有倾向性重连产生的反匹配网络

在具有网络结构的系统中度关联属性对于动力学行为具有重要的影响, 所以产生适当度关联网络的方法对于大量网络系统的研究具有重要的作用. 尽管产生正匹配网络的方法已经得到很好的验证, 但是产生反匹配网络的方法还没有被系统的讨论过. 重新连接网络中的边是产生度关联网络的一个常用方法. 这里我们研究使用重连方法产生反匹配无标度网络的有效性. 我们的研究表明, 有倾向的重连可以增强网络的反匹配属性. 但是有倾向重连不能使皮尔森度相关系数下降到-1, 而是存在一个依赖于网络参数的最小值. 我们研究了网络的主要参数对于网络度相关系数的影响, 包括网络尺寸, 网络的连接密度和网络节点的度差异程度. 研究表明在网络尺寸大的情况下和节点度差异性强的情况下, 重连的效果较差. 我们研究了真实Internet网络, 发现模型产生的网络经过重连不能达到真实网络的度关联系数.     

计算物理教学中基于FORTRAN的结果可视化方法

介绍在计算物理教学中配合F o r t r a n语言进行可视化输出的一种高效的方法. 以利萨如图形的模拟和 可视化输出作为例子介绍了这种可视化方法. 这种方法结合了F o r t r a n的系统函数功能和g n u p l o t的脚本功能, 可 以自动地把数据文件以图形的方式显示出来或者保存为图片文件. 整个可视化过程需要的绘图代码少, 操作简洁, 并且所用软件都是在科学研究中常用的免费软件. 通过这种方法能够低成本高效地实现计算结果的可视化     

Phase Locking Phenomena and Electroencephalogram-Like Activities in Dynamic Neuronal Systems

We study signal detection and transduction of dynamic neuronal systems under the influence of external noise,white and coloured. Based on simulations, we show explicitly phase locking phenomena between the output and the input of a single neuron and Electroencephalogram-like activities on neural networks with small-world connectivity. The numerical results prove that the dynamic neuronal system can be adjusted to an optimal sensitive state for signal processing in the presence of additive noise.     

Undetermination of the relation between network synchronizability and betweenness centrality

Betweenness centrality is taken as a sensible indicator of the synchronizability of complex networks. To test whether betweenness centrality is a proper measure of the synchronizability in specific realizations of random networks,this paper adds edges to the networks and then evaluates the changes of betweenness centrality and network synchronizability. It finds that the two quantities vary independently.     

Self-Organized Criticality in an Anisotropic Earthquake Model

We have made an extensive numerical study of a modified model proposed by Olami,Feder,and Christensen to describe earthquake behavior.Two situations were considered in this paper.One situation is that the energy of the unstable site is redistributed to its nearest neighbors randomly not averagely and keeps itself to zero.The other situation is that the energy of the unstable site is redistributed to its nearest neighbors randomly and keeps some energy for itself instead of reset to zero.Different boundary conditions were considered as well.By analyzing the distribution of earthquake sizes,we found that self-organized criticality can be excited only in the conservative case or the approximate conservative case in the above situations.Some evidence indicated that the critical exponent of both above situations and the original OFC model tend to the same result in the conservative case.The only difference is that the avalanche size in the original model is bigger.This result may be closer to the real world,after all,every crust plate size is different.     

分子动力学方法中速度标度因子的推导

在使用分子动力学方法对微正则系综进行模拟的情况下,以单原子粒子系统为例,给出了标度因子在国际单位制下的数学表达式.然后说明了如何把物理量重新标度得到无量纲公式,使得在模拟中计算更加方便.给出了无量纲化操作中时间单位的物理意义.最后,推导了趋衡过程的速度标度因子在教材中常用的数学表达式.     

Power-law statistics of synchronous transition in inhibitory neuronal networks

We investigate the relationship between the synchronous transition and the power law behavior in spiking networks which are composed of inhibitory neurons and balanced by dc current. In the region of the synchronous transition, the avalanche size and duration distribution obey a power law distribution. We demonstrate the robustness of the power law for event sizes at different parameters and multiple time scales. Importantly, the exponent of the event size and duration distribution can satisfy the critical scaling relation. By changing the network structure parameters in the parameter region of transition, quasicriticality is observed, that is, critical exponents depart away from the criticality while still hold approximately to a dynamical scaling relation. The results suggest that power law statistics can emerge in networks composed of inhibitory neurons when the networks are balanced by external driving signal.     

度关联无标度网络上的有倾向随机行走

有倾向随机行走是研究网络上数据包路由策略的有效方法. 由于许多真实技术网络包括互联网都具有负的度关联特征, 因此本文研究这种网络上的有倾向随机行走性质. 研究表明: 在负关联网络上粒子可以在连接度较大的节点上均匀分布, 而连接度小的节点上粒子较少; 负关联网络上随机行走的速度比非关联网络更快; 找到了负关联网络上的最佳倾向性系数, 在此情况下负关联网络上随机行走的速度远快于非关联网络. 负关联网络既可以利用度小的节点容纳粒子, 又可以利用度大的节点快速传输, 这是负关联网络上高行走效率产生的机制.     

Undetermination of the synchronizability and relation between network betweenness centrality

Betweenness centrality is taken as a sensible indicator of the synchronizability of complex networks. To test whether betweenness centrality is a proper measure of the synchronizability in specific realizations of random networks, this paper adds edges to the networks and then evaluates the changes of betweenness centrality and network synchronizability. It finds that the two quantities vary independently.     

关于新的教学模式下课堂探究环节的体会

结合自身的教学实践,从4个方面论述了在新教学模式下,做好课堂探究环节的体会。