Showing papers on "Monte Carlo method published in 1984"

New Monte Carlo method to compute the free energy of arbitrary solids. Application to the fcc and hcp phases of hard spheres

Abstract: We present a new method to compute the absolute free energy of arbitrary solid phases by Monte Carlo simulation. The method is based on the construction of a reversible path from the solid phase under consideration to an Einstein crystal with the same crystallographic structure. As an application of the method we have recomputed the free energy of the fcc hard‐sphere solid at melting. Our results agree well with the single occupancy cell results of Hoover and Ree. The major source of error is the nature of the extrapolation procedure to the thermodynamic limit. We have also computed the free energy difference between hcp and fcc hard‐sphere solids at densities close to melting. We find that this free energy difference is not significantly different from zero: −0.001<ΔF<0.002.

Sputtering Studies with the Monte Carlo Program TRIM.SP

Abstract: The Monte Carlo Program TRIM.SP (sputtering version of TRIM) was used to determine sputtering yields and energy and angular distributions of sputtered particles in physical (collisional) sputtering processes. The output is set up to distinguish between the contributions of primary and secondary knock-on atoms as caused by in- and outgoing incident ions, in order to get a better understanding of the sputtering mechanisms and to check on previous theoretical models. The influence of the interatomic potential and the inelastic energy loss model as well as the surface binding energy on the sputtering yield is investigated. Further results are sputtering yields versus incident energy and angle as well as total angular distributions of sputtered particles and energy distributions in specific solid angles for non-normal incidence. The calculated data are compared with experimental results as far as possible. From this comparison it turns out that the TRIM.SP is able to reproduce experimental results even in very special details of angular and energy distributions.

Applications of the Monte Carlo method in statistical physics

Abstract: 1. A Simple Introduction to Monte Carlo Simulation and Some Specialized Topics.- 2. Recent Developments in the Simulation of Classical Fluids.- 3. Monte Carlo Studies of Critical and Multicritical Phenomena.- 4. Few- and Many-Fermion Problems.- 5. Simulations of Polymer Models.- 6. Simulation of Diffusion in Lattice Cases and Related Kinetic Phenomena.- 7. Roughening and Melting in Two Dimensions.- 8. Monte Carlo Studies of "Random" Systems.- 9. Monte Carlo Calculations in Lattice Gauge Theories.- 10. Recent Developments.- Additional References with Titles.

Electrical double layer forces: a Monte Carlo study

Abstract: Using a novel method the force between two charged surfaces with an intervening electrolyte solution has been determined from Monte Carlo simulations. We find large deviations from the standard Poisson–Boltzmann treatment of the so called double layer force for divalent counterions at high surface charge densities and at short separations. The deviations have two causes: (i) Due to the inclusion of the effect of ion–ion correlations the counterions concentrate more towards the charged wall reducing the overlap between the double layers; and (ii) correlated fluctuations in the ion clouds of the two surfaces lead to an attractive interaction of a van der Waals type. For some realistic values of the parameters the attraction overcomes the repulsive part and there is a net attractive force between similarly charged surfaces. This finding leads to a modification of our conceptual understanding of the interaction between charged particles and it shows that the DLVO theory is qualitatively deficient under some, realistic, conditions.

Monte Carlo study of the isotropic and nematic phases of infinitely thin hard platelets

Abstract: We present the results of a detailed Monte Carlo study of the phase diagram of infinitely thin hard platelets. A weak first order isotropicnematic transition is observed. The equation of state in the isotropic regime is compared with several current theories, none of which is found to be fully satisfactory. The density dependence of the nematic order parameter is found to be compatible with a ‘critical’ exponent β=0·25. A study of the fluctuations of the order parameter in the isotropic phase casts doubt on the applicability of the Landau-de Gennes expression for the free energy. We observe that the relation between the nematic order parameters and is compatible with the predictions of mean-field theory. Practical aspects of the computation are discussed. A novel method to compute the pressure in a constant-volume Monte Carlo run is presented.

