He has developed nonequilibrium simulation methods including the SLLOD algorithm for the study of shear flow, the Evans'method for heat flow, the color conductivity method for the determination of self diffusion.
32.
The three-phase approach is used by a number of commercial simulation software packages, but from the user's point of view, the specifics of the underlying simulation method are generally hidden.
33.
The Zhuye Lake record is a typical record in monsoon marginal zones, which matches well with the simulation results, and the simulation method further explains the mechanism of the millennial-scale lake evolution.
34.
Experimental measurements can be combined with computer simulation methods, such as Reverse Monte Carlo ( RMC ) or molecular dynamics ( MD ) simulations, to obtain more complete and detailed description of the atomic structure.
35.
As in every simulation method, also in PIC, the time step and the grid size must be well chosen, so that the time and length scale phenomena of interest are properly resolved in the problem.
36.
Extensive research using N-body simulation methods has calibrated functional forms that predict the proper number density of dark matter halos above mass M as a function and redshift, n ( > M, z ).
37.
For example, they are the basis for a general stochastic simulation method known as Markov Chain Monte Carlo, which is used for simulating random objects with specific probability distributions, and has found application in Bayesian statistics.
38.
The use of stochastic geometry can then allow for the derivation of closed-form or semi-closed-form expressions for these quantities without resorting to simulation methods or ( possibly intractable or inaccurate ) deterministic models.
39.
Furthermore, Markov processes are the basis for a general stochastic simulation methods known as Gibbs sampling and Markov Chain Monte Carlo methods, are used for simulating random objects with specific probability distributions, and has found extensive application in Bayesian statistics.
40.
The demands, for example, of simulation methods in modern computational finance are focusing increasing attention on methods based on quantile functions, as they work well with copula or quasi-Monte-Carlo methods and Monte Carlo methods in finance.
