二次耦合光力学系统的一类高维可控自持振荡行为

光力学系统通常的耦合是光压耦合, 是光场强度和纳米振子位移的一次耦合, 但在光场很强和振子振幅较大的光力学系统中, 非线性的耦合效应会变得非常明显和重要, 而且其所产生的非线性效应对制造具有特殊功能的光力学器件具有重要意义. 本文在二次耦合模型的基础上研究了光腔和振子之间通过二次耦合作用达到能 量平衡状态时系统所产生的自持振荡现象, 给出了二次耦合光力学系统的一般模型, 并通过数值方法研究了系统的定态行为和远离定态的极限环动力学行为, 标定了系统定态响应的稳定区域到极限环行为的分岔点. 发现在调节输入场参数(改变耦合系数)以及光腔和振子的弛豫系数时, 系统的相空间会出现一些稳定的高维自持振荡极限环. 通过数值分析发现该四维极限环在三维相空间的投影都趋于稳定的三维周期轨道, 并且该极限环轨道会随外部调控参数的改变发生扭动, 出现类似二维李萨如图样的稳定纽结结构. 该现象表明: 通过光场与振子的能量耦合, 利用一定强度的外部驱动可以有效控制振子的定态响应和振动, 可以让微振子锁定在具有一定振幅和频率的自发振动上, 为开发物理器件提供了可靠的光力学控制系统. 关键词： 光力系统 二次耦合 自持振荡 极限环     

基于有限差分法刚性圆柱体涡激振动响应特性数值研究

基于尾流振子模型对刚性圆柱体涡激振动响应特性进行数值研究.建立圆柱体结构振子及尾流振子之间的耦合方程,基于二阶精度中心差分格式对耦合模型先离散后迭代进行求解.对不同质量比及不同阻尼比圆柱体涡激振动响应的无量纲位移、无量纲升力、频率比及锁定区间等参数进行分析.结果表明数值方法可以很好地模拟刚性圆柱体的涡激振动响应特性.随着质量比的增加,锁定开始点逐渐延后,锁定结束点逐渐提前,锁定区间宽度逐渐变窄.     

自催化三分子模型内噪声随机共振

运用化学Langevin方程 ,数值研究了内噪声对单个和单向耦合自催化三分子模型动力学行为的影响 .研究发现 ,对于单个振子体系 ,内噪声可以诱导持续振荡 ,而且随着系统尺度的增大 ,信噪比经过一个极大值 ,从而证明了内噪声随机共振和最佳尺度效应的存在 ;对于单向耦合系统 ,信噪比还随耦合强度的变化而经过极大值 .此外 ,边界条件对耦合体系的内噪声随机共振行为有很大影响 ,非零流条件下 ,耦合可以增强内噪声随机共振 ,而零流条件下 ,耦合会抑制随机共振 ;当耦合强度适宜时 ,每个振子发生随机共振时的尺度几乎相同 ,表明最佳体系尺度和耦合强度有助于体系达到最佳的化学反应状态 .     

斯特林制冷机中压缩活塞振子与排出器振子相互影响的研究

从振动力学的角度来看 ,斯特林制冷机的工作实际上是压缩活塞振子与排出器振子两个振动系统的耦合与匹配 ,两振动系统的相互影响特性对提高整机性能具有非常重要的意义。文中首先给出了压缩活塞振子与排出器振子两个振动系统相互影响特性的理论分析 ,其次对二者相关影响特性的试验研究结果与模拟结果进行了对比分析和讨论     

耦合混沌振子系统完全同步的动力学行为

以耦合Duffing振子为对象，研究了混沌系统进入完全同步态时的一些动力学行为. 在对称耦合情况下，随着耦合系数的变化系统达到各个混沌振子的相轨道完全相同的同步态——完全同步态. 通过计算Lyapunov指数表明，此时系统的前两个横向Lyapunov指数相等，同时系统之间的时间关联表现出明显的规律性. 关键词： Duffing振子 混沌同步 Lyapunov指数     

振转耦合振子实验研究

介绍一个非常有趣的物理演示实验——振转耦合振子实验.弹簧振子实际上是一个具有两个振动模式的振动系统,两振动模式之间存在着耦合,振动能量将从一种模式向另一模式转移.在共振条件下可以实现能量在两模式之间的来回完全转移.     

基于Matlab/Simulink的三弹簧谐振子微振动的仿真实验

建立了三弹簧振子耦合系统微振动的实验模型,利用Matlab/Simulink仿真软件对该实验进行仿真建模,讨论系统在不同实验参数下从周期振动到混沌的各种动力学状态。仿真实验结果表明,参数的选取对系统微振动的动力学行为有着很大的影响。     

梯度耦合下神经元网络中靶波和螺旋波的诱发研究

神经系统内数量众多的神经元电活动的群体行为呈现一定的节律性和自组织性. 当网络局部区域存在异质性或者受到持续周期性刺激, 则在网络内诱发靶波, 且这些靶波如'节拍器'可调制介质中行波的诱发和传播. 基于Hindmarsh-Rose 神经元模型构造了最近邻连接下的二维神经元网络, 研究在非均匀耦合下神经元网络内有序波的诱发问题. 在研究中, 选定网络中心区域的耦合强度最大, 从中心向边界的神经元之间的耦合强度则按照阶梯式下降. 研究结果表明, 在恰当的耦合梯度下, 神经元网络内诱发的靶波或螺旋波可以占据整个网络, 并有效调制神经元网络的群体电活动, 使得整个网络呈现有序性. 特别地, 当初始值为随机值时, 梯度耦合也可以诱发稳定的有序态. 这种梯度耦合对网络群体行为调制的研究结果有助于理解神经元网络的自组织行为.     