Efficient Monte Carlo Procedures for Generating Points Uniformly Distributed over Bounded Regions

Abstract: We consider the Monte Carlo problem of generating points uniformly distributed within an arbitrary bounded measurable region. The class of Markovian methods considered generate points asymptotically uniformly distributed within the region. Computational experience suggests the methods are potentially superior to conventional rejection techniques for large dimensional regions.

Techniques for Estimating the Bit Error Rate in the Simulation of Digital Communication Systems

Abstract: Computer simulation is often used to estimate the bit error rate (BER) performance of digital communication systems. There are a number of distinct techniques in the simulation context that can be used to construct this estimate. A tutorial exposition of such techniques is provided, with particular reference to five specific methods which can be implemented in a simulation. These methods range from the traditional Monte Carlo trials to assumption of definite forms for the noise statistics. An attempt is made to show how these methods are related, and the specific assumptions that are invoked in order to apply them.

Fundamental properties and performance of conventional bearings-only target motion analysis

Abstract: This paper considers the problem of estimating the position and velocity of an object from noise corrupted bearing measurements obtained by a single moving observation platform. The process is inherently nonlinear and exhibits unusual observability properties that are geometry-dependent. A maximum likelihood estimate (MLE) of the target motion analysis solution is developed and its performance analyzed. A comparison is drawn between the MLE and two previously reported methods, a nonlinear modified-instrumental variable estimate (MIV) and the pseudo-linear estimate (PLE). Both the MIV and PLE are shown to derive from approximations to the nonlinear measurement equation and therefore share some common properties with the MLE. The limits on performance that can be expected from processing bearing data are detailed. Specifically, for long range-to-baseline geometries, approximate expressions for the Cramer-Rao bound are derived. Extension of the results to the practical filters approximately predicts numerically observed behavior. For less restrictive geometries, bounds are presented. Incorporation of a target speed constraint on the MLE results in a transition to a lower dimensional problem as noise level and range increases. Monte Carlo experimental results are presented and the improvements realized by the MLE techniques are evident.

Bootstrapping a Regression Equation: Some Empirical Results

Abstract: The bootstrap, like the jackknife, is a technique for estimating standard errors. The idea is to use Monte Carlo simulation based on a nonparametric estimate of the underlying error distribution. The main object of this article is to present the bootstrap in the context of an econometric equation describing the demand for energy by industry. As it turns out, the conventional asymptotic formulas for estimating standard errors are too optimistic by factors of nearly three, when applied to a particular finite-sample problem. In a simpler context, this finding can be given a mathematical proof.

Phase Transition of the Two-Dimensional Heisenberg Antiferromagnet on the Triangular Lattice

Abstract: Ordering process of the antiferromagnetic Heisenberg model on the two-dimensional triangular lattice is studied both by topological analysis of defects and by Monte Carlo simulation. It is shown that the order parameter space of this model is isomorphic to the three-dimensional rotation group SO(3) due to the inherent frustration effect. Homotopy analysis shows that the system bears a topologically stable point defect characterized by a two-valued topological quantum number and exhibits a phase transition driven by the dissociation of the vortices. A Monte Carlo study on the specific heat and the behavior of vortices strongly suggests the occurence of a Kosterlitz-Thouless-type phase transition. It is, however, argued that in contrast to the two-dimensional X Y model, the spin-correlation function decays exponentially even in the low-temperature phase. In order to distinguish the high- and low-temperature phases qualitatively, we introduce a “vorticity function” analogously to the Wilson loop in the quark...

Phase diagram of a system of hard ellipsoids

Abstract: The phase diagram of a system of hard ellipsoids of revolution was investigated by means of constant-pressure Monte Carlo simulation. Prolate as well as oblate ellipsoids were considered. The results for the isotherms of the system at several different values of the length-to-breadth ratio are presented. Four different phases of the system are identified and a tentative picture of the phase diagram is given.

