2008/11/12 by Xin Zhou, Yi Jiang, Zhou, Xin +1
Physics and Astronomy · #FOS: Physical sciences #Statistical Mechanics (cond-mat.stat-mech) #cond-mat.stat-mech
paper · pdf · doi:10.48550/arxiv.0811.1829
5 pages, 4 figures
arxiv created 2008/11/12 · arxiv updated 2009/12/01
We presented an efficient algorithm, fast adaptive flat-histogram ensemble (FAFE), to estimate the density of states (DOS) and to enhance sampling in large systems. FAFE calculates the means of an arbitrary extensive variable U in generalized ensembles to form points on the curve βs(U) ≡ (∂ S(U))/(∂ U), the derivative of the logarithmic DOS. Unlike the popular Wang-Landau-like (WLL) methods, FAFE satisfies the detailed-balance condition through out the simulation and automatically generates non-uniform (βi, Ui) data points to follow the real change rate of βs(U) in different U regions and in different systems. Combined with a U-compression transformation, FAFE reduces the required simulation steps from O(N3/2) in WLL to O(N1/2), where N is the system size. We demonstrate the efficiency of FAFE in Lennard-Jones liquids with several N values. More importantly, we show its abilities in finding and identifying different macroscopic states including meta-stable states in phase co-existing regions.