Overcoming artificial spatial correlations in simulations of superstructure domain growth with parallel Monte Carlo algorithms
- Univ. Erlangen-Nuernberg (Germany)
The authors study the applicability of parallelized/vectorized Monte Carlo (MC) algorithms to the simulation of domain growth in two-dimensional lattice gas models undergoing an ordering process after a rapid quench below an order-disorder transition temperature. As examples they consider models with 2 [times] 1 and c(2 [times] 2) equilibrium superstructures on the square and rectangular lattices, respectively. They also study the case of phase separation ( 1 [times] 1' islands) on the square lattice. A generalized parallel checkerboard algorithm for Kawasaki dynamics is shown to give rise to artificial spatial correlations in all three models. However, only if superstructure domains evolve do these correlations modify the kinetics by influencing the nucleation process and result in a reduced growth exponent compared to the value from the conventional heat bath algorithm with random single-site updates. In order to overcome these artificial modifications, two MC algorithms with a reduced degree of parallelism ( hybrid' and mask' algorithms, respectively) are presented and applied. As the results indicate, these algorithms are suitable for the simulation of superstructure domain growth on parallel/vector computers. 60 refs., 10 figs., 1 tab.
- OSTI ID:
- 6912172
- Journal Information:
- Journal of Statistical Physics; (United States), Vol. 66:3-4; ISSN 0022-4715
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
SUPERCONDUCTIVITY AND SUPERFLUIDITY
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
DOMAIN STRUCTURE
COMPUTERIZED SIMULATION
SUPERLATTICES
ALGORITHMS
MONTE CARLO METHOD
PARALLEL PROCESSING
VECTOR PROCESSING
MATHEMATICAL LOGIC
PROGRAMMING
SIMULATION
665000* - Physics of Condensed Matter- (1992-)
990200 - Mathematics & Computers