A simple density functional theory for inhomogeneous liquids

Abstract: A simple free energy functional, which incorporates both ‘local’ thermodynamics and short ranged correlations, is formulated and applied to the calculation of the density profile of fluids near hard walls. For hard sphere fluids the calculated profiles are in reasonable agreement with Monte Carlo results. For a Lennard-Jones liquid the profiles exhibit the phenomenon of wetting by gas; the oscillations in the density profiles become much less pronounced and a layer of gas develops near the wall as the bulk density approaches its value at coexistence. Such behaviour was found earlier in Monte Carlo simulations but is not accounted for by existing integral equation theories based on closures of the wall-particle Ornstein-Zernike equation.

Quantum Monte Carlo for molecules: Green’s function and nodal release

Abstract: A random walk algorithm is presented which exactly calculates the properties of a many‐electron system. For that purpose both the Green’s function Monte Carlo method and nodal relaxation have been employed and both are described in detail. The scheme is applied to several small molecules, (H3, LiH, Li2, H20) and with modest computational effort and simple importance functions, ground state energies are obtained which agree with experimental energies within statistical error bars. The small energy decrease due to nodal release is accurately evaluated by a difference method.

Pattern Formation in Diffusion-Limited Aggregation

Abstract: The diffusion-limited-aggregation model is generalized in order to take into account the surface effects playing an essential role during most of the growth processes. With variation of a parameter of the model the geometry of the clusters generated in the Monte Carlo simulations gradually changes from the randomly branched diffusion-limited-aggregation clusters into compact, nearly regular, snowflakelike patterns. The deposition of particles along a line results in patterns similar to those observed in the experiments on directional solidification.

Chapter 16 Monte carlo experimentation in econometrics

Abstract: Publisher Summary At the outset, it is useful to distinguish Monte Carlo methods from distribution sampling even though their application in econometrics may seem rather similar. The former is a general approach whereby mathematical problems of an analytical nature, which prove technically intractable, can be solved by substituting an equivalent stochastic problem and solving the latter. In contrast, distribution sampling is used to evaluate features of a statistical distribution by representing it numerically and drawing observations from that numerical distribution. The chapter investigates the distribution of the mean of random samples of T observations from a distribution that was uniform between zero and unity, one could simply draw a large number of samples of that size from a set of one million evenly spaced numbers in the interval and plot the resulting distribution. Such a procedure is invariably part of a Monte Carlo experiment.

Power Transformations When Fitting Theoretical Models to Data

Abstract: We investigate power transformations in nonlinear regression problems when there is a physical model for the response but little understanding of the underlying error structure. In such circumstances, and unlike the ordinary power transformation model, both the response and the model must be transformed simultaneously and in the same way. We show by an asymptotic theory and a small Monte Carlo study that for estimating the model parameters there is little cost for not knowing the correct transform a priori; this is in dramatic contrast to the results for the usual case where only the response is transformed. Possible applications of the theory are illustrated by examples.

Monte Carlo Calculation for Electromagnetic-Wave Scattering from Random Rough Surfaces

Abstract: A Monte Carlo calculation for light intensities scattered from a random Gaussian-correlated surface is presented for the first time. It is shown that small randomness on a grating surface can considerably change the intensities and, in particular, the surface polariton resonances. These results should be used to check perturbation-theory calculations.

Monte Carlo Calculation of Quantum Systems

Abstract: Thermodynamic properties of non-relativistic quantum systems are treated by the Monte Carlo calculation of path integrals. This method can be applied to the N-body problem. For boson systems the importance sampling of permutation and coordinates is efficient. For fermion systems direct calculation of determinant of propagators is efficient to avoid the negative sign problem.

Monte Carlo shock-like solutions to the Boltzmann equation with collective scattering

Abstract: The results of Monte Carlo simulations of steady state shocks generated by a collision operator that isotropizes the particles by means of elastic scattering in some locally defined frame of reference are presented. The simulations include both the back reaction of accelerated particles on the inflowing plasma and the free escape of high-energy particles from finite shocks. Energetic particles are found to be naturally extracted out of the background plasma by the shock process with an efficiency in good quantitative agreement with an earlier analytic approximation (Eichler, 1983 and 1984) and observations (Gosling et al., 1981) of the entire particle spectrum at a quasi-parallel interplanetary shock. The analytic approximation, which allows a self-consistent determination of the effective adiabatic index of the shocked gas, is used to calculate the overall acceleration efficiency and particle spectrum for cases where ultrarelativistic energies are obtained. It is found that shocks of the strength necessary to produce galactic cosmic rays put approximately 15 percent of the shock energy into relativistic particles.

