Pair approximation for polarization interaction and adiabatic nuclear and electronic sampling method for fluids with dipole polarizability

The adiabatic nuclear and electronic sampling method (ANES), originally formulated as an efficient Monte Carlo algorithm for systems with fluctuating charges, is applied to the simulation of a polarizable water model with induced dipole moments. Structural, thermodynamic and dipolar properties obtained by ANES and a newer algorithm, the pair approximation for polarization interaction (PAPI), are compared with full iteration. With the best parameters, the inaccuracy of both approximate methods was found to be comparable with the uncertainty of the full iteration. The PAPI method with iteration radius equal to the second minimum of the oxygen—oxygen correlation function is, depending on the convergence tolerance, 10–15 times faster than the full iteration for 256 molecules, and yields very accurate structure and thermodynamics with deviation about 0.3%. When the iteration radius is increased to the cutoff distance, exact results are recovered at the cost of decreased efficiency. The ANES method with small nuclear displacements proved to inefficiently sample the configurational space. Simulations at low electronic temperatures with large nuclear displacements are inaccurate for up to 100 electronic moves, and increasing this number would make the simulations as slow as the full iteration. The most accurate and efficient adiabatic ANES simulations are those with infinite electronic temperature, large nuclear displacements and 1–10 electronic moves. The extra freedom of induced dipoles in the ANES method at high electronic temperatures modifies the observed dipolar properties; however, the question of whether the dielectric constant is also modified needs further consideration.     

A hybrid transport-diffusion Monte Carlo method for frequency-dependent radiative-transfer simulations

Discrete Diffusion Monte Carlo (DDMC) is a technique for increasing the efficiency of Implicit Monte Carlo radiative-transfer simulations in optically thick media. In DDMC, particles take discrete steps between spatial cells according to a discretized diffusion equation. Each discrete step replaces many smaller Monte Carlo steps, thus improving the efficiency of the simulation. In this paper, we present an extension of DDMC for frequency-dependent radiative transfer. We base our new DDMC method on a frequency-integrated diffusion equation for frequencies below a specified threshold, as optical thickness is typically a decreasing function of frequency. Above this threshold we employ standard Monte Carlo, which results in a hybrid transport-diffusion scheme. With a set of frequency-dependent test problems, we confirm the accuracy and increased efficiency of our new DDMC method.     

Advanced multicanonical Monte Carlo methods for efficient simulations of nucleation processes of polymers

The investigation of freezing transitions of single polymers is computationally demanding, since surface effects dominate the nucleation process. In recent studies we have systematically shown that the freezing properties of flexible, elastic polymers depend on the precise chain length. Performing multicanonical Monte Carlo simulations, we faced several computational challenges in connection with liquid–solid and solid–solid transitions. For this reason, we developed novel methods and update strategies to overcome the arising problems. We introduce novel Monte Carlo moves and two extensions to the multicanonical method.     

Monte Carlo simulation of confined fluids of polarizable particles: an efficient iterative treatment of the local field in slab geometry using Ewald summation

We propose a method for treating in Monte Carlo simulations the problem of the induced dipoles for polarizable particle fluids confined in slab geometry and subject to an external field. In order to compute the local field in a reasonable time, a partial update of the induced dipole moments is performed by introducing a cut-off distance, as in bulk systems. This strategy is then combined with a slab adapted 3D-Ewald summation for treating the long-range interactions between the induced dipoles. The method is illustrated by simulations of confined binary mixtures in the canonical and grand canonical ensembles.     

The chemical potential of Lennard-Jones associating fluids from osmotic Monte Carlo simulations

The chemical potential for a two-component Lennard-Jones fluid with associative interaction between opposite species promoting the formation of dimers is calculated using osmotic Monte Carlo (OMC) canonical ensemble simulations. Grand canonical Monte Carlo simulations also are performed to verify the accuracy of the OMC approach. The data from both methods agree very well for thermodynamic states with different degrees of dimerization. It follows that the OMC is a promising approach for the determination of the thermodynamics of and equilibria between associating and non-associating fluids and associating fluid mixtures.     

Theoretical simulations of magnetic nanotubes using Monte Carlo method

We present the results of the Monte Carlo simulations of magnetic nanotubes, which are based on the plane structures with the square unit cell at low temperatures. The spin configurations, thermal equilibrium magnetization, magnetic susceptibility and the specific heat are investigated for the nanotubes of different diameters, using armchair or zigzag edges. The dipolar interaction, Heisenberg model interaction and also their combination are considered for both ferromagnetic and anti-ferromagnetic cases. It turns out that the magnetic properties of the nanotubes strongly depend on the form of the rolling up (armchair or zigzag). The effect of dipolar interaction component strongly manifests itself for the small radius nanotubes, while for the larger radius nanotubes the Heisenberg interaction is always dominating. In the thermodynamic part, we have found that the specific heat is always smaller for the nanotubes with smaller radii.     

