Epidemic outbreaks on two-dimensional quasiperiodic lattices

We present a novel kinetic Monte Carlo technique to study the susceptible-infected-removed model in order to simulate epidemic outbreaks on two quasiperiodic lattices, namely, Penrose and Ammann-Beenker. Our analysis around criticality is performed by investigating the order parameter, which is defined as the probability of growing a spanning cluster formed by removed sites, evolving from an initial system configuration with a single random chosen infective site. This system is studied by means of the cluster size distribution, obtained by the Newman-Ziff algorithm. Additionally, we obtained the mean cluster size, and a cumulant ratio to estimate the epidemic threshold. In spite of the quasiperiodic order moves the transition point, compared to periodic lattices, this is not able to alter the universality class of the model, leading to the same critical exponents. In addition, our technique can be generalized to study epidemic outbreaks in networks and diffusing populations.     

Network formed by traces of random walks

We propose a model of time evolving networks in which a kind of transport between vertices generates new edges in the graph. We call the model “Network formed by traces of random walks”, because the transports are represented abstractly by random walks. Our numerical calculations yield several important properties observed commonly in complex networks, although the graph at initial time is only a one-dimensional lattice. For example, the distribution of vertex degree exhibits various behaviors such as exponential, power law like, and bi-modal distribution according to change of probability of extinction of edges. Another property such as strong clustering structure and small mean vertex–vertex distance can also be found. The transports represented by random walks in a framework of strong links between regular lattice is a new mechanisms which yields biased acquisition of links for vertices.     

一种无线传感器网络簇间拓扑演化模型及其免疫研究

基于复杂网络理论, 研究由于节点失效所导致的无线传感器网络性能下降的问题, 提出一种新的簇间拓扑演化模型, 在此基础上讨论病毒的免疫策略, 并给出一种新的免疫机理. 理论分析表明, 该模型演化生成的网络不仅具有较强的容错性, 而且还可以有效避免节点因能量很快耗尽而过早死亡. 研究还发现, 对于网络全局信息未知的情况, 与随机免疫和熟人免疫策略相比, 本文所提免疫策略能够获得较好的免疫效果. 通过数值仿真对理论分析进行验证.     

Speckle interferometry for measurement of continuous deformations

Improvements of a method for measurement of continuous displacements and deformations with digital phase shifting speckle pattern interferometry are presented. The method is based on an algorithm that, with the knowledge of the initial phase, only needs one image at a time to evaluate continuos phase changes due to object deformations. In the improved method, the initial random phase of the speckle pattern is evaluated using a number of phase-shifted images before the deformation under study. This is used for increasing the accuracy of the initial phase estimation and reducing influences from image noise and other measurement disturbances. The phase-shifted speckle patterns are used as references for comparison with the speckle patterns of the deformed object, thereby increasing the reliability and accuracy of the phase estimations of the deformed patterns. The technique can be used for measuring deformations such as transients and other dynamic events, heat expansion as well as other phenomena where it is difficult to accomplish phase shifting during deformation.     

Population dynamics advected by chaotic flows: A discrete-time map approach

A discrete-time model of reacting evolving fields, transported by a bidimensional chaotic fluid flow, is studied. Our approach is based on the use of a Lagrangian scheme where fluid particles are advected by a two-dimensional symplectic map possibly yielding Lagrangian chaos. Each fluid particle carries concentrations of active substances which evolve according to its own reaction dynamics. This evolution is also modeled in terms of maps. Motivated by the question, of relevance in marine ecology, of how a localized distribution of nutrients or preys affects the spatial structure of predators transported by a fluid flow, we study a specific model in which the population dynamics is given by a logistic map with space-dependent coefficient, and advection is given by the standard map. Fractal and random patterns in the Eulerian spatial concentration of predators are obtained under different conditions. Exploiting the analogies of this coupled-map (advection plus reaction) system with a random map, some features of these patterns are discussed. (c) 2001 American Institute of Physics.     

A Well-Posed Numerical Method to Track Isolated Conformal Map Singularities in Hele-Shaw Flow

We present a new numerical method for calculating an evolving 2D Hele-Shaw interface when surface tension effects are neglected. In the case where the flow is directed from the less viscous fluid into the more viscous fluid, the motion of the interface is ill-posed; small deviations in the initial condition will produce significant changes in the ensuing motion. This situation is disastrous for numerical computation, as small roundoff errors can quickly lead to large inaccuracies in the computed solution. Our method of computation is most easily formulated using a conformal map from the fluid domain into a unit disk. The method relies on analytically continuing the initial data and equations of motion into the region exterior to the disk, where the evolution problem becomes well-posed. The equations are then numerically solved in the extended domain. The presence of singularities in the conformal map outside of the disk introduces specific structures along the fluid interface. Our method can explicitly track the location of isolated pole and branch point singularities, allowing us to draw connections between the development of interfacial patterns and the motion of singularities as they approach the unit disk. In particular, we are able to relate physical features such as finger shape, side-branch formation, and competition between fingers to the nature and location of the singularities. The usefulness of this method in studying the formation of topological singularities (self intersections of the interface) is also pointed out.     