相关激励形式下保守和非保守耦合振子的能量分布与功率流

作为相关输入形式下保守或非保守耦合系统统计能量分析的基础,本文主要研究耦合振子在比例相关输入条件下的能量分布与功率流.在推导了相关输入条件下耦合振子间的功率流与振子能量的基本关系式和功率平衡方程式及振子能量比的表达式之后,本文分别详细讨论了保守耦合振子和非保守耦合振子系统的能量分布和功率流问题,并与互不相关输入时耦合振子的能量分布与功率流的特点进行了比较,对于各种耦合阻尼情况下的振子能量分布与功率流也进行了数值计算,研究结果表明,相关输入下耦合振子的能量分布与功率流的特征与互不相关输入时的特征有着显著的差别.     

耦合相振子系统同步的序参量理论

节律行为,即系统行为呈现随时间的周期变化,在我们的周围随处可见.不同节律之间可以通过相互影响、相互作用产生自组织,其中同步是最典型、最直接的有序行为,它也是非线性波、斑图、集群行为等的物理内在机制.不同的节律可以用具有不同频率的振子(极限环)来刻画,它们之间的同步可以用耦合极限环系统的动力学来加以研究.微观动力学表明,随着耦合强度增强,振子同步伴随着动力学状态空间降维到一个低维子空间,该空间由序参量来描述.序参量的涌现及其所描述的宏观动力学行为可借助于协同学与流形理论等降维思想来进行.本文从统计物理学的角度讨论了耦合振子系统序参量涌现的几种降维方案,并对它们进行了对比分析.序参量理论可有效应用于耦合振子系统的同步自组织与相变现象的分析,通过进一步研究序参量的动力学及其分岔行为,可以对复杂系统的涌现动力学有更为深刻的理解.     

Emergence and evolution of multiple clusters of attracting agents

We investigate a multi-agent system with a behavior akin to the cluster formation in systems of coupled oscillators. The saturating attractive interactions between an infinite number of non-identical agents, characterized by a multimodal distribution of their natural velocities, lead to the emergence of clusters. We derive expressions that characterize the clusters, and calculate the asymptotic velocities of the agents and the critical value for the coupling strength under which no clustering can occur. The results are supported by mathematical analysis.For the particular case of a symmetric and unimodal distribution of the natural velocities, the relationship with the Kuramoto model of coupled oscillators is highlighted. While in the generic case the emergence of a cluster corresponds to a second-order phase transition, for a specific choice of the natural velocity distribution a first-order phase transition may occur, a phenomenon recently observed in the Kuramoto model. We also present an example for which the clustering behavior is quantitatively described in terms of the coupling strength.As an illustration of the potential of the model, we discuss how it applies to the dynamic process of opinion formation.     

Phase clustering in globally coupled photochemical oscillators

We experimentally investigate the formation of clusters in a population of globally coupled photochemical oscillators. The system consists of catalytic micro-particles in Belousov-Zhabotinsky solution and the coupling exploits the excitatory properties of light; an increase in the light intensity leads to excitation (“firing") of an oscillator. As the coupling strength is increased, a transition occurs from incoherence to clustering, whereby the oscillators split into synchronised groups, to complete synchronisation. Multistability is observed between a one-phase cluster (fully synchronised group) and two-phase clusters (two groups with the same frequency but different phases). The results are reproduced in simulations and we demonstrate that the heterogeneity of the population as well as the relaxational nature of the oscillators is important in the observation of clusters. We also examine the exploitation of the phase model for the prediction of clusters in experiments.     

Frequency clustering of coupled phase oscillators on small-world networks

We analyze the phenomenon of frequency clustering in a system of coupled phase oscillators. The oscillators, which in the absence of coupling have uniformly distributed natural frequencies, are coupled through a small-world network, built according to the Watts-Strogatz model. We study the time evolution and determine variations in the transient times depending on the disorder of the network and on the coupling strength. We investigate the effects of fluctuations in the average frequencies, and discuss the definition of the threshold for synchronization. We characterize the structure of clusters and the distribution of cluster sizes in the synchronization transition, and define suitable order parameters to describe the aggregation of the oscillators as the network disorder and the coupling strength change. The non-monotonic behavior observed in some order parameters is related to fluctuations in the mean frequencies.     