Computer Studies of Phase Transitions and Critical Phenomena

Abstract: 1. Introduction.- 2. Computer Methods in the Study of Phase Transitions and Critical Phenomena.- 2.1 Statistical Mechanics and Phase Transitions.- 2.1.1 Modern theories of phase transitions and critical phenomena.- 2.1.2 Statistical mechanics, order parameters, fluctuations, critical exponents, scaling, and universality.- 2.2 Numerical Simulation Techniques.- 2.2.1 Monte Carlo methods.- 2.2.2 A Monte Carlo importance-sampling method.- 2.2.3 A realization of a Monte Carlo method.- 2.2.4 General limitations of the Monte Carlo method.- 2.2.5 Broken ergodicity.- 2.2.6 Distribution functions.- 2.2.7 Coarse-graining techniques and criteria of convergence.- 2.2.8 Finite-size effects.- 2.2.9 Determining the nature of a phase transition.- 2.2.10 Computational details.- 2.2.11 General advantages of the Monte Carlo method: Applications.- 2.3 Exact Configurational Counting and Series Expansions.- 2.3.1 A general approach.- 2.3.2 The moment method.- 2.3.3 Principles of the calculation.- 2.3.4 Step 1. Determination of all distinct graphs and their multiplicities.- 2.3.5 Step 2. Embedding of connected graphs into a lattice.- 2.3.6 General correlation function series.- 2.3.7 Capabilities and limitations of a general approach.- 3. Monte Carlo Pure-model Calculations.- 3.1 Critical Behavior of the Three-dimensional Ising Model.- 3.1.1 The Ising model and its order parameter.- 3.1.2 Numerical evidence of a phase transition in the Ising model on a diamond lattice.- 3.1.3 Finite-size scaling analysis and critical behavior.- 3.1.4 Are Monte Carlo techniques practicable in the study of critical phenomena?.- 3.2 Phase Behavior of Ising Models with Multi-spin Interactions.- 3.2.1 Higher-order exchange in magnetic systems.- 3.2.2 Ising models with multi-spin interactions.- 3.2.3 First-order phase transitions of Ising models with pure multi-spin interactions.- 3.2.4 Universality and tricritical behavior of Ising models with two- and four-spin interactions: Pair interactions as a symmetry-breaking field.- 3.3 Thermodynamics of One-dimensional Heisenberg Models.- 3.3.1 One-dimensional magnetic models.- 3.3.2 The anisotropic Heisenberg model in a magnetic field.- 3.3.3 Comparison with theoretical calculations on a continuum model.- 3.3.4 A model ofthe linear magnet CsNiF3?.- 4. Testing Modern Theories of Critical Phenomena.- 4.1 Fluctuation-induced First-order Phase Transitions.- 4.1.1 The role of fixed points in the renormalization group theory.- 4.1.2 Motivation for computer studies of fluctuation-induced first-order phase transitions.- 4.1.3 Phase transitions in antiferromagnets with order Parameters of dimension n=6 and n=3.- 4.1.4 Crossover from first-order to continuous transitions in a symmetry-breaking field.- 4.1.5 Fluctuation-induced first-order phase transitions in Ising models with competing interactions.- 4.2 Critical Phenomena at Marginal Dimensionality.- 4.2.1 The role of a marginal spatial dimension.- 4.2.2 Computer experiments of hypercubic Ising models: ?A romance of many dimensions?.- 4.2.3 Susceptibility and critical isotherm of the four-dimensional Ising model.- 4.2.4 Conclusions on critical behavior in marginal dimensions.- 4.3 Basic Assumptions of Critical Correlation Theories.- 4.3.1 Review of a critical correlation theory.- 4.3.2 Testing the basic assumption by Monte Carlo calculations.- 5. Numerical Experiments.- 5.1 Phase Transitions in Lipid Bilayers and Biological Membranes.- 5.1.1 What are biological membranes and what do they do?.- 5.1.2 Lipid bilayers are model membranes.