Lamellar pattern formation in small-world media

Numerical and analytical techniques are used to investigate the effects of quenched disorder of small-world networks on the phase ordering dynamics of lamellar patterns as modeled by the Swift-Hohenberg equation. Morphologies for small and large values of the network randomness are quite different. It is found that addition of shortcuts to an underlying regular lattice makes the growth of domains evolving from random initial conditions much slower at late times. As the randomness increases, the evolution is eventually frozen.     

瑞利-泰勒不稳定性中尺度效应的数值模拟研究

 瑞利-泰勒不稳定性是一种由于密度梯度引起的界面不稳定性，在惯性约束聚变中具有重要的意义。利用被动标量输运模型对包含不同尺度初始扰动的界面演化过程进行数值模拟。计算结果表明界面的初始形状对不稳定性的发展具有很大的影响，狭长型扰动比正方型扰动发展慢。另外，不同尺度扰动的相互作用一般会减小沿界面发展方向运动的动能，使能量更多地用于平行于界面方向的运动。     

The structure and resilience of financial market networks

Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience.     

Turing instability for a semi-discrete Gierer-Meinhardt system

In this paper, we investigate the spatial patterns of a Gierer-Meinhardt system where the space is discrete in two dimensions with the periodic boundary condition and time is continuous, in contrast to the continuum models. The conditions of Turing instability are obtained by linear analysis and a series of numerical simulations are performed. In the instability region, we have shown that this system can produce a number of different patterns such as stripes and snowflake pattern, other than ubiquitous fix-spotted patterns. As mentioned, the results are substantiated only by means of snapshots of the apatial grid. However, we also give some analysis by using the time series at three random grids and of the average value of states, that is, the stable state patterns can be observed. On the other hand, the effects of varying parameters on pattern formation are also discussed. Moreover, simulations for fixed parameters and special initial conditions indicate that the initial conditions can alter the structure of patterns. The patterns can form as a consequence of cellular interaction. So patterns arising from a semi-discrete model can present simulations on a geometrically accurate representation in biology. As a result, our work is interesting and important in ecology.     

Path algebras,wave-particle duality,and quantization of phase space

Semigroup algebras admit certain ‘coherent’ deformations which, in the special case of a path algebra, may associate a periodic function to an evolving path; for a particle moving freely on a straight line after an initial impulse, the wave length is that hypothesized by de Broglie’s wave-particle duality. This theory leads to a model of “physical” phase space of which mathematical phase space, the cotangent bundle of configuration space, is a projection. This space is singular, quantized at the Planck level, its structure implies the existence of spin, and the spread of a packet can be described as a random walk. The wavelength associated to a particle moving in this space need not be constant and its phase can change discontinuously.     

Relaxation of the topological T1 process in a two-dimensional foam

The so-called topological T1 process, during which bubbles within a foam exchange neighbours is studied. The Durand and Stone model (Phys. Rev. Lett., 97, 226101 (2006)) describes the growth of a film that is newly created during the T1 process, and also the evolution of surfactant concentration on this newly created film. Here some characteristic features of the Durand and Stone model (not previously described by Durand and Stone) are elucidated. In particular it is shown that the surfactant concentration on the newly created film is predicted to undergo an extremely rapid initial evolution, which occurs long before the film itself approaches anywhere near its final equilibrium length. Associated with this, the predicted length of the newly created film tends to exhibit an extremely rapid acceleration early on in its growth. An intermediate asymptotic analysis is developed to explain the above model predictions, by focussing on the regime when the film is several times larger than its initial length, but still several times smaller than its final length. A physical explanation is offered for these predictions in terms of slippage between material points instantaneously at the end of the newly created film, and the evolving location of the film endpoint itself: this slippage implies surfactant being transferred onto the newly created film from neighbouring films, overwhelming the amount of surfactant initially present. The implications of these predictions for the likely observations in an experimental study of the T1 process are discussed.     

Evolving hypernetwork model

Complex hypernetworks are ubiquitous in real-life systems. While a substantial body of previous research has only focused on the applications of hypernetworks, relatively little work has investigated the evolving models of hypernetworks. Considering the formations of many real world networks, we propose two evolving mechanisms of the hyperedge growth and the hyperedge preferential attachment, then construct an evolving hypernetwork model. We introduce some basic topological quantities, such as a variety of degree distributions, clustering coefficients as well as average path length. We numerically investigate these quantities in the limit of large hypernetwork size and find that our hypernetwork model shares similar qualitative features with the majority of complex networks that have been previously studied, such as the scale-free property of the degree distribution and a high degree of clustering, as well as the small-world property. It is expected that our attempt in the hypernetwork model can bring the upsurge in the study of the hypernetwork model in further.     

