全局耦合网络上的两种类集团的聚集-湮没反应动力学

利用Monte-Carlo模拟研究了全局耦合网络上扩散限制的不可逆聚集-湮没过程的动力学行为. 在系统中, 同种类集团相遇, 将发生聚集反应; 不同种类的集团相遇, 则发生部分湮没反应. 模拟结果表明:1) 当两种粒子初始浓度相等时, 系统长时间演化后, 集团浓度c(t)和粒子浓度g(t)呈现幂律形式, c(t)～t^{- α}和g(t)～t^-β, 其中幂指数α 和β 满足α=2β 的关系, 且α=2/(2 + q); 集团大小分布随时间的演化满足标度律, a_kt)=k^-τt^-ω\varPhi (k/t^z), 其中τ≈-1.27q, ω≈(3 + 1.27q)/(2 + q), z=α/2=1/(2 + q); 2) 当两种粒子初始浓度不相等时, 系统经长时间演化后, 初始浓度较小的种类完全湮没, 而初始浓度较大的那个种类的集团浓度c_A(t)仍具有幂律形式, c_A(t)～t^-α, 其中α=1/(1+q), 其集团大小分布随时间的演化也满足标度律, 标度指数为τ≈-1.27q, ω≈(2 + 1.27q)/(1 + q)和z=α=1/(1 + q). 模拟结果与已报道的理论分析结果相符得很好.     

全局耦合网络上的两种类集团的聚集-湮没反应动力学

利用Monte-Carlo模拟研究了全局耦合网络上扩散限制的不可逆聚集-湮没过程的动力学行为. 在系统中, 同种类集团相遇, 将发生聚集反应; 不同种类的集团相遇, 则发生部分湮没反应. 模拟结果表明:1) 当两种粒子初始浓度相等时, 系统长时间演化后, 集团浓度c(t)和粒子浓度g(t)呈现幂律形式, c(t)～t^{- α}和g(t)～t^-β, 其中幂指数α 和β 满足α=2β 的关系, 且α=2/(2 + q); 集团大小分布随时间的演化满足标度律, a相似文献   

两种类粒子间的聚集与完全湮没竞争过程的标度行为

考虑一个由两种类粒子组成的系统,同种类粒子相遇时发生不可逆的聚集反应;不同种类的粒子相遇时,则发生不可逆的完全湮没反应.利用Mont-Carlo模拟各种参数条件下的粒子聚集-完全湮没竞争过程,分析了聚集速率、湮没速率以及初始浓度分布对系统动力学行为的影响.模拟结果表明:1)粒子大小分布总是满足一定的标度律;2)当两种粒子的聚集速率都等于湮没速率的2倍时,粒子大小分布的标度指数与粒子初始浓度分布有关;3)其余情况下,标度指数则取决于反应速率的相对大小.此外,当两种粒子的聚集速率都大于或等于湮没速率的两倍,系统的所有粒子将完全湮没;当且仅当至少一种粒子的聚集速率小于湮没速率的两倍,聚集速率较小的那一种粒子才可能最终保存下来.模拟结果与已报道的理论分析结果符合得较好.     

小世界网络中的量子纠缠渗流

本文研究了小世界复杂网络中的长程量子纠缠态的制备。提出了量子纠缠渗流优化网络量子通信的方案。通过在经典纠缠渗流协议(CEP)中引入局域化的"target-swap"量子操作,形成量子纠缠渗流协议(QEP)。研究表明QEP在长程纠缠制备的效能方面明显优于CEP,通过度分布变化的分析解释了QEP具有优势的原因。     

小世界网络上螺旋波失稳的研究

利用数值计算和分析,研究了螺旋波失稳与重联概率p之间的关系.通过对基于FitzHugh-Nagumo神经元模型的小世界网络的计算和分析,发现螺旋波的小世界效应失稳具有全局性作用和失稳后再激发作用等特点,是不同于爱克豪斯(Eckhaus)失稳和多普勒(Doppler)失稳的又一种新的重要失稳方式. 关键词： 螺旋波 失稳 小世界网络 重联概率     

小世界网络中投资者的从众行为

研究了社会网络中个体连边不同的重连概率下股票市场的收益率的概率分布情况,发现重连概率较小时收益率呈现了波动丛集性、收益率的概率分布呈现尖峰胖尾等典型现象。此外,股票的原始收益率不具有长记忆性,而原始收益率取绝对值后却具有长记忆性。     

反应限制聚集模型的动力学行为的研究

根据反应限制聚集（reaction limited aggregation, RLA）模型,研究表面活性剂存在时 的薄膜外延生长动力学过程. 研究结果表明,在二维岛的生长初期,分形岛与紧致岛具有不 同的岛密度和“死”原子密度（岛的相对总面积）增长方式：分形岛密度随覆盖率生长指数 小于1,紧致岛密度的生长指数大于1;分形岛相对总面积随覆盖率线性增长,紧致岛相对总 面积随覆盖率非线性增长. 关键词： 反应限制聚集模型 岛密度 “死”原子密度     

基于小世界网络模型的光伏微网系统同步方法研究

建立了光伏微网逆变器严格的分段线性状态方程,分析其非线性动力学行为,然后以光伏微网逆变器为网络节点,研究基于小世界网络模型的光伏微网系统同步方法,并与基于邻近耦合规则的光伏微网同步进行比较.研究发现,基于小世界网络模型的光伏微网系统比传统的基于邻近耦合规则的光伏微网系统具有更短的同步时间,在外加扰动的情况下也具有更快的恢复时间.     