热辐射输运问题的高效蒙特卡罗模拟方法

惯性约束聚变研究中,热辐射光子在介质中的输运以及热辐射光子与介质的相互作用是重要研究课题,蒙特卡罗方法是该类问题的重要研究手段之一.隐式蒙特卡罗方法虽然能正确地模拟热辐射在介质中的输运过程,但当模拟重介质(材料的吸收系数大)问题时,该方法花费的计算时间将变得很长,导致模拟效率很低.本文以离散扩散蒙特卡罗方法为基础,开发了"离散扩散蒙特卡罗方法辐射输运模拟程序",可以较好地解决重介质区的计算效率问题,但是离散扩散蒙卡罗方法在模拟轻介质区时精度不够高.辐射输运问题中通常既有轻介质也有重介质,为了能同时解决蒙特卡罗方法模拟的效率和精度问题,本文研究了离散扩散蒙特卡罗方法与隐式蒙特卡罗方法相结合的模拟方法,并提出了新的扩散区与输运区界面处理方法,研制了混合蒙特卡罗方法的辐射输运模拟程序.典型辐射输运问题模拟显示:在模拟重介质问题时,该程序能大幅缩短模拟时间,且能取得与隐式蒙特卡罗方法一致的结果;在模拟轻重介质均存在的问题时,与隐式蒙特卡罗方法相比,混合蒙特卡罗方法的模拟精度与其相当且计算效率同样能够得到显著提升.     

Multiscale Monte Carlo algorithm for simple fluids

We introduce a multiscale Monte Carlo algorithm to simulate dense simple fluids. The probability of an update follows a power law distribution in its length scale. The collective motion of clusters of particles requires generalization of the Metropolis update rule to impose detailed balance. We apply the method to the simulation of a Lennard-Jones fluid and show improvements in efficiency over conventional Monte Carlo and molecular dynamics simulations, eliminating hydrodynamic slowing down.     

Monte Carlo simulations for two-dimensional quantum systems

The Trotter-Suzuki transformation has been used to obtain the classical representation ford-dimensional lattice systems with boson and fermion degrees of freedom. A Monte Carlo algorithm for the equivalent (d+1)-dimensional classical system is presented. Numerical results are shown for the Heisenberg-spin-glass, the XY model and the spinless fermion lattice gas in two dimensions.     

Benchmark calculations for Monte Carlo simulations of electrontransport

Benchmark calculations have been performed for electron transport coefficients with an aim to produce a body of data required to verify the codes used in plasma modeling. The present code for the time resolved Monte Carlo simulation (MCS) was shown to represent properly DC transport coefficients in a purely electric field, in crossed electric and magnetic fields, and in the presence of nonconservative collisions, ionization, and attachment. In addition, we have suggested tests of the time dependent solutions. Relaxation of the initial transport coefficient may serve as an accurate test of the code as well as the input data for some fluid codes. In this paper, we show only one example, but several different sets of conditions and cross sections should be used as well. Finally, we propose application of the quasi-steady state results in RF fields. As an example we suggest calculation of the components of diffusion tensor showing anomalous longitudinal diffusion and calculations made with nonconservative collisions (ionization in this case). We also check the application of approximate formulas to determine drift velocity on the basis of total collision frequency and to determine a diffusion coefficient by using the Einstein relation. Other tests required to verify the transport data calculations are discussed as well     

Monte Carlo simulations of sexual reproduction

Modifying the Redfield model of sexual reproduction and the Penna model of biological aging, we compare reproduction with and without recombination in age-structured populations. In constrast to Redfield and in agreement with Bernardes we find sexual reproduction to be preferred to asexual one. In particular, the presence of old but still reproducing males helps the survival of younger females beyond their reproductive age.     

Monte Carlo simulations of parapatric speciation

Parapatric speciation is studied using an individual-based model with sexual reproduction. We combine the theory of mutation accumulation for biological ageing with an environmental selection pressure that varies according to the individuals geographical positions and phenotypic traits. Fluctuations and genetic diversity of large populations are crucial ingredients to model the features of evolutionary branching and are intrinsic properties of the model. Its implementation on a spatial lattice gives interesting insights into the population dynamics of speciation on a geographical landscape and the disruptive selection that leads to the divergence of phenotypes. Our results suggest that assortative mating is not an obligatory ingredient to obtain speciation in large populations at low gene flow.     

