Probability routing strategy for scale-free networks

This study proposes a probability routing strategy for improving traffic capability on scale-free networks. Compared with the shortest path routing strategy depending on central nodes largely and the efficient routing strategy avoiding hub routers as much as possible, the probability routing strategy makes use of hub routers more efficiently, transferring approximate average amount of packs of the whole network. Simulation results indicate that the probability routing strategy has the highest network capacity among the three routing strategies. This strategy provides network capacity that can be more than 30 times higher than that of the shortest path routing strategy and over 50% higher than that of the efficient routing strategy. In addition, the average routing path length of our proposed strategy is over 10% shorter than that of the efficient routing strategy and only about 10% longer than that of the shortest path routing strategy.     

Epidemic spreading in a scale-free network of regular lattices

The susceptible-infected-susceptible (SIS) epidemics in a scale-free network in which each node is a square lattice itself is investigated through large-scale computer simulations. The model combines a local contact process among individuals in a node (or city) with stochastic long-range infections due to people traveling between cities interconnected by the national transportation scale-free network. A nonzero epidemic threshold is found and it is approached with a power-law behavior by the density of infected individuals, as observed in the small-world network of Watts and Strogatz. Also, the epidemic propagation follows a 1/f$1/f$, hierarchical dynamics from the highly connected square lattices to the smaller degree nodes in outbreaks with sizes distributed accordingly a Gaussian function.     

An estimation formula for the average path length of scale-free networks

A universal estimation formula for the average path length of scale free networks is given in this paper. Different from other estimation formulas, most of which use the size of network, $N$, as the only parameter, two parameters including $N$ and a second parameter $\alpha $ are included in our formula. The parameter $\alpha $ is the power-law exponent, which represents the local connectivity property of a network. Because of this, the formula captures an important property that the local connectivity property at a microscopic level can determine the global connectivity of the whole network. The use of this new parameter distinguishes this approach from the other estimation formulas, and makes it a universal estimation formula, which can be applied to all types of scale-free networks. The conclusion is made that the small world feature is a derivative feature of a scale free network. If a network follows the power-law degree distribution, it must be a small world network. The power-law degree distribution property, while making the network economical, preserves the efficiency through this small world property when the network is scaled up. In other words, a real scale-free network is scaled at a relatively small cost and a relatively high efficiency, and that is the desirable result of self-organization optimization.     

Emergence of complex networks from diffusion on fractal lattices. A special case of the Sierpinski gasket and tetrahedron

A new approach to the assemblage of complex networks displaying the scale-free architecture is proposed. While the growth and the preferential attachment of incoming nodes assure an emergence of such networks according to the Barabási–Albert model, it is argued here that the preferential linking condition needs not to be a principal rule. To assert this statement a simple computer model based on random walks on fractal lattices is introduced. It is shown that the model successfully reproduces the degree distributions, the ultra-small-worldness and the high clustering arising from the topology of scale-free networks.     

A temporal ant colony optimization approach to the shortest path problem in dynamic scale-free networks

A large number of networks in the real world have a scale-free structure, and the parameters of the networks change stochastically with time. Searching for the shortest paths in a scale-free dynamic and stochastic network is not only necessary for the estimation of the statistical characteristics such as the average shortest path length of the network, but also challenges the traditional concepts related to the “shortest path” of a network and the design of path searching strategies. In this paper, the concept of shortest path is defined on the basis of a scale-free dynamic and stochastic network model, and a temporal ant colony optimization (TACO) algorithm is proposed for searching for the shortest paths in the network. The convergence and the setup for some important parameters of the TACO algorithm are discussed through theoretical analysis and computer simulations, validating the effectiveness of the proposed algorithm.     

Scaling of average receiving time and average weighted shortest path on weighted Koch networks

In this paper we present weighted Koch networks based on classic Koch networks. A new method is used to determine the average receiving time (ART), whose key step is to write the sum of mean first-passage times (MFPTs) for all nodes to absorption at the trap located at a hub node as a recursive relation. We show that the ART exhibits a sublinear or linear dependence on network order. Thus, the weighted Koch networks are more efficient than classic Koch networks in receiving information. Moreover, average weighted shortest path (AWSP) is calculated. In the infinite network order limit, the AWSP depends on the scaling factor. The weighted Koch network grows unbounded but with the logarithm of the network size, while the weighted shortest paths stay bounded.     

