Condensation for a Fixed Number of Independent Random Variables

A family of m independent identically distributed random variables indexed by a chemical potential φ∈[0,γ] represents piles of particles. As φ increases to γ, the mean number of particles per site converges to a maximal density ρ _c <∞. The distribution of particles conditioned on the total number of particles equal to n does not depend on φ (canonical ensemble). For fixed m, as n goes to infinity the canonical ensemble measure behave as follows: removing the site with the maximal number of particles, the distribution of particles in the remaining sites converges to the grand canonical measure with density ρ _c ; the remaining particles concentrate (condensate) on a single site.     

Robust Parametric Generators of Random Variables

Russian Physics Journal - A method of constructing consistent and effective algorithms for robust parametric generators of random variables intended for solving problems of statistical simulation...     

Distribution Functions for Random Variables for Ensembles of Positive Hermitian Matrices

Distribution functions for random variables that depend on a parameter are computed asymptotically for ensembles of positive Hermitian matrices. The inverse Fourier transform of the distribution is shown to be a Fredholm determinant of a certain operator that is an analogue of a Wiener-Hopf operator. The asymptotic formula shows that, up to the terms of order o(1), the distributions are Gaussian. Received: 5 November 1996 / Accepted: 8 January 1997     

Central Limit Theorems for Nonlinear Hierarchical Sequences of Random Variables

Let a random variable x ₀ and a function f:[a, b] ^k [a, b] be given. A hierarchical sequence {x _n :n=0, 1, 2,...} of random variables is defined inductively by the relation x _n =f(x _{n–1, 1}, x _{n–1, 2}..., x _{n–1, k} ), where {x _{n–1, i} :i=1, 2,..., k} is a family of independent random variables with the same distribution as x _n–1. We prove a central limit theorem for this hierarchical sequence of random variables when a function f satisfies a certain averaging condition. As a corollary under a natural assumption we prove a central limit theorem for a suitably normalized sequence of conductivities of a random resistor network on a hierarchical lattice.     

Results on Varextropy Measure of Random Variables

In 2015, Lad, Sanfilippo and Agrò proposed an alternative measure of uncertainty dual to the entropy known as extropy. This paper provides some results on a dispersion measure of extropy of random variables which is called varextropy and studies several properties of this concept. Especially, the varextropy measure of residual and past lifetimes, order statistics, record values and proportional hazard rate models are discussed. Moreover, the conditional varextropy is considered and some properties of this measure are studied. Finally, a new stochastic comparison method, named varextropy ordering, is introduced and some of its properties are presented.     

Generating Simple Random Graphs with Prescribed Degree Distribution

Let F be a probability distribution with support on the non-negative integers. Four methods for generating a simple undirected graph with (approximate) degree distribution F are described and compared. Two methods are based on the so called configuration model with modifications ensuring a simple graph, one method is an extension of the classical Erdös-Rényi graph where the edge probabilities are random variables, and the last method starts with a directed random graph which is then modified to a simple undirected graph. All methods are shown to give the correct distribution in the limit of large graph size, but under different assumptions on the degree distribution F and also using different order of operations.     

General Limit Distributions for Sums of Random Variables with a Matrix Product Representation

The general limit distributions of the sum of random variables described by a finite matrix product ansatz are characterized. Using a mapping to a Hidden Markov Chain formalism, non-standard limit distributions are obtained, and related to a form of ergodicity breaking in the underlying non-homogeneous Hidden Markov Chain. The link between ergodicity and limit distributions is detailed and used to provide a full algorithmic characterization of the general limit distributions.     

On the Freezing of Variables in Random Constraint Satisfaction Problems

The set of solutions of random constraint satisfaction problems (zero energy groundstates of mean-field diluted spin glasses) undergoes several structural phase transitions as the amount of constraints is increased. This set first breaks down into a large number of well separated clusters. At the freezing transition, which is in general distinct from the clustering one, some variables (spins) take the same value in all solutions of a given cluster. In this paper we introduce and study a message passing procedure that allows to compute, for generic constraint satisfaction problems, the sizes of the rearrangements induced in response to the modification of a variable. These sizes diverge at the freezing transition, with a critical behavior which is also investigated in details. We apply the generic formalism in particular to the random satisfiability of boolean formulas and to the coloring of random graphs. The computation is first performed in random tree ensembles, for which we underline a connection with percolation models and with the reconstruction problem of information theory. The validity of these results for the original random ensembles is then discussed in the framework of the cavity method.     

