A COMPARISON OF DIFFERENT NUMERICAL PROPAGATION SCHEMES FOR SOLVING THE TIME-DEPENDENT SCHRODINGER-EQUATION IN THE POSITION REPRESENTATION IN ONE-DIMENSION FOR MIXED QUANTUM-DYNAMICS AND MOLECULAR-DYNAMICS SIMULATIONS
Sr. Billeter et Wf. Vangunsteren, A COMPARISON OF DIFFERENT NUMERICAL PROPAGATION SCHEMES FOR SOLVING THE TIME-DEPENDENT SCHRODINGER-EQUATION IN THE POSITION REPRESENTATION IN ONE-DIMENSION FOR MIXED QUANTUM-DYNAMICS AND MOLECULAR-DYNAMICS SIMULATIONS, Molecular simulation, 15(5), 1995, pp. 301-322
Various numerical integration schemes to calculate the propagation of
a state following the time-dependent Schrodinger equation in the one d
imensional position representation are presented and compared to each
other. Three potentials have been used: a harmonic, a double-well and
a zero potential. Eigenstates and a coherent state have been chosen as
initial states. Special attention has been given to the long-time sta
bility of the algorithms. These are: kinetic referenced split operator
(KRSO), kinetic referenced Cayley (KRC), distributed approximating fu
nctions (DAF), Chebysheff expansion (CH), residuum minimization (RES),
second-order differencing (SOD), an eigenstate expansion (EE) and a c
orrected kinetic referenced split operator (CKRSO). In addition, a spe
edup of the KRC and KRSO methods is presented which is specially suite
d when very few grid points are used. Numerical results are compared t
o analytically calculated values. Mixed classical/quantum mechanical s
imulations require a representation of the quantum state on a limited
number of grid points, classical integration time steps of about one f
emtosecond and compatibility with methods to solve the time-ordering p
roblem. For the considered potentials which differ quite essentially f
rom the potentials used for scattering problems in particle physics, t
he EE method has been found to be faster, more accurate and more stabl
e than the other methods if only a few grid points are required. Other
wise, good results have been obtained with KRC, KRSO, CH, DAF and RES.
SOD has been found to be too slow, and CKRSO is not stable enough for
long simulation times.