Monte Carlo simulation of quantum statistical lattice models

In this article we review recent developments in computational methods for quantum statistical lattice problems. We begin by giving the necessary mathematical basis, the generalized Trotter formula, and discuss the computational tools, exact summations and Monte Carlo simulation, that will be used to examine explicit examples. To illustrate the general strategy, the method is applied to an analytically solvable, non-trivial, model: the one-dimensional Ising model in a transverse field. Next it is shown how to generalized Trotter formula most naturally leads to different path-integral representations of the partition function by considering one-dimensional fermion lattice models. We show how to analyze the different representations and discuss Monte Carlo simulation results for one-dimensional fermions. Then Monte Carlo work on one- and two-dimensional spin-$\text{1}\text{2}$ models based upon the Trotter formula approach is reviewed and the more dedicated Handscomb Monte Carlo method is discussed. We consider electron-phonon models and discuss Monte Carlo simulation data on the Molecular Crystal Model in one, two and three dimensions and related one-dimensional polaron models. Exact numerical results are presented for free fermions and free bosons in the canonical ensemble. We address the main problem of Monte Carlo simulations of fermions in more than one dimension: the cancellation of large contributions. Free bosons on a lattice are compared with bosons in a box and the effects of finite size on Bose-Einstein condensation are discussed.     

A new proposal for Monte Carlo simulation of fermions on a lattice

With F flavours of matter fields extrapolation to negative F effectively changes bosons into fermions and vice-versa. Extrapolatingresults of calculations performed with bosonic quarks we reproduce results obtained by evaluating the fermion determinant in some simple examples. We find an example of a long computer run apparently converging to the wrong answer when systematic lattice site access is used.     

A Monte Carlo algorithm for lattice ribbons

A lattice ribbon is a connected sequence of plaquettes subject to certain selfavoidance conditions. The ribbon can be closed to form an object which is topologically either a cylinder or a Möbius band, depending on whether its surface is orientable or nonorientable. We describe a grand canonical Monte Carlo algorithm for generating a sample of these ribbons, prove that the associated Markov chain is ergodic, and present and discuss numerical results about the dimensions and entanglement complexity of the ribbons.     

Monte Carlo simulation of a lattice gas model of multilayer adsorption

A lattice gas model of physical adsorption of atoms on a periodic substrate has been studied using Monte Carlo simulations. Adsorption isotherms and layer coverage isotherms are determined and from these we find distinct phase boundaries for transitions on successive layers. In contrast to mean field results our data suggests that the critical temperature increases only slowly with increasing layer number, and appears to approach the roughening temperature for infinite layer number.     

A Monte Carlo simulation of coagulation

A Monte Carlo simulation technique is described for the study of the coagulation of suspended particles. The method is computationally efficient since the particle trajectories are not used to determine coagulations. Instead, pairs of particles are assigned probabilities to coagulate and the evolution is computed as a stochastic Markov game. We also describe a simple analytic method to obtain the stationary distribution of sizes for the various mechanisms of relative particle motion. It is demonstrated that the simulation yields the correct stationary size distribution independent of initial condition.     

A new Monte Carlo simulation for two models of self-avoiding lattice trees in two dimensions

By means of a new Monte Carlo sampling of a grand canonical ensemble, we verify universality for the critical exponents and of two models of lattice trees constrained to be self-avoiding on sites or on bonds. The attrition constants are also obtained. This algorithm, a generalization of that recently proposed by Berretti and Sokal for random walks, appears to optimize the critical slowing down in the scaling region. Systematic and statistical errors are carefully estimated.     

A Monte Carlo simulation of random surfaces

We use a previously proposed stochastic process and carry out Monte Carlo simulations for two models of random surfaces defined on hypercubic lattices. Tests are carried out in five dimensions. The critical coupling constants are estimated for both models. One of the models allows also results on its entropy.     

Monte Carlo computations in lattice gauge theories

The formulation of gauge theories on Euclidean space-time lattices and the application of the Monte Carlo computational technique to the ensuing systems are reviewed. A variety of numerical results obtained for lattice gauge theories are presented and discussed.     

Dendrimer-magnetic nanostructure: a Monte Carlo simulation

In this paper, the magnetic properties of ternary mixed spins (σ,S,q) Ising model on a dendrimer nanostructure are studied using Monte Carlo simulations. The ground state phase diagrams of dendrimer nanostructure with ternary mixed spins σ = 1/2, S = 1 and q = 3/2 Ising model are found. The variation of the thermal total and partial magnetizations with the different exchange interactions, the external magnetic fields and the crystal fields have been also studied. The reduced critical temperatures have been deduced. The magnetic hysteresis cycles have been discussed. In particular, the corresponding magnetic coercive filed values have been deduced. The multiples hysteresis cycles are found. The dendrimer nanostructure has several applications in the medicine.     

Monte Carlo study of noncompact lattice QCD

We study a noncompact version of lattice QCD₄ by Monte Carlo simulation. The results indicate that the model possesses asymptotic freedom but does not confine static quarks. It looks rather like a self-Higgsed system.     

Diffusion Monte Carlo method with lattice regularization

We introduce an efficient lattice regularization scheme for quantum Monte Carlo calculations of realistic electronic systems. The kinetic term is discretized by a finite difference Laplacian with two mesh sizes, a and a', chosen so that the electrons can diffuse in a configuration space which is in practice indistinguishable from the continuum, and the different length scales in the system can be efficiently taken in account. The regularized Hamiltonian goes to the continuous limit for a --> 0 and allows the inclusion of nonlocal potentials in a consistent variational scheme, substantially improving the accuracy upon previous nonvariational approaches.     

Efficient kinetic Monte Carlo simulation

This paper concerns kinetic Monte Carlo (KMC) algorithms that have a single-event execution time independent of the system size. Two methods are presented—one that combines the use of inverted-list data structures with rejection Monte Carlo and a second that combines inverted lists with the Marsaglia–Norman–Cannon algorithm. The resulting algorithms apply to models with rates that are determined by the local environment but are otherwise arbitrary, time-dependent and spatially heterogeneous. While especially useful for crystal growth simulation, the algorithms are presented from the point of view that KMC is the numerical task of simulating a single realization of a Markov process, allowing application to a broad range of areas where heterogeneous random walks are the dominate simulation cost.     

Monte Carlo simulation of mictomagnets

Monte Carlo simulations of a binary alloy with impurity concentrations between 20 and 45 at.% have been carried out. The proportion of large clusters relative to that of small clusters increases with the number of MC diffusion steps as well as impurity concentration. Magnetic susceptibility peaks become more prominent and occur at higher temperatures with increasing impurity concentration. The different peaks in the susceptibility and specific heat curves seem to correspond to different sized clusters. A freezing model would explain the observed behaviour with the large clusters freezing first and the small clusters contributing to susceptibility (specific heat) peaks at lower temperatures.Contribution No. 153 from the Solid State and Structural Chemistry Unit     

A comparison between Monte Carlo algorithms for simulating lattice gauge theories

We compare three updating methods (Metropolis, heat bath and overrelaxed) for pure lattice quantum chromodynamics, by directly measuring their efficiency in a typical mass calculation.