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The weighted stochastic simulation algorithm (wSSA) recently introduced by Kuwahara and Mura [J. Chem. Phys. 129, 165101 (2008)] is an innovative variation on the stochastic simulation algorithm (SSA). It enables one to estimate, with much less computational effort than was previously thought possible using a Monte Carlo simulation procedure, the probability that a specified event will occur in a chemically reacting system within a specified time when that probability is very small. This paper presents some procedural extensions to the wSSA that enhance its effectiveness in practical applications. The paper also attempts to clarify some theoretical issues connected with the wSSA, including its connection to first passage time theory and its relation to the SSA. [ABSTRACT FROM AUTHOR]

In the preceding paper [A. E. Ismail, G. C. Rutledge, and G. Stephanopoulos J. Chem. Phys. (in press)] we introduced wavelet-accelerated Monte Carlo (WAMC), a coarse-graining methodology based on the wavelet transform, as a method for sampling polymer chains. In the present paper, we extend our analysis to consider excluded-volume effects by studying self-avoiding chains. We provide evidence that the coarse-grained potentials developed using the WAMC method obey phenomenological scaling laws, and use simple physical arguments for freely jointed chains to motivate these laws. We show that coarse-grained self-avoiding random walks can reproduce results obtained from simulations of the original, more-detailed chains to a high degree of accuracy, in orders of magnitude less time. [ABSTRACT FROM AUTHOR]

Finding informative low-dimensional descriptions of high-dimensional simulation data (like the ones arising in molecular dynamics or kinetic Monte Carlo simulations of physical and chemical processes) is crucial to understanding physical phenomena, and can also dramatically assist in accelerating the simulations themselves. In this paper, we discuss and illustrate the use of nonlinear intrinsic variables (NIV) in the mining of high-dimensional multiscale simulation data. In particular, we focus on the way NIV allows us to functionally merge different simulation ensembles, and different partial observations of these ensembles, as well as to infer variables not explicitly measured. The approach relies on certain simple features of the underlying process variability to filter out measurement noise and systematically recover a unique reference coordinate frame. We illustrate the approach through two distinct sets of atomistic simulations: a stochastic simulation of an enzyme reaction network exhibiting both fast and slow time scales, and a molecular dynamics simulation of alanine dipeptide in explicit water. [ABSTRACT FROM AUTHOR]

In this paper we study the electrostatic properties of 'Janus' spheres with unequal charge densities on both hemispheres. We introduce a method to compare primitive-model Monte Carlo simulations of the ionic double layer with predictions of (mean-field) nonlinear Poisson-Boltzmann theory. We also derive practical Derjaguin Landau Verwey Overbeek (DLVO)-like expressions that describe the Janus-particle pair interactions by mean-field theory. Using a large set of parameters, we are able to probe the range of validity of the Poisson-Boltzmann approximation, and thus of DLVO-like theories, for such particles. For homogeneously charged spheres this range corresponds well to the range that was predicted by field-theoretical studies of homogeneously charged flat surfaces. Moreover, we find similar ranges for colloids with a Janus-type charge distribution. The techniques and parameters we introduce show promise for future studies of an even wider class of charged-patterned particles. [ABSTRACT FROM AUTHOR]

In this paper we investigate the solubility of a hard-sphere gas in a solvent modeled as an associating lattice gas. The solution phase diagram for solute at 5% is compared with the phase diagram of the original solute free model. Model properties are investigated both through Monte Carlo simulations and a cluster approximation. The model solubility is computed via simulations and is shown to exhibit a minimum as a function of temperature. The line of minimum solubility (TmS) coincides with the line of maximum density (TMD) for different solvent chemical potentials, in accordance with the literature on continuous realistic models and on the 'cavity' picture. [ABSTRACT FROM AUTHOR]