漫反射立方腔单次反射平均光程的理论和实验研究

根据Beer-Lambert定律可知,增加气体池的有效光程是提高气体监测灵敏度最直接而有效的途径.通过实验研究和分析,漫反射立方腔作为气体池能显著地增加有效光程,因此研究其内部的光线传播规律具有重要意义.基于对漫反射立方腔内光线传播规律的理论分析,得到了单次反射平均光程的理论值,建立了漫反射立方腔内光线传播的理论近似模型,并通过有限元法仿真获得了单次反射平均光程的模拟值.利用可调谐二极管激光吸收光谱技术得到了立方腔的有效光程,间接求得了单次反射平均光程的实验值.对理论值、模拟值和实验值进行比较分析,验证了理论近似模型和有限元法仿真的准确性和稳定性.     

Local preferential attachment model for hierarchical networks

In real-life networks, incomers may only connect to a few others in a local area for their limited information, and individuals in a local area are likely to have close relations. Accordingly, we propose a local preferential attachment model. Here, a local-area-network stands for a node and all its neighbors, and the new nodes perform nonlinear preferential attachment, , in local areas. The stable degree distribution and clustering-degree correlations are analytically obtained. With the increasing of α, the clustering coefficient increases, while assortativity decreases from positive to negative. In addition, by adjusting the parameter α, the model can generate different kinds of degree distribution, from exponential to power-law. The hierarchical organization, independent of α, is the most significant character of this model.     

The phase transition of the directed polymer on disordered hierarchical lattices

The directed polymer on disordered hierarchical lattices is studied using an exact renormalization scheme. The phase transition is studied and a hyperscaling relation is derived. The fixed distributions of the renormalized energies are obtained numerically. The specific heat and associated exponents are computed from the fixed distributions.     

激光陀螺腔长控制机构研究与改进

腔长控制机构在激光陀螺中通过控制腔长来保证激光陀螺工作光束的频率稳定,其对激光陀螺性能的提高有着重要意义。针对激光陀螺工作过程中,传统腔长控制机构的控制镜扭偏导致光束在腔中的位置偏移毛细孔的中心位置,引起腔内的散射、损耗发生变化从而影响陀螺性能及精度的问题,对激光陀螺腔长控制机构进行了研究,并设计了一种新的腔长控制机构以减小控制镜的扭偏对陀螺产生的影响。利用有限元分析法对新腔长控制机构进行了优化设计和仿真。试验表明,新的腔长控制机构减小了控制镜的扭偏,使得激光陀螺的零偏稳定性由0.7/h提高至0.3/h。     

On the structural properties of small-world networks with range-limited shortcut links

We explore a new variant of Small-World Networks (SWNs), in which an additional parameter (r$r$) sets the length scale over which shortcuts are uniformly distributed. When r=0$r=0$ we have an ordered network, whereas r=1$r=1$ corresponds to the original Watts–Strogatz SWN model. These limited range SWNs have a similar degree distribution and scaling properties as the original SWN model. We observe the small-world phenomenon for r?1$r?1$, indicating that global shortcuts are not necessary for the small-world effect. For limited range SWNs, the average path length changes nonmonotonically with system size, whereas for the original SWN model it increases monotonically. We propose an expression for the average path length for limited range SWNs based on numerical simulations and analytical approximations.     

Density-based shrinkage for revealing hierarchical and overlapping community structure in networks

The investigation of community structure in networks is an important issue in many disciplines, which still remains a challenging task. First, complex networks often show a hierarchical structure with communities embedded within other communities. Moreover, communities in the network may overlap and have noise, e.g., some nodes belonging to multiple communities and some nodes marginally connected with the communities, which are called hub and outlier, respectively. Therefore, a good algorithm is desirable to be able to not only detect hierarchical communities, but also to identify hubs and outliers. In this paper, we propose a parameter-free hierarchical network clustering algorithm DenShrink. By combining the advantages of density-based clustering and modularity optimization methods, our algorithm can reveal the embedded hierarchical community structure efficiently in large-scale weighted undirected networks, and identify hubs and outliers as well. Moreover, it overcomes the resolution limit possessed by other modularity-based methods. Our experiments on the real-world and synthetic datasets show that DenShrink generates more accurate results than the baseline methods.     

