56 research outputs found
Numerical integrators for motion under a strong constraining force
This paper deals with the numerical integration of Hamiltonian systems in
which a stiff anharmonic potential causes highly oscillatory solution behavior
with solution-dependent frequencies. The impulse method, which uses micro- and
macro-steps for the integration of fast and slow parts, respectively, does not
work satisfactorily on such problems. Here it is shown that variants of the
impulse method with suitable projection preserve the actions as adiabatic
invariants and yield accurate approximations, with macro-stepsizes that are not
restricted by the stiffness parameter
Structure preserving Stochastic Impulse Methods for stiff Langevin systems with a uniform global error of order 1 or 1/2 on position
Impulse methods are generalized to a family of integrators for Langevin
systems with quadratic stiff potentials and arbitrary soft potentials. Uniform
error bounds (independent from stiff parameters) are obtained on integrated
positions allowing for coarse integration steps. The resulting integrators are
explicit and structure preserving (quasi-symplectic for Langevin systems)
From efficient symplectic exponentiation of matrices to symplectic integration of high-dimensional Hamiltonian systems with slowly varying quadratic stiff potentials
We present a multiscale integrator for Hamiltonian systems with slowly
varying quadratic stiff potentials that uses coarse timesteps (analogous to
what the impulse method uses for constant quadratic stiff potentials). This
method is based on the highly-non-trivial introduction of two efficient
symplectic schemes for exponentiations of matrices that only require O(n)
matrix multiplications operations at each coarse time step for a preset small
number n. The proposed integrator is shown to be (i) uniformly convergent on
positions; (ii) symplectic in both slow and fast variables; (iii) well adapted
to high dimensional systems. Our framework also provides a general method for
iteratively exponentiating a slowly varying sequence of (possibly high
dimensional) matrices in an efficient way
A mollified Ensemble Kalman filter
It is well recognized that discontinuous analysis increments of sequential
data assimilation systems, such as ensemble Kalman filters, might lead to
spurious high frequency adjustment processes in the model dynamics. Various
methods have been devised to continuously spread out the analysis increments
over a fixed time interval centered about analysis time. Among these techniques
are nudging and incremental analysis updates (IAU). Here we propose another
alternative, which may be viewed as a hybrid of nudging and IAU and which
arises naturally from a recently proposed continuous formulation of the
ensemble Kalman analysis step. A new slow-fast extension of the popular
Lorenz-96 model is introduced to demonstrate the properties of the proposed
mollified ensemble Kalman filter.Comment: 16 pages, 6 figures. Minor revisions, added algorithmic summary and
extended appendi
Numerical Integrators for Highly Oscillatory Hamiltonian Systems: A Review
Numerical methods for oscillatory, multi-scale Hamiltonian systems are reviewed. The construction principles are described, and the algorithmic and analytical distinction between problems with nearly constant high frequencies and with time- or state-dependent frequencies is emphasized. Trigonometric integrators for the first case and adiabatic integrators for the second case are discussed in more detail
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