Multicanonical Methods vs. Molecular Dynamics vs. Monte Carlo: Comparison for Lennard-Jones Glasses

We applied a multicanonical algorithm (entropic sampling) to a two-dimensional and a three-dimensional Lennard-Jones system with quasicrystalline and glassy ground states. Focusing on the ability of the algorithm to locate low lying energy states, we compared the results of the multicanonical simulations with standard Monte Carlo simulated annealing and molecular dynamics methods. We find slight benefits to using entropic sampling in small systems (less than 80 particles), which disappear with larger systems. This is disappointing as the multicanonical methods are designed to surmount energy barriers to relaxation. We analyze this failure theoretically, and show (1) the multicanonical method is reduced in the thermodynamic limit (large systems) to an effective Monte Carlo simulated annealing with a random temperature vs. time, and (2) the multicanonical method gets trapped by unphysical entropy barriers in the same metastable states whose energy barriers trap the traditional quenches. The performance of Monte Carlo and molecular dynamics quenches were remarkably similar.Comment: 12 pages, 6 figures, REVTEX, epsf.st

Application of Multicanonical Multigrid Monte Carlo Method to the Two-Dimensional ϕ4\phi^4-Model: Autocorrelations and Interface Tension

We discuss the recently proposed multicanonical multigrid Monte Carlo method and apply it to the scalar $\phi^4$-model on a square lattice. To investigate the performance of the new algorithm at the field-driven first-order phase transitions between the two ordered phases we carefully analyze the autocorrelations of the Monte Carlo process. Compared with standard multicanonical simulations a real-time improvement of about one order of magnitude is established. The interface tension between the two ordered phases is extracted from high-statistics histograms of the magnetization applying histogram reweighting techniques.Comment: 49 pp. Latex incl. 14 figures (Fig.7 not included, sorry) as uuencoded compressed tar fil

Multicanonical Monte Carlo Calculation of the First-order Phase Transition of Lennard-Jones Fluids

The liquid-solid phase transition was investigated by the multicanonical Monte Carlo method for a bulk Lennard-Jones fluid system that consists of 256 argon particles. The reliability of the multicanonical weight factor we determined was confirmed by the flatness of the histogram obtained by the multicanonical Monte Carlo production run. The first-order phase transition between solid and liquid phase was observed around 130 K from the change in thermodynamic properties as a function of temperature. Besides, the small change between two solid structures was also observed at 60 K from the radial distribution function, from the heat capacity and from conventional canonical Monte Carlo calculation at 60 K. Neither of them is not f. c. c. structure which is known as the most stable

Simulation of Lattice Polymers with Multi-Self-Overlap Ensemble

A novel family of dynamical Monte Carlo algorithms for lattice polymers is proposed. Our central idea is to simulate an extended ensemble in which the self-avoiding condition is systematically weakened. The degree of the self-overlap is controlled in a similar manner as the multicanonical ensemble. As a consequence, the ensemble --the multi-self-overlap ensemble-- contains adequate portions of self-overlapping conformations as well as higher energy ones. It is shown that the multi-self-overlap ensemble algorithm reproduce correctly the canonical averages at finite temperatures of the HP model of lattice proteins. Moreover, it outperforms massively a standard multicanonical algorithm for a difficult example of a polymer with 8-stickers. Alternative algorithm based on exchange Monte Carlo method is also discussed.Comment: 5 Pages, 4 Postscript figures, uses epsf.st

Multicanonical Parallel Tempering

We present a novel implementation of the parallel tempering Monte Carlo method in a multicanonical ensemble. Multicanonical weights are derived by a self-consistent iterative process using a Boltzmann inversion of global energy histograms. This procedure gives rise to a much broader overlap of thermodynamic-property histograms; fewer replicas are necessary in parallel tempering simulations, and the acceptance of trial swap moves can be made arbitrarily high. We demonstrate the usefulness of the method in the context of a grand-multicanonical ensemble, where we use multicanonical simulations in energy space with the addition of an unmodified chemical potential term in particle-number space. Several possible implementations are discussed, and the best choice is presented in the context of the liquid-gas phase transition of the Lennard-Jones fluid. A substantial decrease in the necessary number of replicas can be achieved through the proposed method, thereby providing a higher efficiency and the possibility of parallelization.Comment: 8 pages, 3 figure, accepted by J Chem Phy

Combination of improved multibondic method and the Wang-Landau method

We propose a method for Monte Carlo simulation of statistical physical models with discretized energy. The method is based on several ideas including the cluster algorithm, the multicanonical Monte Carlo method and its acceleration proposed recently by Wang and Landau. As in the multibondic ensemble method proposed by Janke and Kappler, the present algorithm performs a random walk in the space of the bond population to yield the state density as a function of the bond number. A test on the Ising model shows that the number of Monte Carlo sweeps required of the present method for obtaining the density of state with a given accuracy is proportional to the system size, whereas it is proportional to the system size squared for other conventional methods. In addition, the new method shows a better performance than the original Wang-Landau method in measurement of physical quantities.Comment: 12 pages, 3 figure