Abstract
A dynamic Monte Carlo (MC) method for simulations has been presented which is similar to the well-known Brownian dynamics method, but is suitable for many systems and can readily be adopted to isobaric simulations. This dynamic MC has been applied to several systems and shows similar accuracy and improved efficiency compared with routine methods. It samples configuration space approximately according to the equilibrium probability density and is applicable to NPT simulations of rather complex systems, also with rigid constraints.
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