一种高效计算各向异性磁化等离子体的时域有限差分算法

利用电流密度和电场强度的卷积关系,引入电流密度和电场强度分段线性近似,导出一种适合各向异性磁化等离子体介质的FDTD算法的计算公式.计算各向异性碰撞磁化等离子体平板对平行于磁场传播的电磁波的反射和透射系数,与解析结果比较,验证该算法的高效性和高精度,与电流密度卷积(JEC)算法和分段线性电流密度卷积(PLCDRC)算法相比,计算精度及计算效率显著提高.此外,用该算法验证了法拉第旋转效应.     

Tsallis Entropy for Loss Models and Survival Models Involving Truncated and Censored Random Variables

The aim of this paper consists in developing an entropy-based approach to risk assessment for actuarial models involving truncated and censored random variables by using the Tsallis entropy measure. The effect of some partial insurance models, such as inflation, truncation and censoring from above and truncation and censoring from below upon the entropy of losses is investigated in this framework. Analytic expressions for the per-payment and per-loss entropies are obtained, and the relationship between these entropies are studied. The Tsallis entropy of losses of the right-truncated loss random variable corresponding to the per-loss risk model with a deductible d and a policy limit u is computed for the exponential, Weibull, χ2 or Gamma distribution. In this context, the properties of the resulting entropies, such as the residual loss entropy and the past loss entropy, are studied as a result of using a deductible and a policy limit, respectively. Relationships between these entropy measures are derived, and the combined effect of a deductible and a policy limit is also analyzed. By investigating residual and past entropies for survival models, the entropies of losses corresponding to the proportional hazard and proportional reversed hazard models are derived. The Tsallis entropy approach for actuarial models involving truncated and censored random variables is new and more realistic, since it allows a greater degree of flexibility and improves the modeling accuracy.     

Efficient Algorithm for Learning Optimization Of Morphological Filters

An efficient algorithm based on the simulated annealing for the learning optimization of morphological filters is proposed. The learning stage is divided into two consecutive parts; the initial-learning stage finds and fixes the most important parts of the structuring elements, and the precise-learning stage determines details of the rest. This method significantly reduces the number of trials for the modification of structuring elements. The proposed algorithm is applied to the learning optimization of the bipolar morphological operation, whose optimization problem has not yet been investigated. It is shown experimentally that the algorithm optimizes the operator as efficiently as the conventional one and reduces the amount of calculation.     

一种用多色光作为激发源产生拉曼光谱的新算法

探讨用多色光代替激光作为拉曼光源的新型拉曼光谱仪的可能性。根据拉曼光谱原理, 并通过数学分析, 发现当用多色光照射在样品上时, 所得到的散射光经散射频率校正后在不同频率上的强度分布可以写成样品的Raman-Rayleigh联合散射谱和激发光光源的功率谱的卷积。利用傅里叶变换算法,有可能从多色光照射样品所得到的散射光谱中导出样品的拉曼光谱。基于上述原理,可能发展出不用激光的新一代拉曼光谱仪。     

一种固定网格上拉格朗日点追踪的快速算法

提出一种基于非结构网格颗粒追踪的改进算法.在已有算法的基础上,发展适用于包含任意多边形单元界面的混合网格算法,对不共面的空间多边形界面进行虚拟三角化,实现基于任意混合网格的拉格朗日追踪.数值试验证明方法可行可靠.通过对固定容器内喷入的不同数量颗粒进行追踪的数值测试及与文献对比,显示算法高效,在颗粒数为10000时,效率提高约47%.     

An Efficient Proximity Point Algorithm for Total-Variation-Based Image Restoration

In this paper, we propose a fast proximity point algorithm and apply it to total variation (TV) based image restoration. The novel method is derived from the idea of establishing a general proximity point operator framework based on which new first-order schemes for total variation (TV) based image restoration have been proposed. Many current algorithms for TV-based image restoration, such as Chambolle's projection algorithm, the split Bregman algorithm, the Bermúdez-Moreno algorithm, the Jia-Zhao denoising algorithm, and the fixed point algorithm, can be viewed as special cases of the new first-order schemes. Moreover, the convergence of the new algorithm has been analyzed at length. Finally, we make comparisons with the split Bregman algorithm which is one of the best algorithms for solving TV-based image restoration at present. Numerical experiments illustrate the efficiency of the proposed algorithms.     