We present a short overview of pressure calculation in molecular dynamics or Monte Carlo simulations. The emphasis is given to polarizable models in order to resolve the controversy caused by the paper of M. J. Louwerse and E. J. Baerends [Chem. Phys. Lett. 421, 138 (2006)] about pressure calculation in systems with periodic boundaries. We systematically derive expressions for the pressure and show that despite the lack of explicit pairwise additivity, the pressure formula for polarizable models is identical with that of nonpolarizable ones. However, a strict condition for using this formula is that the induced dipole should be in perfect mechanical equilibrium prior to pressure calculation. The perfect convergence of induced dipoles ensures conservation of energy as well. We demonstrate using more cumbersome but exact methods that the derived expressions for the polarizable model of water provide correct numerical results. We also show that the inaccuracy caused by imperfect convergence of the induced dipoles correlates with the inaccuracy of the calculated pressure. [ABSTRACT FROM AUTHOR]

This paper describes the use of a Monte Carlo model incorporating a finite-element method computing the electrostatic fields inside and outside a semiconductor, plus a ray-tracing algorithm for determining the doping contrast observed in a scanning electron microscope (SEM). This combined numerical method also enables the effects on the doping contrast of surface band-bending to be distinguished from those of external patch fields outside the specimen, as well as any applied macroscopic external fields from the detection system in the SEM. Good agreement of our new theory with experiment is obtained. The contrast characteristics in energy-filtered secondary electron images are also explained. The results of this work lead to a more advanced understanding of the doping contrast mechanisms, thereby enabling quantitative dopant profiling using the SEM. [ABSTRACT FROM AUTHOR]

In this paper a new algorithm is presented that improves the efficiency of Wang and Landau algorithm or density of states (DOS) Monte Carlo simulations by employing rejected states. The algorithm is shown to have a performance superior to that of the original Wang-Landau [F. Wang and D. P. Landau, Phys. Rev. Lett. 86, 2050 (2001)] algorithm and the more recent configurational temperature DOS algorithm. The performance of the method is illustrated in the context of results for the Lennard-Jones fluid. [ABSTRACT FROM AUTHOR]

This paper formulates a hybrid Monte Carlo implementation of the Fourier path integral (FPI-HMC) approach with partial averaging. Such a hybrid Monte Carlo approach allows one to generate collective moves through configuration space using molecular dynamics while retaining the computational advantages associated with the Fourier path integral Monte Carlo method. In comparison with the earlier Metropolis Monte Carlo implementations of the FPI algorithm, the present HMC method is shown to be significantly more efficient for quantum Lennard-Jones solids and suggests that such algorithms may prove useful for efficient simulations of a range of atomic and molecular systems. [ABSTRACT FROM AUTHOR]

We suggest a practical solution to dealing with the three-body interactions in the transcorrelated variational Monte Carlo method (TC-VMC). In the TC-VMC method, which was suggested in our previous paper [N. Umezawa and S. Tsuneyuki, J. Chem. Phys. 119, 10015 (2003)], the Jastrow–Slater-type wave function is efficiently optimized through a self-consistent procedure by minimizing the variance of the local energy. The three-body terms in the transcorrelated self-consistent-field equation, which have been simply ignored in our previous works, are efficiently calculated by the Monte Carlo numerical integration. We found that our treatment for the three-body interactions is successful for atoms from Li to Ne. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Previously we developed a general method for calculating the free energy of any surface constrained to a distinct surface excess number/density. In this paper we show how to combine a range of such surfaces, whose free energies have been calculated, to produce an ad hoc semigrand canonical ensemble of surfaces from which ensemble surface properties can be calculated, including the ensemble surface free energy. We construct such an ensemble for the disordered Au(100) semihexagonal reconstructed surface using a Glue model potential at 1000 K and calculate the ensemble surface free energy to be 0.088 18 eV/Å2. The ensemble average surface lateral density was found to be 1.375 (with respect to the bulk), which is in agreement with previous grand canonical Monte Carlo studies. [ABSTRACT FROM AUTHOR]