Irreversible Monte Carlo algorithms for efficient sampling

Equilibrium systems evolve according to Detailed Balance (DB). This principle guided the development of Monte Carlo sampling techniques, of which the Metropolis–Hastings (MH) algorithm is the famous representative. It is also known that DB is sufficient but not necessary. We construct irreversible deformation of a given reversible algorithm capable of dramatic improvement of sampling from known distribution. Our transformation modifies transition rates keeping the structure of transitions intact. To illustrate the general scheme we design an Irreversible version of Metropolis–Hastings (IMH) and test it on an example of a spin cluster. Standard MH for the model suffers from critical slowdown, while IMH is free from critical slowdown.     

Monte Carlo simulations of primitive models for ionic systems using the Wolf method

Thermodynamic and structural properties of primitive models for electrolyte solutions and molten salts were studied using NVT and NPT Monte Carlo simulations. The Coulombic interactions were simulated using the Wolf method [D. Wolf, Phys. Rev. Lett. 68, 3315 (1992); D. Wolf, P. Keblinnski, S. R. Phillpot, and J. Eggebrecht, J. Chem. Phys. 110, 8254 (1999)]. Results for 1?:?1 and 2?:?1 charge ratio electroneutral systems are presented, using the restricted and non-restricted primitive models, as well as a soft PM pair potential for a monovalent salt [J.-P. Hansen and I. R. McDonald, Phys. Rev. A 11, 2111 (1975)] that has also been used to model 2?:?12 and 1?:?20 asymmetric colloidal systems, with size ratios 1?:?10 and 2?:?15, respectively [B. Hribar, Y. V. Kalyuzhnyi, and V. Vlachy, Molec. Phys. 87, 1317 (1996)]. We present the predictions obtained for these systems using the Wolf method. Our results are in very good agreement with simulation data obtained with the Ewald sum method as well as with integral-equation theories results. We discuss the relevance of the Wolf method in the context of variable-ranged potentials in molecular thermodynamic theories for complex fluids.     

Parallel cluster labeling for large-scale Monte Carlo simulations

We present an optimized version of a cluster labeling algorithm previously introduced by the authors. This algorithm is well suited for large-scale Monte Carlo simulations of spin models using cluster dynamics on parallel computers with large numbers of processors. The algorithm divides physical space into rectangular cells which are assigned to processors and combines a serial local labeling procedure with a relaxation process across nearest-neighbor processors. By controlling overhead and reducing inter-processor communication this method attains good computational speed-up and efficiency. Large systems of up to 65536² spins have been simulated at updating speeds of 11 nanosecs/site (90.7 × 10⁶ spin updates/sec) using state-of-the-art supercomputers. In the second part of the article we use the cluster algorithm to study the relaxation of magnetization and energy on large Ising models using Swendsen-Wang dynamics. We found evidence that exponential and power law factors are present in the relaxation process as has been proposed by Hackl et al. The variation of the power-law exponent λ_M taken at face value indicates that the value of Z_M falls in the interval 0.31–0.49 for the time interval analysed and appears to vanish asymptotically.     

Monte Carlo molecular dynamics simulations for two-dimensional magnets

A combined Monte Carlo molecular dynamics simulation technique is used to study thedynamic structure factor on a square lattice for isotropic Heisenberg and planar classical ferromagnetic spin Hamiltonians.     

The pivot algorithm: A highly efficient Monte Carlo method for the self-avoiding walk

The pivot algorithm is a dynamic Monte Carlo algorithm, first invented by Lal, which generates self-avoiding walks (SAWs) in a canonical (fixed-N) ensemble with free endpoints (hereN is the number of steps in the walk). We find that the pivot algorithm is extraordinarily efficient: one effectively independent sample can be produced in a computer time of orderN. This paper is a comprehensive study of the pivot algorithm, including: a heuristic and numerical analysis of the acceptance fraction and autocorrelation time; an exact analysis of the pivot algorithm for ordinary random walk; a discussion of data structures and computational complexity; a rigorous proof of ergodicity; and numerical results on self-avoiding walks in two and three dimensions. Our estimates for critical exponents are=0.7496±0.0007 ind=2 and= 0.592±0.003 ind=3 (95% confidence limits), based on SAWs of lengths 200N10000 and 200N 3000, respectively.