- 5.1.3 Phase behavior of lipid bilayers.- 5.1.4 Back to biology: Are phase transitions at all relevant to the biological functions of the membrane?.- 5.1.5 Theories of lipid bilayer phase transitions.- 5.1.6 Computer simulations of lipid bilayers.- 5.1.7 Multi-state models of lipid bilayers.- 5.1.8 Computer simulations of the q-state models for the gel-fluid phase transition.- 5.1.9 Computer Simulation of the phase behavior of lipid bilayers with ?impurities?: cholesterol, proteins, and Polypeptides.- 5.1.10 Have Computer studies provided any new insight into the properties of biological membranes?.- 5.2 Nuclear Dipolar Magnetic Ordering and Phase Transitions.- 5.2.1 Nuclear dipolar magnetic ordering.- 5.2.2 The secular dipolar Hamiltonian.- 5.2.3 Perspectives in studies of nuclear dipolar magnetic ordering.- 5.2.4 Motivation for a numerical Simulation study of nuclear dipolar magnetic ordering.- 5.2.5 Monte Carlo studies of systems with truncated classical secular dipolar interactions.- 5.2.6 Nature of the spin structures: ?Permanent? structures or the devil's staircase?.- 5.2.7 Double-layered spin structures in CaF2-like systems: Continuous transitions and critical behavior.- 5.2.8 Multi-layered spin structures in CaF2-like systems: Firstorder phase transitions.- 5.2.9 Can series expansions provide information on the nature of the phase transitions?.- 5.2.10 Nuclear antiferrimagnetic susceptibilities of systems with two spin species: LiF and LiH.- 5.3 Phase Transitions of Adsorbed Monolayers.- 5.3.1 Two-dimensional phases of molecules adsorbed on solid surfaces.- 5.3.2 N2 physisorbed on graphite: The anisotropic-planar rotor model.- 5.3.3 The Heisenberg model with cubic anisotropy.- 5.3.4 Fluctuation-induced first-order phase transition in the anisotropic-planar rotor model.- 5.3.5 Comparison with experiments on N2 physisorbed on graphite.- 5.3.6 Phase behavior on the anisotropic-planar rotor model with vacancies.- 5.3.7 Physical realizations of the anisotropic-planar rotor model with vacancies.- 5.4 Kinetics of Growth.- 5.4.1 Growth.- 5.4.2 Computer Simulation of domain-growth kinetics.- 5.4.3 Domain-growth kinetics of herringbonephases.- 5.4.4 Domain-growth kinetics of pinwheel phases.- 5.4.5 Kinetics of growth and critical phenomena.

A Monte Carlo sampling plan for estimating network reliability

Abstract: For an undirected network G = V, E whose arcs are subject to random failure, we present a relatively complete and comprehensive description of a general class of Monte Carlo sampling plans for estimating g = gs, T, the probability that a specified node s is connected to all nodes in a node set T. We also provide procedures for implementing these plans. Each plan uses known lower and upper bounds [B, A] on g to produce an estimator of g that has a smaller variance A-gg-B/K on K independent replications than that obtained for crude Monte Carlo sampling B = 0, A = 1. We describe worst-case bounds on sample sizes K, in terms of B and A, for meeting absolute and relative error criteria. We also give the worst-case bound on the amount of variance reduction that can be expected when compared with crude Monte Carlo sampling. Two plans arc studied in detail for the case T = {t}. An example illustrates the variance reductions achievable with these plans. We also show how to assess the credibility that a specified error criterion for g is met as the Monte Carlo experiment progresses, and show how confidence intervals can be computed for g. Lastly, we summarize the steps needed to implement the proposed technique.