气液段塞流气弹区相界面结构理论研究

根据气液段塞流气弹区相界面结构特征将气弹分为气弹头、气弹体、水跃面和气弹尾四部分,并根据各自的流动和界面结构特征分别进行模化,建立了描述不同倾角的圆管内气液段塞流气弹区相界面结构的一维理论模型.该模型的计算结果表明气液混合Froude数、管道倾角和气弹长度显著影响气液段塞流气弹区相界面结构,计算与实验结果吻合良好.     

Interpretation of heart rate variability via detrended fluctuation analysis and alphabeta filter

Detrended fluctuation analysis (DFA), suitable for the analysis of nonstationary time series, has confirmed the existence of persistent long-range correlations in healthy heart rate variability data. In this paper, we present the incorporation of the alphabeta filter to DFA to determine patterns in the power-law behavior that can be found in these correlations. Well-known simulated scenarios and real data involving normal and pathological circumstances were used to evaluate this process. The results presented here suggest the existence of evolving patterns, not always following a uniform power-law behavior, that cannot be described by scaling exponents estimated using a linear procedure over two predefined ranges. Instead, the power law is observed to have a continuous variation with segment length. We also show that the study of these patterns, avoiding initial assumptions about the nature of the data, may confer advantages to DFA by revealing more clearly abnormal physiological conditions detected in congestive heart failure patients related to the existence of dominant characteristic scales.     

A random walk evolution model of wireless sensor networks and virus spreading

In this paper, considering both cluster heads and sensor nodes, we propose a novel evolving a network model based on a random walk to study the fault tolerance decrease of wireless sensor networks (WSNs) due to node failure, and discuss the spreading dynamic behavior of viruses in the evolution model. A theoretical analysis shows that the WSN generated by such an evolution model not only has a strong fault tolerance, but also can dynamically balance the energy loss of the entire network. It is also found that although the increase of the density of cluster heads in the network reduces the network efficiency, it can effectively inhibit the spread of viruses. In addition, the heterogeneity of the network improves the network efficiency and enhances the virus prevalence. We confirm all the theoretical results with sufficient numerical simulations.     

纳米级随机粗糙表面微观滑动摩擦力的计算研究

表面形貌很大程度上决定了摩擦副的摩擦性能, 而所有的表面都不可能是绝对光滑的.由于摩擦表面形貌的随机性, 决定了实际的摩擦过程具有随机性的特点, 因此为了获得与随机形貌对应的摩擦特性, 建立合理的随机摩擦模型是必要的. 本文基于Lennard-Jones势能建立了纳米级随机粗糙表面和原子级光滑的刚性平面间的随机摩擦模型; 模型中, 界面势能由法向载荷和界面间平衡距离决定.通过数值计算的方法, 推导了微观滑动摩擦力的计算公式和摩擦力与法向载荷之间的关系. 研究结果表明摩擦力随着法向载荷的增加而增加, 但不是线性增长. 结果也说明界面间的表面势能可能是微观摩擦力的本质起源. 关键词： 随机粗糙表面 Lennard-Jones势能 微滑动摩擦力 微摩擦     

二元随机网

在二分网的基础上明确提出了二元网的概念：同样包含两类节点,二分网同类节点之间没有连接,而二元网同类节点之间可以有连接.构建了一个二元随机网模型,并对二元随机网的结构性质进行研究.二元随机网可以具有小世界效应,并且其平均最短路径长度比单元随机网还要小.另外,两类节点的规模比是一个重要参量,会对网络的结构性质产生重大影响. 关键词： 复杂网络 二分网 二元网 小世界     

Topological patterns in street networks of self-organized urban settlements

Many urban settlements result from a spatially distributed, decentralized building process. Here we analyze the topological patterns of organization of a large collection of such settlements using the approach of complex networks. The global efficiency (based on the inverse of shortest-path lengths), robustness to disconnections and cost (in terms of length) of these graphs is studied and their possible origins analyzed. A wide range of patterns is found, from tree-like settlements (highly vulnerable to random failures) to meshed urban patterns. The latter are shown to be more robust and efficient.     

Order patterns and chaos

Chaotic maps can mimic random behavior in a quite impressive way. In particular, those possessing a generating partition can produce any symbolic sequence by properly choosing the initial state. We study in this Letter the ability of chaotic maps to generate order patterns and come to the conclusion that their performance in this respect falls short of expectations. This result reveals some basic limitation of a deterministic dynamic as compared to a random one. This being the case, we propose a non-statistical test based on ‘forbidden’ order patterns to discriminate chaotic from truly random time series with, in principle, arbitrarily high probability. Some relations with discrete chaos and chaotic cryptography are also discussed.