小世界网络的临界阈值

“小世界”网络可以为真实世界提供大量的信息和各种状态的模拟，例如真实世界中的互联网到供电的电力网，从生活中常发生的流行病传播到大选时的民意测验等都是一种小世界网络．一个“小世界”网络一般包含一定数量的网点，称为网络中心．它们具有非常广泛的联系，通常可以从一个网络中心经过简单的几步就能进行到其它网点．     

小世界网络与无标度网络的社区结构研究

模块性(modularity)是度量网络社区结构(community structure)的主要参数.探讨了Watts和Strogatz的小世界网络(简称W-S模型)以及Barabàsi 等的B-A无标度网络(简称B-A模型)两类典型复杂网络模块性特点.结果显示，网络模块性受到网络连接稀疏的影响，W-S模型具有显著的社区结构，而B-A模型的社区结构特征不明显.因此，应用中应该分别讨论网络的小世界现象和无标度特性.社区结构不同于小世界现象和无标度特性，并可以利用模块性区别网络类型，因此网络复杂性指标应该包括 关键词： 模块性 社区结构 小世界网络 无标度网络     

小世界生物神经网络的相干共振研究

研究了无外界周期信号时Hodgkin-Huxley模型小世界生物神经网络的非线性响应.数值模拟结果显示：当噪声强度取某一有限值时,峰序列有序度可以达到最大,即产生相干共振现象.同时发现： 随着网络规模N的变化,相干共振系数cv的极小值不是一个,而是多个.这表明相干共振可发生在神经元集群数目特定的不同规模的网络中. 关键词： 相干共振 有序度 小世界网络 生物神经网络     

An effective method to improve the robustness of small-world networks under attack

In this study, the robustness of small-world networks to three types of attack is investigated. Global efficiency is introduced as the network coefficient to measure the robustness of a small-world network. The simulation results prove that an increase in rewiring probability or average degree can enhance the robustness of the small-world network under all three types of attack. The effectiveness of simultaneously increasing both rewiring probability and average degree is also studied, and the combined increase is found to significantly improve the robustness of the small-world network.Furthermore, the combined effect of rewiring probability and average degree on network robustness is shown to be several times greater than that of rewiring probability or average degree individually. This means that small-world networks with a relatively high rewiring probability and average degree have advantages both in network communications and in good robustness to attacks. Therefore, simultaneously increasing rewiring probability and average degree is an effective method of constructing realistic networks. Consequently, the proposed method is useful to construct efficient and robust networks in a realistic scenario.     

Scaling of weighted spectral distribution in weighted small-world networks

Many real-world systems can be modeled by weighted small-world networks with high clustering coefficients. Recent studies for rigorously analyzing the weighted spectral distribution(W SD) have focused on unweighted networks with low clustering coefficients. In this paper, we rigorously analyze the W SD in a deterministic weighted scale-free small-world network model and find that the W SD grows sublinearly with increasing network order(i.e., the number of nodes) and provides a sensitive discrimination for each input of this model. This study demonstrates that the scaling feature of the W SD exists in the weighted network model which has high and order-independent clustering coefficients and reasonable power-law exponents.     

耦合小世界神经网络的随机共振

噪声广泛存在于生物神经系统中,对系统功能具有重要作用.采用神经元二维映射模型构建一个复杂神经网络,由多个小世界子网络构成,研究了Gaussian白噪声诱导的随机共振现象.研究发现,只有合适的噪声强度才能使神经网络对输入刺激信号的频率响应达到峰值.另外,网络结构对系统随机共振特性有重要影响.在固定的耦合强度下,存在一个最优的局部小世界子网络结构,使得整个系统的频率响应最佳.     

Kinetics of an n-Species Aggregation Chain Model with Complete Annihilation

The kinetic behavior of an n-species (n ≥ 3) aggregation-annihilation chain reaction model is studied. In this model, an irreversible aggregation reaction occurs between any two clusters of the same species, and an irreversible complete annihilation reaction occurs only between two species with adjacent number. Based on the rnean-field theory, we investigate the rate equations of the process with constant reaction rates to obtain the asymptotic solutions of the clustermass distributions for the system. The results show that the kinetic behavior of the system not only depends crucially on the ratio of the aggregation rate I to the annihilation rate J, but also has relation with the initial concentration of each species and the species number's odevity. We find that the cluster-mass distribution of each species obeys always a scaling law. The scaling exponents may strongly depend on the reaction rates for most cases, however, for the case in which the ratio of the aggregation rate to the annihilation rate is equal to a certain value, the scaling exponents are only dependent on the initial concentrations of the reactants.     

Phase synchronization on small-world networks with community structure

In this paper, we propose a simple model that can generate small-world network with community structure. The network is introduced as a tunable community organization with parameter r, which is directly measured by the ratio of inter- to intra-community connectivity, and a smaller r corresponds to a stronger community structure. The structure properties, including the degree distribution, clustering, the communication efficiency and modularity are also analysed for the network. In addition, by using the Kuramoto model, we investigated the phase synchronization on this network, and found that increasing the fuzziness of community structure will markedly enhance the network synchronizability; however, in an abnormal region (r ≤ 0.001), the network has even worse synchronizability than the case of isolated communities (r = 0). Furthermore, this network exhibits a remarkable synchronization behaviour in topological scales: the oscillators of high densely interconnected communities synchronize more easily, and more rapidly than the whole network.