Speeding up the FMMR perfect sampling algorithm: A case study revisited

In a previous paper by the second author, two Markov chain Monte Carlo perfect sampling algorithms—one called coupling from the past (CFTP) and the other (FMMR) based on rejection sampling—are compared using as a case study the move‐to‐front (MTF) self‐organizing list chain. Here we revisit that case study and, in particular, exploit the dependence of FMMR on the user‐chosen initial state. We give a stochastic monotonicity result for the running time of FMMR applied to MTF and thus identify the initial state that gives the stochastically smallest running time; by contrast, the initial state used in the previous study gives the stochastically largest running time. By changing from worst choice to best choice of initial state we achieve remarkable speedup of FMMR for MTF; for example, we reduce the running time (as measured in Markov chain steps) from exponential in the length n of the list nearly down to n when the items in the list are requested according to a geometric distribution. For this same example, the running time for CFTP grows exponentially in n. © 2003 Wiley Periodicals, Inc. Random Struct. Alg., 2003     

Minimax estimators for location vectors in elliptical distributions with unknown scale parameter and its application to variance reduction in simulation

In this paper, we give an ever wider and new class of minimax estimators for the location vector of an elliptical distribution (a scale mixture of normal densities) with an unknown scale parameter. The its application to variance reduction for Monte Carlo simulation when control variates are used is considered. The results obtained thus extend (i) Berger's result concerning minimax estimation of location vectors for scale mixtures of normal densities with known scale parameter and (ii) Strawderman's result on the estimation of the normal mean with common unknown variance.Research partially supported by National Science Foundation, Grant #DMS 8901922.     

空化现象的模拟准则

本文在现有理论基础上导出空化现象的模拟准则.为模拟空化现象提供依据.     

Metastable systems driven by colored noise: The stationary state

The influence of the Bardeen-Herring back-jump correlations on the Fermi-Dirac statistics of the one-dimensional nonhomogeneous fermionic lattice gas is studied by the Monte Carlo simulation technique and semianalytically. The resulting distribution is obtained, exhibiting increased population of the lower levels in comparison to the Fermi-Dirac statistics.     

Monte Carlo simulation of phase separation and clustering in the ABV model

As a model for a binary alloy undergoing an unmixing phase transition, we consider a square lattice where each site can be either taken by an A atom, a B atom, or a vacancy (V), and there exists a repulsive interaction between AB nearest neighbor pairs. Starting from a random initial configuration, unmixing proceeds via random jumps of A atoms or B atoms to nearest neighbor vacant sites. In the absence of any interaction, these jumps occur at jump rates _A and _B, respectively. For a small concentration of vacancies (c _v=0.04) the dynamics of the structure factorS(k,t) and its first two momentsk ₁(t),k ₂ ² (t) is studied during the early stages of phase separation, for several choices of concentrationc _B of B atoms. Forc _B=0.18 also the time evolution of the cluster size distribution is studied. Apart from very early times, the mean cluster sizel(t) as well as the moments of the structure function depend on timet and the ratio of the jump rates (= _B/ _A) only via a scaled timet/(). Qualitatively, the behavior is very similar to the direct exchange model containing no vacancies. Consequences for phase separation of real alloys are briefly discussed.     

高功率振荡器锁相的粒子模拟

用粒子(PIC,Particle-in-Cell)模拟方法研究了当前颇感兴趣的高功率振荡器的锁相问题。给出了模拟计算结果。讨论了锁相(Phase Locking)、Priming和InjectionSeeding等概念的区别。     

一类重尾风险因子的模拟及其投资高风险值和置信区间的估计

由于金融市场中的日周期或短周期对数回报率的样本数据多数呈现胖尾分布，于是现有的正态或对数正态分布模型都在不同程度上失效，为了准确模拟这种胖尾分布和提高投资风险估计及金融管理，本文引进了一种可根据实际金融市场数据作出调正的蒙特卡洛模拟方法．这个方法可以有效地复制金融产品价格的日周期对数回报率数据的胖尾分布．结合非参数估计方法，利用该模拟方法还得到投资高风险值以及高风险置信区间的准确估计。     

Polymer confinement and bacterial gliding motility

Cyanobacteria and myxobacteria use slime secretion for gliding motility over surfaces. The slime is produced by the nozzle-like pores located on the bacteria surface. To understand the mechanism of gliding motion and its relation to slime polymerization, we have performed molecular dynamics simulations of a molecular nozzle with growing inside polymer chains. These simulations show that the compression of polymer chains inside the nozzle is a driving force for propulsion. There is a linear relationship between the average nozzle velocity and the chain polymerization rate with a proportionality coefficient dependent on the geometric characteristics of the nozzle such as its length and friction coefficient. This minimal model of the molecular engine was used to explain the gliding motion of bacteria over surfaces.     

Large eddy simulation of turbulent premixed flames using level-set G-equation

Level-set G-equation and stationary flamelet chemistry are used in large eddy simulation of a propane/air premixed turbulent flame stabilized by a bluff body. The aim was to study the interaction between the flame front and turbulent eddies, and in particular to examine the effect of sub-grid scale (SGS) eddies on the wrinkling of the flame surface. The results indicated that the two types of turbulence eddies—the resolved large scale eddies and the unresolved SGS eddies—have different effects on the flame. The fluctuation of the flame surface, which is responsible for the broadening of the time averaged mean flame brush by turbulence, depends on the large resolved turbulence eddies. Time averaged mean flow velocity, temperature, and major species concentrations mainly depend on the large scale resolved eddies. The unresolved SGS eddies contribute to the wrinkling at the SGS level and play an important role in the enhancement of the propagation speed of the resolved flame front. In addition, the spatially filtered intermediate species, such as radicals, and the spatially filtered reaction rates strongly depend on the small SGS eddies. The asymptotic behavior of flame wrinkling by the SGS eddies, with respect to the decrease in filter size and grid size, is investigated further using a simplified level-set equation in a model shear flow. It is shown that to minimize the influence of the SGS eddies, fine grid and filter size may have to be used.     

Investigation of lengthscales, scalar dissipation, and flame orientation in a piloted diffusion flame by LES

This work investigates the structure of a diffusion flame in terms of lengthscales, scalar dissipation, and flame orientation by using large eddy simulation. This has been performed for a turbulent, non-premixed, piloted methane/air jet flame (Flame D) at a Reynolds-number of 22,400. A steady flamelet model, which was represented by artificial neural networks, yields species mass fractions, density, and viscosity as a function of the mixture fraction. This will be shown to suffice to simulate such flames. To allow to examine scalar dissipation, a grid of 1.97 × 10⁶ nodes was applied that resolves more than 75% of the turbulent kinetic energy. The accuracy of the results is assessed by varying the grid-resolution and by comparison to experimental data by Barlow, Frank, Karpetis, Schneider (Sandia, Darmstadt), and others. The numerical procedure solves the filtered, incompressible transport equations for mass, momentum, and mixture fraction. For subgrid closure, an eddy viscosity/diffusivity approach is applied, relying on the dynamic Germano model. Artificial turbulent inflow velocities were generated to feature proper one- and two-point statistics. The results obtained for both the one- and two-point statistics were found in good agreement to the experimental data. The PDF of the flame orientation shows the tilting of the flame fronts towards the centerline. Finally, the steady flamelet approach was found to be sufficient for this type of flame unless slowly reacting species are of interest.