33 research outputs found
Polynomial propagators for classical molecular dynamics
Classical molecular dynamics simulation is performed mostly using the established velocity Verlet integrator or other symplectic propagation schemes. In this work, an alternative formulation of numerical propagators for classical molecular dynamics is introduced based on an expansion of the time evolution operator in series of Chebyshev and Newton polynomials. The suggested propagators have, in principle, arbitrary order of accuracy which can be controlled by the choice of expansion order after that the series is truncated. However, the expansion converges only after a minimum number of terms is included in the expansion and this number increases linearly with the time step size. Measurements of the energy drift demonstrate the acceptable long-time stability of the polynomial propagators. It is shown that a system of interacting Lennard-Jones particles is tractable by the proposed technique and that the scaling with the expansion order is only polynomial while the scaling with the number of particles is the same as with the conventional velocity Verlet. The proposed method is, in principle, extendable for further interaction force fields and for integration with a thermostat, and can be parallelized to speed up the computation of every time step
Efficiency of different numerical methods for solving Redfield equations
The numerical efficiency of different schemes for solving the Liouville-von
Neumann equation within multilevel Redfield theory has been studied. Among the
tested algorithms are the well-known Runge-Kutta scheme in two different
implementations as well as methods especially developed for time propagation:
the Short Iterative Arnoldi, Chebyshev and Newtonian propagators. In addition,
an implementation of a symplectic integrator has been studied. For a simple
example of a two-center electron transfer system we discuss some aspects of the
efficiency of these methods to integrate the equations of motion. Overall for
time-independent potentials the Newtonian method is recommended. For
time-dependent potentials implementations of the Runge-Kutta algorithm are very
efficient
Stochastic unraveling of Redfield master equations and its application to electron transfer problems
A method for stochastic unraveling of general time-local quantum master
equations (QMEs) is proposed. The present kind of jump algorithm allows a
numerically efficient treatment of QMEs which are not in Lindblad form, i.e.
are not positive semidefinite by definition. The unraveling can be achieved by
allowing for trajectories with negative weights. Such a property is necessary,
e.g. to unravel the Redfield QME and to treat various related problems with
high numerical efficiency. The method is successfully tested on the damped
harmonic oscillator and on electron transfer models including one and two
reaction coordinates. The obtained results are compared to those from a direct
propagation of the reduced density matrix (RDM) as well as from the standard
quantum jump method. Comparison of the numerical efficiency is performed
considering both the population dynamics and the RDM in the Wigner phase space
representation.Comment: accepted in J. Chem. Phys.; 26 pages, 6 figures; the order of
authors' names on the title page correcte
A density matrix approach to photoinduced electron injection
Electron injection from an adsorbed molecule to the substrate (heterogeneous
electron transfer) is studied. One reaction coordinate is used to model this
process. The surface phonons and/or the electron-hole pairs together with the
internal degrees of freedom of the adsorbed molecule as well as possibly a
liquid surrounding the molecule provide a dissipative environment, which may
lead to dephasing, relaxation, and sometimes excitation of the relevant system.
In the process studied the adsorbed molecule is excited by a light pulse. This
is followed by an electron transfer from the excited donor state to the
quasi-continuum of the substrate. It is assumed that the substrate is a
semiconductor. The effects of dissipation on electron injection are
investigated
Pt nanoparticles under oxidizing conditions – implications of particle size, adsorption sites and oxygen coverage on stability
Platinum nanoparticles are efficient catalysts for different reactions, such as oxidation of carbon and nitrogen monoxides. Adsorption and interaction of oxygen with the nanoparticle surface, taking place under reaction conditions, determine not only the catalytic efficiency but also the stability of the nanoparticles against oxidation. In this study, platinum nanoparticles in oxygen environment are investigated by systematic screening of initial nanoparticle–oxygen configurations and employing density functional theory and a thermodynamics-based approach. The structures formed at low oxygen coverages are described by adsorption of atomic oxygen on the nanoparticles whereas at high coverages oxide-like species are formed. The relative stability of adsorption configurations at different oxygen coverages, including the phase of fully oxidized nanoparticles, is investigated by constructing p–T phase diagrams for the studied systems
Computational Methods in Science and Engineering : Proceedings of the Workshop SimLabs@KIT, November 29 - 30, 2010, Karlsruhe, Germany
In this proceedings volume we provide a compilation of article contributions equally covering applications from different research fields and ranging from capacity up to capability computing. Besides classical computing aspects such as parallelization, the focus of these proceedings is on multi-scale approaches and methods for tackling algorithm and data complexity. Also practical aspects regarding the usage of the HPC infrastructure and available tools and software at the SCC are presented