点电荷和介质球系统的镜像电荷分布

用镜像法处理介质中的静电问题,一般书刊上只论及到两种情形:一是两均匀电介质交界面为一无限大平面,在其中一种介质中有一点电荷;二是无限长均匀电介质圆柱置于另一均匀介质之中,在圆柱内或圆柱外有一与其轴线平行的无限长线电荷.在这两种情形中,电势都可以用简单的镜像系表示     

光学双稳系统中不稳态的控制

采用一种简便易行的控制方法,对一个由延时微分方程描述的无穷维光学系统的双稳行为进行控制,成功地稳定了滞后循回曲线中不稳定的中间态;抑制了该系统的Hopf分岔和倍周期分岔.这些数值控制结果均是在模拟该光学系统的实验条件下完成的.     

带注入信号的双光子激光器的双稳性质

以原子均匀展宽的单模环形双光子激光器为模型,用半经典方法讨论有注入信号的双光子激光器的双稳性质。论证在谐调情况下该系统会出现双稳态,并且对于“好腔”和“坏腔”极限,通过绝热消除描述了双稳性导致的输出光的瞬态行为和滞后循环。发现在低分支是单调地趋向稳态,而在高分支是振荡地趋向稳态;在输出场不连续变化之处出现临界慢化现象。     

Synchronization of time-delay chaotic systems on small-world networks with delayed coupling

By using the well-known Ikeda model as the node dynamics, this paper studies synchronization of time-delay systems on small-world networks where the connections between units involve time delays. It shows that, in contrast with the undelayed case, networks with delays can actually synchronize more easily. Specifically, for randomly distributed delays, time-delayed mutual coupling suppresses the chaotic behaviour by stabilizing a fixed point that is unstable for the uncoupled dynamical system.     

Effects of average degree of network on an order-disorder transition in opinion dynamics

We have investigated the influence of the average degree \langle k \rangle of network on the location of an order--disorder transition in opinion dynamics. For this purpose, a variant of majority rule (VMR) model is applied to Watts--Strogatz (WS) small-world networks and Barab\'{a}si--Albert (BA) scale-free networks which may describe some non-trivial properties of social systems. Using Monte Carlo simulations, we find that the order--disorder transition point of the VMR model is greatly affected by the average degree \langle k \rangle of the networks; a larger value of \langle k \rangle results in a more ordered state of the system. Comparing WS networks with BA networks, we find WS networks have better orderliness than BA networks when the average degree \langle k \rangle is small. With the increase of \langle k \rangle, BA networks have a more ordered state. By implementing finite-size scaling analysis, we also obtain critical exponents \beta/\nu, \gamma/\nu and 1/\nu for several values of average degree \langle k \rangle. Our results may be helpful to understand structural effects on order--disorder phase transition in the context of the majority rule model.     

Synchronization of Chaos in Time-Delayed Systems under Parameter Mismatch

We report on synchronization between two identical time delay chaotic systems under parameter mismatch. It overcomes some limitations of the previous work where synchronization and antisynchronization has been investigated only in finite-dimensional chaotic systems under parameter mismatch, so we can achieve synchronization and antisynchronization in infinite- dimensional chaotic systems under parameter mismatch, For infinite-dimensional systems modelled by delay differential equations, we find stable synchronization and antisynehronization in long-, moderate- and short-time delay regions, in particular for the hyperchaotic ease.     

Memory-Based Boolean Game and Self-Organized Phenomena on Networks

We study a memory-based Boolean game （MBBG） taking place on a regular ring, wherein each agent acts according to its local optimal states of the last M time steps recorded in memory, and the agents in the minority are rewarded. One free parameter p between 0 and 1 is introduced to denote the strength of the agent willing to make a decision according to its memory. It is found that giving proper willing strength p, the MBBG system can spontaneously evolve to a state of performance better than the random game; while for larger p, the herd behaviour emerges to reduce the system profit. By analysing the dependence of dynamics of the system on the memory capacity M, we find that a higher memory capacity favours the emergence of the better performance state, and effectively restrains the herd behaviour, thus increases the system profit. Considering the high cost of long-time memory, the enhancement of memory capacity for restraining the herd behaviour is also discussed, and M =5 is suggested to be a good choice.     

Evolution of Weighted Networks with Exponential Aging of Sites

We study the growth of weighted networks with exponential aging of sites. Each new vertex of the network is connected to some old vertices with proportional (i) to the strength of the old vertex and (ii) to e^-αT, where T is the age of the old vertex and α is a positive constant. As soon as the preferential attachment is modified by such factors, the interesting quantities of the produced network (the vertex degree, vertex strength, clustering coefficient and average path length) will be significantly transformed.     

Walks on Weighted Networks

We investigate the dynamics of random walks on weighted networks. Assuming that the edge weight and the node strength are used as local information by a random walker. Two kinds of walks, weight-dependent walk and strength-dependent walk, are studied. Exact expressions for stationary distribution and average return time are derived and confirmed by computer simulations. The distribution of average return time and the mean-square displacement are calculated for two walks on the Barrat-Barthelemy-Vespignani （BBV） networks. It is found that a weight-dependent walker can arrive at a new territory more easily than a strength-dependent one.