Makarov, Keller, Plaxco, and Metiu (MKPM) (to be published) have proposed a model that assumes that the kinetics of protein folding is controlled by the formation of the native contacts. An approximate solution of this model leads to a connection between the rate constant and the number of contacts in the folded state, which agrees with the measurements. In the present article, we perform Kinetic Monte Carlo simulations to test the assumptions and the results of MKPM theory. These simulations require us to know the rate constant for contact formation and dissociation. We show that these can be calculated for the case of a Gaussian chain and then used, in a Kinetic Monte Carlo program, to simulate folding kinetics. It is likely that a Gaussian chain is not a realistic model for the folding of a specific protein. However, it is reasonable to use it to test the assumptions made by MKPM, or by other kinetic models, or to derive generic features of folding rate, such as the dependence on the number of contacts. Another valuable feature of the simulation is that it provides information about the stochastic kinetics of a single chain, which is not yet available experimentally. The simulations find that the probability that a single chain folds at a time t has a maximum, at a time t[sub m], and decays exponentially for longer times. We show that t[sub m] is shorter than the time resolution of the experiments and therefore the measurements will conclude that folding is a first-order rate process. This is what is observed experimentally. The folding rate constant produced by simulations agrees with the one obtained by the simplified MKPM theory. Moreover, the simulations were used to test directly some of the assumptions made by MKPM. For example, we show that the free energy of a chain that has made a fair number of contacts can be approximated by a linear function of the number of contacts. The paper also contains two simplified models, which do not assume that the... [ABSTRACT FROM AUTHOR]

It is well known that a magnetic field applied onto a Heisenberg antiferromagnet acts as an effective easy-plane anisotropy leading, in the case of two dimensions, to a Berezinskii–Kosterlitz–Thouless transition at a field-dependent temperature. If a nonmagnetic impurity is introduced in the lattice, an island of finite staggered magnetization develops, for which a recently proposed effective model predicts a universal shape that is almost independent of temperature and whose amplitude decays exponentially with the distance from the impurity. This picture was confirmed for the two-dimensional spin-12 case by quantum Monte Carlo simulations, whose outcomes, however, display also a counterintuitive effect: as the temperature approaches the critical value, the field-induced staggered magnetization surprisingly increases its range, which reaches a maximum before definitely dropping to zero in the disordered phase. In this paper an explanation of such a strange behavior is given as the result of vortex excitation. [ABSTRACT FROM AUTHOR]

We theoretically study noise-induced phase switch phenomena in an inertial majority-vote (IMV) model introduced in a recent paper [Chen et al., Phys. Rev. E 95, 042304 (2017)]. The IMV model generates a strong hysteresis behavior as the noise intensity f goes forward and backward, a main characteristic of a first-order phase transition, in contrast to a second-order phase transition in the original MV model. Using the Wentzel-Kramers-Brillouin approximation for the master equation, we reduce the problem to finding the zero-energy trajectories in an effective Hamiltonian system, and the mean switching time depends exponentially on the associated action and the number of particles N. Within the hysteresis region, we find that the actions, along the optimal forward switching path from the ordered phase (OP) to disordered phase (DP) and its backward path show distinct variation trends with f, and intersect at f=fc that determines the coexisting line of the OP and DP. This results in a nonmonotonic dependence of the mean switching time between two symmetric OPs on f, with a minimum at fc for sufficiently large N. Finally, the theoretical results are validated by Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

High current density is indispensable to shift domain walls (DWs) in magnetic nanowires, which limits the using of racetrack memory (RM) for low power and high density purposes. In this paper, we present perpendicular-magnetic-anisotropy (PMA) Co/Ni RM with global magnetic field assistance, which lowers the current density for DW motion. By using a compact model of PMA RM and 40 nm design kit, we perform mixed simulation to validate the functionality of this structure and analyze its density potential. Stochastic DW motion behavior has been taken into account and statistical Monte-Carlo simulations are carried out to evaluate its reliability performance. [ABSTRACT FROM AUTHOR]