Correlations Between Record Events in Sequences of Random Variables with a Linear Trend

The statistics of records in sequences of independent, identically distributed random variables is a classic subject of study. One of the earliest results concerns the stochastic independence of record events. Recently, records statistics beyond the case of i.i.d. random variables have received much attention, but the question of independence of record events has not been addressed systematically. In this paper, we study this question in detail for the case of independent, non-identically distributed random variables, specifically, for random variables with a linearly moving mean. We find a rich pattern of positive and negative correlations, and show how their asymptotics is determined by the universality classes of extreme value statistics.     

Transport Coefficients for Inelastic Maxwell Mixtures

The Boltzmann equation for inelastic Maxwell models (IMM) is used to determine the Navier–Stokes transport coefficients of a granular binary mixture in d-dimensions. The Chapman–Enskog method is applied to solve the Boltzmann equation for states near the (local) homogeneous cooling state. The mass, heat, and momentum fluxes are obtained to first order in the spatial gradients of the hydrodynamic fields, and the corresponding transport coefficients are identified. There are seven relevant transport coefficients: the mutual diffusion, the pressure diffusion, the thermal diffusion, the shear viscosity, the Dufour coefficient, the pressure energy coefficient, and the thermal conductivity. All these coefficients are exactly obtained in terms of the coefficients of restitution and the ratios of mass, concentration, and particle sizes. The results are compared with known transport coefficients of inelastic hard spheres (IHS) obtained analytically in the leading Sonine approximation and by means of Monte Carlo simulations. The comparison shows a reasonably good agreement between both interaction models for not too strong dissipation, especially in the case of the transport coefficients associated with the mass flux     

Tanaka Theorem for Inelastic Maxwell Models

We show that the Euclidean Wasserstein distance is contractive for inelastic homogeneous Boltzmann kinetic equations in the Maxwellian approximation and its associated Kac-like caricature. This property is as a generalization of the Tanaka theorem to inelastic interactions. Even in the elastic classical Boltzmann equation, we give a simpler proof of the Tanaka theorem than the ones in [29, 31]. Consequences are drawn on the asymptotic behavior of solutions in terms only of the Euclidean Wasserstein distance.     

Estimation of Probability Densities of the Absolute Value and Argument of Complex Random Variables

We particularize criteria proposed by one of the authors for estimating the probability densities of a random vector of size N to the case of even N. For the presentation convenience in this case, two-dimensional vectors are treated as complex random variables and the probability densities of their absolute values and arguments are estimated. The estimation algorithms are synthesized on the basis of the obtained criteria under conditions of both presence and absence of complete a priori information on the sample statistic. A number of examples are given to prove that the obtained algorithms are optimal in the statistical sense. __________ Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 48, No. 7, pp. 616–627, July 2005.     

Algorithm for Detecting a Sequence of Pulsed Signals with Random Appearance Times

Using the methods of optimal nonlinear Markov filtering, we obtain an algorithm for optimal detection of a sequence of pulsed signals with random times of appearance against the background of white Gaussian noise in discrete time. Statistical characteristics of the synthesized algorithm are studied by computer simulation. The dependences of correct-detection probability on the signal-to-noise ratio and the intervals between pulses are obtained. It is shown that using the optimal nonlinear filtering methods we can improve the quality of detection of a sequence of pulsed signals compared with the methods based on the matched filtering of individual pulses in a packet.     

White Noise in Quantum Random Walk Search Algorithm

The quantum random walk is a possible approach to construct new quantum search algorithms. It has been shown by Shenvi et al. [Phys. Rev. A 67（2003）52307] that a kind of algorithm can perform an oracle search on a database of N items with O（√N） calling to the oracle, yielding a speedup similar to other quantum search algorithms. We study the effect of white or Gaussian noise on this algorithm. The algorithm loses efficiency when noise is added. We also show that noise on the target state plays a more important role than that on other states. Finally we compare the effects of similar types of noise in the quantum random walk search algorithm and Grover＇s search algorithm.