Relaxation dynamics of the Kuramoto model with uniformly distributed natural frequencies

The Kuramoto model describes a system of globally coupled phase-only oscillators with distributed natural frequencies. The model in the steady state exhibits a phase transition as a function of the coupling strength, between a low-coupling incoherent phase in which the oscillators oscillate independently and a high-coupling synchronized phase. Here, we consider a uniform distribution for the natural frequencies, for which the phase transition is known to be of first order. We study how the system close to the phase transition in the supercritical regime relaxes in time to the steady state while starting from an initial incoherent state. In this case, numerical simulations of finite systems have demonstrated that the relaxation occurs as a step-like jump in the order parameter from the initial to the final steady state value, hinting at the existence of metastable states. We provide numerical evidence to suggest that the observed metastability is a finite-size effect, becoming an increasingly rare event with increasing system size.     

Molecular communication through stochastic synchronization induced by extracellular fluctuations

We model a synthetic gene regulatory network in a microbial cell, and investigate the effect of noises on cell-cell communication in a well-mixed multicellular system. A biologically plausible model is developed for cellular communication in an indirectly coupled multicellular system. Without extracellular noises, all cells, in spite of interaction among them, behave irregularly due to independent intracellular noises. On the other hand, extracellular noises that are common to all cells can induce collective dynamics and stochastically synchronize the multicellular system by actively enhancing the integrated interchange of signaling molecules.     

Modeling of intercellular synchronization in the Drosophila circadian clock

In circadian rhythm generation,intercellular signaling factors are shown to play a crucial role in both sustaining intrinsic cellular rhythmicity and acquiring collective behaviours across a population of circadian neurons.However,the physical mechanism behind their role remains to be fully understood.In this paper,we propose an indirectly coupled multicellular model for the synchronization of Drosophila circadian oscillators combining both intracellular and intercellular dynamics.By simulating different experimental conditions,we find that such an indirect coupling way can synchronize both heterogeneous self-sustained circadian neurons and heterogeneous mutational damped circadian neurons.Moreover,they can also be entrained to ambient light-dark(LD) cycles depending on intercellular signaling.     

Partitioning networks into clusters and residuals with average association

We investigate the problem of detecting clusters exhibiting higher-than-average internal connectivity in networks of interacting systems. We show how the average association objective formulated in the context of spectral graph clustering leads naturally to a clustering strategy where each system is assigned to at most one cluster. A residual set is formed of the systems that are not members of any cluster. Maximization of the average association objective leads to a discrete optimization problem, which is difficult to solve, but a relaxed version can be solved using an eigendecomposition of the connectivity matrix. A simple approach to extracting clusters from a relaxed solution is described and developed by applying a variance maximizing solution to the relaxed solution, which leads to a method with increased accuracy and sensitivity. Numerical studies of theoretical connectivity models and of synchronization clusters in a lattice of coupled Lorenz oscillators are conducted to show the efficiency of the proposed approach. The method is applied to an experimentally obtained human resting state functional magnetic resonance imaging dataset and the results are discussed.     

Clustering zones in the turbulent phase of a system of globally coupled chaotic maps

The paper develops an approach to investigate the clustering phenomenon in the system of globally coupled chaotic maps first introduced by Kaneko in 1989. We obtain a relation between the transverse and longitudinal multipliers of the periodic clusters and prove the stability of these clusters for the case of symmetric, equally populated distributions between subclusters. Stable clusters emanate from the periodic windows of the logistic map and extend far into the turbulent phase. By numerical simulations we estimate a total basin volume of low-periodic clusters issued from the period-3 window and analyze the basin structure. The complement to the basin volume is ascribed to chaotic, very asymmetric high-dimensional clusters that are characterized by the presence of one or more leading clusters, accumulating about half of the oscillators while all the remaining oscillators do not cluster at all.     

Finite-size corrections to scaling behavior in sorted cell aggregates

Cell sorting is a widespread phenomenon pivotal to the early development of multicellular organisms. In vitro cell sorting studies have been instrumental in revealing the cellular properties driving this process. However, these studies have as yet been limited to two-dimensional analysis of three-dimensional cell sorting events. Here we describe a method to record the sorting of primary zebrafish ectoderm and mesoderm germ layer progenitor cells in three dimensions over time, and quantitatively analyze their sorting behavior using an order parameter related to heterotypic interface length. We investigate the cell population size dependence of sorted aggregates and find that the germ layer progenitor cells engulfed in the final configuration display a relationship between total interfacial length and system size according to a simple geometrical argument, subject to a finite-size effect.     

Chaotic cluster itinerancy and hierarchical cluster trees in electrochemical experiments

Experiments on an array of 64 globally coupled chaotic electrochemical oscillators were carried out. The array is heterogeneous due to small variations in the properties of the electrodes and there is also a small amount of noise. Over some ranges of the coupling parameter, dynamical clustering was observed. The precision-dependent cluster configuration is analyzed using hierarchical cluster trees. The cluster configurations varied with time: spontaneous changes of number of clusters and their configurations were detected. Simple transitions occurred with the switch of a single element or groups of elements. During more complicated transitions subclusters were exchanged among clusters but original cluster configurations were revisited. At weaker coupling the system itinerated among lower-dimensional quasistationary chaotic two-cluster states and higher-dimensional states with many clusters. In this region the transitions showed characteristics of on-off intermittency.