In this paper we describe a 4π cylindrical field acquisition configuration surrounding a bare (unshielded, uncollimated) high purity germanium detector. We perform an efficiency calibration with a flexible planar source and model the configuration in the 4π cylindrical field. We then use exact calculus to model the flux on the cylindrical sides and end faces of the detector. We demonstrate that the model accurately represents the experimental detection efficiency compared to that of a point source and to Monte Carlo N-particle (MCNP) calculations of the flux. The model sums over the entire source surface area and the entire detector surface area including both faces and the detector's cylindrical sides. Agreement between the model and both experiment and the MCNP calculation is within 8%. [ABSTRACT FROM AUTHOR]

The quantum-kinetic, or Q-K, model is based on the quantum vibration model that is employed in the computation of gas flows at the molecular level by the direct simulation Monte Carlo (DSMC) method. The Q-K procedure for dissociation is physically realistic within the context of the vibration model in that the reaction occurs upon the selection of the vibrational level that corresponds to dissociation. An analogous, but entirely phenomenological, procedure has been presented for endothermic exchange and chain reactions. These procedures for the endothermic reactions have been well validated, but the existing procedures for the corresponding exothermic reactions have proved to be problematic. This paper presents new procedures for the exothermic reactions that are computationally efficient and provide a near exact match with the equilibrium constant of statistical mechanics. The Q-K model does not depend on the availability of continuum rate coefficients. Instead, the simplicity of the new DSMC procedures allows analytical expressions to be written down for the corresponding rate coefficients in an equilibrium gas. These are used to validate the Q-K model for reactions in high temperature air and in hydrogen-oxygen combustion. The development of the Q-K model has been driven by the need for efficient reaction procedures in DSMC applications that often involve the computation of billions of simulated collisions. It is not intended to compete with the modern theories for gas-phase chemical reactions that employ more accurate physical representations of real reactions. At the same time, the degree of validation of the model is such that the analytical expressions for the rate coefficients that correspond to the model should be useful in their own right. [ABSTRACT FROM AUTHOR]

This paper reviews basic results and recent developments in the field of small-scale gaseous hydrodynamics which has received significant attention in connection with small-scale science and technology. We focus on the modeling challenges arising from the breakdown of the Navier-Stokes description, observed when characteristic lengthscales become of the order of, or smaller than, the molecular mean free path. We discuss both theoretical results and numerical methods development. Examples of the former include the limit of applicability of the Navier-Stokes constitutive laws, the concept of second-order slip and the appropriate form of such a model, and how to reconcile experimental measurements of slipping flows with theory. We also review a number of recently developed theoretical descriptions of canonical nanoscale flows of engineering interest. On the simulation front, we review recent progress in characterizing the accuracy of the prevalent Boltzmann simulation method known as direct simulation Monte Carlo. We also present recent variance reduction ideas which address the prohibitive cost associated with the statistical sampling of macroscopic properties in low-speed flows. [ABSTRACT FROM AUTHOR]

We study secondary electron yield (SEY) suppression for metal materials using a roughened surface with a micro-porous array. First, we perform a Monte Carlo simulation of the electron trajectory in a single cylindrical well using a phenomenological model of secondary electron emission and the SEY suppression efficiency of a micro-porous array. The simulation results show that the SEY of a roughened surface is affected significantly by the aspect ratio of the micro-pores and the surface porosity of the metal plate. Then, to verify the simulation results, we produce a micro-porous array on metal plates using photolithography and measure their SEYs. We show that the micro-porous array structure can efficiently suppress the SEY of metal materials, and the measurements agree quantitatively with the corresponding simulation results. Finally, we derive an analytical formula to evaluate easily the SEY suppression efficiency of the Ag micro-porous array. In total, the micro-porous array proposed in this paper offers an alternative to SEY suppression in related areas such as multipactor effects in satellite payloads or electron cloud effects in accelerators. [ABSTRACT FROM AUTHOR]