A j-walking algorithm for microcanonical simulations: Applications to Lennard-Jones clusters

On the use of a weak-coupling thermostat in replica-exchange molecular dynamics simulations

In a molecular dynamics (MD) simulation, various thermostat algorithms, including Langevin dynamics (LD), Nosé-Hoover (NH), and weak-coupling (WC) thermostats, can be used to keep the simulation temperature constant. A canonical ensemble is generated by the use of LD and NH, while the nature of the ensemble produced by WC has not yet been identified. A few years ago, it was shown that when using a WC thermostat with particular values of the temperature coupling time for liquid water at ambient temperature and pressure, the distribution of the potential energy is less wide than the canonical one. This led to an artifact in temperature replica-exchange molecular dynamics (T-REMD) simulations in which the potential energy distributions appear not to be equal to the ones of standard MD simulations. In this paper, we re-investigate this problem. We show that this artifact is probably due to the ensemble generated by WC being incompatible with the T-REMD replica-exchange criterion, which assumes a canonical configurational ensemble. We also show, however, that this artifact can be reduced or even eliminated by particular choices of the temperature coupling time of WC and the replica-exchange time period of T-REMD, i.e., when the temperature coupling time is chosen very close to the MD time step or when the exchange time period is chosen large enough. An attempt to develop a T-REMD replica-exchange criterion which is likely to be more compatible with the WC configurational ensemble is reported. Furthermore, an exchange criterion which is compatible with a microcanonical ensemble is used in total energy REMD simulations.

A rare event sampling method for diffusion Monte Carlo using smart darting

We identify a set of multidimensional potential energy surfaces sufficiently complex to cause both the classical parallel tempering and the guided or unguided diffusion Monte Carlo methods to converge too inefficiently for practical applications. The mathematical model is constructed as a linear combination of decoupled Double Wells [(DDW)(n)]. We show that the set (DDW)(n) provides a serious test for new methods aimed at addressing rare event sampling in stochastic simulations. Unlike the typical numerical tests used in these cases, the thermodynamics and the quantum dynamics for (DDW)(n) can be solved deterministically. We use the potential energy set (DDW)(n) to explore and identify methods that can enhance the diffusion Monte Carlo algorithm. We demonstrate that the smart darting method succeeds at reducing quasiergodicity for n ≫ 100 using just 1 × 10(6) moves in classical simulations (DDW)(n). Finally, we prove that smart darting, when incorporated into the regular or the guided diffusion Monte Carlo algorithm, drastically improves its convergence. The new method promises to significantly extend the range of systems computationally tractable by the diffusion Monte Carlo algorithm.

Parallel tempering simulations of the 13-center Lennard-Jones dipole-dipole cluster (muD=0-->0.5 a.u.)

We investigate the thermodynamic behavior of the thirteen center uniform Lennard-Jones dipole-dipole cluster [(LJDD)(13)] for a wide range of dipole moment strengths. We find a relatively wide range of potential parameters where solid-solid coexistence manifests itself. Using structural characterization methods we determine the shape of the few isomers that contribute to the solid-solid coexistence region. The thermal distributions of the size of the net dipole moment are broad even at the coldest temperatures of the simulation where the (LJDD)(13) cluster is solid.

A unified methodological framework for the simulation of nonisothermal ensembles

A general framework is developed for the simulation of nonisothermal statistical-mechanical ensembles. This framework is intended to synthesize the formulation of advanced Monte Carlo simulation methods such as multihistogram reweighting, replica-exchange methods, and expanded ensemble techniques so that they can be applied to different nonisothermal ensembles. Using Lennard-Jones systems as test cases, novel implementations of these methods are demonstrated with different ensembles including the microcanonical, isobaric-isoenthalpic, and isobaric-semigrand ensembles. In particular, it is shown that the use of multiensemble methods allows the efficient simulation of microcanonical density of states, entropies, vapor-liquid and solid-liquid equilibrium for pure component systems, and fluid-phase coexistence for binary mixtures. In these applications, comparisons are also presented that highlight the advantages of the proposed multiensemble implementations over alternative methods used before.

Stochastic potential switching algorithm for Monte Carlo simulations of complex systems

This paper describes a new Monte Carlo method based on a novel stochastic potential switching algorithm. This algorithm enables the equilibrium properties of a system with potential V to be computed using a Monte Carlo simulation for a system with a possibly less complex stochastically altered potential V. By proper choices of the stochastic switching and transition probabilities, it is shown that detailed balance can be strictly maintained with respect to the original potential V. The validity of the method is illustrated with a simple one-dimensional example. The method is then generalized to multidimensional systems with any additive potential, providing a framework for the design of more efficient algorithms to simulate complex systems. A near-critical Lennard-Jones fluid with more than 20,000 particles is used to illustrate the method. The new algorithm produced a much smaller dynamic scaling exponent compared to the Metropolis method and improved sampling efficiency by over an order of magnitude.

Parameter space minimization methods: Applications to Lennard-Jones–dipole-dipole clusters

The morphology of the uniform Lennard-Jones-dipole-dipole cluster with 13 centers (LJDD)13 is investigated over a relatively wide range of values of the dipole moment. We introduce and compare several necessary modifications of the basin-hopping algorithm for global optimization to improve its efficiency. We develop a general algorithm for T=0 Brownian dynamics in curved spaces, and a graph theoretical approach necessary for the elimination of dissociated states. We find that the (LJDD)13 cluster has icosahedral symmetry for small to moderate values of the dipole moment. As the dipole moment increases, however, its morphology shifts to an hexagonal antiprism, and eventually to a ring.

Parallel Random Tunneling Algorithm for Structural Optimization of Lennard-Jones Clusters up to N = 330

A random tunneling algorithm (RTA) is derived from the terminal repeller unconstrained subenergy tunneling (TRUST) algorithm, and the parallelization of the RTA is implemented with an island parallel paradigm. Combined with the techniques of angular moving, the parallel random tunneling algorithm (PRTA) is applied to the optimization of Lennard-Jones (LJ) atomic clusters, and all the global minima of LJ clusters with size up to 200 are successfully located. For the optimization of larger cluster, a PRTA with an improved seeding technique is developed and successfully applied to the optimization of LJ151-LJ309. Furthermore, the optimized structures of LJ309-330 with the PRTA, which have not been studied before, are also provided.