by-step time ...
Hamiltonian systems typically arise as models of conservative physical systems and have many applica...
We reconsider the problem of the Hamiltonian interpolation of symplectic mappings. Following Moser's...
We prove that a class of A-stable symplectic Runge--Kutta time semidiscretizations (including the Ga...
For Hamiltonian systems, simulation algorithms that exactly conserve numerical energy or pseudo-ener...
Machine learning methods are widely used in the natural sciences to model and predict physical syste...
In this paper we apply some higher order symplectic numerical methods to analyze the dynamics of 3-s...
Abstract. We revisit an algorithm by Skeel et al. [5, 16] for computing the modified, or shadow, ene...
We conduct a systematic comparison of spectral methods with some symplectic methods in solving Hamil...
In long-time numerical integration of Hamiltonian systems, and especially in molecular dynamics simu...
In molecular dynamics Hamiltonian systems of dierential equations are numerically integrated using t...
Full-text article is free to read on the publisher website. In this paper we extend the ideas of Bru...
In long-time numerical integration of Hamiltonian systems, and especially in molecular dynamics simu...
We reconsider the problem of the Hamiltonian interpolation of symplectic mappings. Following Moser's...
Many force–gradient explicit symplectic integration algorithms have been designed for the Hamiltonia...
Several symplectic splitting methods of orders four and six are presented for the step-by-step time ...
Hamiltonian systems typically arise as models of conservative physical systems and have many applica...
We reconsider the problem of the Hamiltonian interpolation of symplectic mappings. Following Moser's...
We prove that a class of A-stable symplectic Runge--Kutta time semidiscretizations (including the Ga...
For Hamiltonian systems, simulation algorithms that exactly conserve numerical energy or pseudo-ener...
Machine learning methods are widely used in the natural sciences to model and predict physical syste...
In this paper we apply some higher order symplectic numerical methods to analyze the dynamics of 3-s...