钻石分形晶格上Ising模型的配分函数与关联函数

用参数变换方法,研究了钻石分形晶格上Ising自旋模型.精确求解了零场和非零场中系统的配分函数、自由能和关联函数,尤其推得了关联函数方程及其渐近行为的解析形式.结果表明，其关联行为与平移对称晶格上的Ising自旋系统类似. 关键词： Ising模型 外磁场 钻石分形晶格 关联函数     

On the extendedness of eigenstates in a hierarchical lattice: A critical view

We take a critical view at the basic definition of extended single particle states in a non-translationally invariant system. For this, we present the case of a hierarchical lattice and incorporate long range interactions that are also distributed in a hierarchical fashion. We show that it is possible to explicitly construct eigenstates with constant amplitudes (normalized to unity) at every lattice point for special values of the electron-energy. However, the end-to-end transmission, corresponding to the above energy of the electron in such a hierarchical system depends strongly on a special correlation between the numerical values of the parameters of the Hamiltonian. Keeping the energy and the distribution of the amplitudes invariant, one can transform the lattice from conducting to insulating simply by tuning the numerical values of the long range interaction. The values of these interactions themselves display a fractal character.     

具有幂率度分布的因特网平均最短路径长度估计

针对具有幂律度分布的复杂网络的平均最短路径长度进行了研究.给出了一个计算因特网平 均最短路径长度的公式.提出因特网的整体构造实质是以最小代价换取最大收益，从此出 发通过对因特网这类复杂网络平均最短路径长度影响因素分析，推断出网络最短路径长度分 布P(l)的基本性质，进而构造了一个只含参数α的P(l)的简洁形式，直接打通了拓扑具有幂 律度分布的因特网的度分布P(k)与网络最短路径长度分布P(l)之间的关系.然后说明了导出 的公式的物理意义，即参数α代表网络节点连接方式和网络的总边数对平均最短路径长 度的影响.此公式意味着只要掌握幂律P(k)～k-α中α值，就可以直接计算相应网 络的平均最短路径长度.通过对已知数据的计算，验证了公式的有效性.阐明了参数 α对网络设计的重要性和对网络功能的影响. 关键词： 复杂网络 幂律 度分布 平均最短路径长度     

激光陀螺腔长控制镜结构特性有限元分析

 为研究激光陀螺腔长控制反射镜结构参数对其性能影响,提出了建立腔长控制镜弹性、压电体耦合有限元模型并进行直接耦合场有限元分析的方法。通过编制ANSYS有限元软件宏文件,实现有限元模型与结构尺寸的自动同步。对某型激光陀螺腔长控制镜仿真计算表明,反射镜环槽内外径以及变形筋的厚度对其光程调节能力影响最大,并在此基础上实现了该型控制镜的优化设计。实验表明该方法对激光陀螺腔长控制镜的结构设计具有一定的指导意义。     

Adsorption of a flexible self-avoiding polymer chain: Exact results on fractal lattices

The large-scale behavior of surface-interacting self-avoiding polymer chains placed on finitely ramified fractal lattices is studied using exact recursion relations. It is shown how to obtain surface susceptibility critical indices and how to modify a scaling relation for these indices in the case of fractal lattices. We present the exact results for critical exponents at the point of adsorption transition for polymer chains situated on a class of Sierpinski gasket-type fractals. We provide numerical evidence for a critical behavior of the type found recently in the case of bulk self-avoiding random walks at the fractal to Euclidean crossover.     

Chinese lexical networks: The structure,function and formation

In this paper Chinese phrases are modeled using complex networks theory. We analyze statistical properties of the networks and find that phrase networks display some important features: not only small world and the power-law distribution, but also hierarchical structure and disassortative mixing. These statistical traits display the global organization of Chinese phrases. The origin and formation of such traits are analyzed from a macroscopic Chinese culture and philosophy perspective. It is interesting to find that Chinese culture and philosophy may shape the formation and structure of Chinese phrases.