基于动力学同步的复杂网络结构识别速度研究

基于动力学同步的复杂网络结构识别是探测复杂网络拓扑性质的重要方面, 其中识别速度是一个重要但鲜有讨论问题. 首先对弱耦合条件下耦合非线性振子网络结构识别速度的问题进行了研究. 发现识别速度随耦合强度成正比增长. 通过解析讨论, 肯定了这一关系是普适的. 之后基于我们最近提出的反复驱动识别方法, 将处于同步稳定态的耦合区域也纳入研究范围. 在这种情形下存在一个最佳的时间片段的长度使识别速度达到极值. 这些结论加深了对时间序列中蕴含的拓扑结构信息量的理解.     

Quantum speed limits for Bell-diagonal states

The lower bounds of the evolution time between two distinguishable states of a system, defined as quantum speed limit time, can characterize the maximal speed of quantum computers and communication channels. We study the quantum speed limit time between the composite quantum states and their target states in the presence of nondissipative decoherence.For the initial states with maximally mixed marginals, we obtain the exact expressions of the quantum speed limit time which mainly depend on the parameters of the initial states and the decoherence channels. Furthermore, by calculating the quantum speed limit time for the time-dependent states started from a class of initial states, we discover that the quantum speed limit time gradually decreases in time, and the decay rate of the quantum speed limit time would show a sudden change at a certain critical time. Interestingly, at the same critical time, the composite system dynamics would exhibit a sudden transition from classical decoherence to quantum decoherence.     

Modulation speed limits of a graphene-based modulator

Electro-optical modulators, working at near-infrared range are a key device in modern optical system. Modulation speed is an important parameter to evaluate the performance of an electro-optical modulator. However, the modulation speed which is controlled by contact resistance and quantum capacitance of a graphene-based modulator is difficult to calculate in previous numerical simulation. In this paper, we proposed a method based on a simple structure to calculate the modulation speed. The simulation results show that the modulation speed is approximate 1.2 GHz which is consistent with the experimental results. And the dependence of the modulation speed on the effective oxide thickness (EOT) and doping of graphene are investigated in our work. Meanwhile, we optimize the structure parameters of modulator to promote the modulation speed which can be increased to ~3.6 GHz. The proposed method to evaluate and optimize the modulation speed could have many applications potential for various graphene-based devices.     

Speed of complex network synchronization

Synchrony is one of the most common dynamical states emerging on networks. The speed of convergence towards synchrony provides a fundamental collective time scale for synchronizing systems. Here we study the asymptotic synchronization times for directed networks with topologies ranging from completely ordered, grid-like, to completely disordered, random, including intermediate, partially disordered topologies. We extend the approach of master stability functions to quantify synchronization times. We find that the synchronization times strongly and systematically depend on the network topology. In particular, at fixed in-degree, stronger topological randomness induces faster synchronization, whereas at fixed path length, synchronization is slowest for intermediate randomness in the small-world regime. Randomly rewiring real-world neural, social and transport networks confirms this picture.     

Function projective synchronization in drive-response dynamical network

In this Letter, the function projective synchronization in the drive-response dynamical network is investigated, where the response dynamical network is affected not only by the drive system, but also coupled via a linearly feedback scheme. Based on Lyapunov stability theory, it is shown that the function projective synchronization with desired scaling function can be realized in the drive-response dynamical network by a simple control law. Moreover it is no need for the scaling function to be differentiable, bounded and nonzero all the time. The numerical simulations are provided to verify the theoretical result.     

Explosive synchronization in network of mobile oscillators

Recently, the explosive synchronization (ES) has attracted great interests. Motivated by the recent dynamic framework of complex network, we focus on the network of mobile oscillators and study synchronization phenomenon. The local synchronous order parameter of the neighbors of the oscillator is used as the controllable variable to adjust the coupling strength of the oscillator. Hence, it can be seen as a kind of adaptive strategy. By numerical simulation, we find that ES can be observed in the dynamic network of mobile oscillators, accompanying with hysteresis loop, as the coupling strength increases gradually. It is found that the critical value of coupling strength and hysteresis loop width is affected by the natural frequency distribution and the number of neighbors the oscillator owning. It can be deduced that ES will be motivated by increasing the number of oscillators in the network. Meanwhile, our results are feasible to different natural frequency distributions, such as Lorentzian, Gaussian power-law, and Rayleigh distribution, whether it is symmetric or not.     

Analyzing and controlling the network synchronization regions

In this paper, the commonly concerned issue of synchronization regions of complex dynamical networks is investigated, for the case when the synchronous state is an equilibrium point. Some simple sufficient conditions for a network to have or have no unbounded synchronization regions of the form (-∞,α₁) are established, where α₁ is a constant. In addition, a sufficient condition for the existence of a bounded synchronization region of the form (α₂,α₃) is derived, where α₂ and α₃ are constants, by using the parameter-dependent Lyapunov function method. Furthermore, some effective controller design methods are presented that can change the synchronization regions, thereby managing the synchronizability of the network. Finally, some numerical examples are given to show that a dynamical network may have disconnected synchronization regions, particularly it may have the coexistence of unbounded and bounded synchronization regions in the form of (-∞,α₁)∪(α₂,α₃).     

Optimal pinning synchronization on directed complex network

In this paper, pinning synchronization on directed network was considered. By analyzing, some general synchronization criteria on directed network were established. And then, we verified it on directed globally coupled network, directed scale-free network, and directed small-world network, respectively. The pinning nodes were selected, respectively, according to order of in-degrees and out-degrees. Through comparing and analyzing simulations, the optimal pinning scheme was found, and a practical principle was induced finally.     

Rich-club network topology to minimize synchronization cost due to phase difference among frequency-synchronized oscillators

As exemplified by power grids and large-scale brain networks, some functions of networks consisting of phase oscillators rely on not only frequency synchronization, but also phase synchronization among the oscillators. Nevertheless, even after the oscillators reach frequency-synchronized status, the phase synchronization is not always accomplished because the phase difference among the oscillators is often trapped at non-zero constant values. Such phase difference potentially results in inefficient transfer of power or information among the oscillators, and avoids proper and efficient functioning of the networks. In the present study, we newly define synchronization cost by using the phase difference among the frequency-synchronized oscillators, and investigate the optimal network structure with the minimum synchronization cost through rewiring-based optimization. By using the Kuramoto model, we demonstrate that the cost is minimized in a network with a rich-club topology, which comprises the densely-connected center nodes and low-degree peripheral nodes connecting with the center module. We also show that the network topology is characterized by its bimodal degree distribution, which is quantified by Wolfson’s polarization index.     

Choosing effective controlled nodes for scale-free network synchronization

Previous studies concerning pinning control of complex-network synchronization have very often demonstrated that in an unweighted symmetrical scale-free network, controlling the high-degree nodes is more efficient than controlling randomly chosen ones; due to the heterogeneity of the node-degree or edge-connection distribution of the scale-free network, small-degree nodes have relatively high probabilities of being chosen at random but their control has less influence on the other nodes through the network. This raises the question of whether or not controlling the high-degree nodes is always better than controlling the small ones in scale-free networks. Our answer to this is yes and no. In this study, we carry out extensive numerical simulations to show that in an unweighted symmetrical Barabasi-Albert scale-free network, when the portion of controlled nodes is relatively large, controlling the small nodes becomes better than controlling the big nodes and controlling randomly chosen nodes has approximately the same effect as controlling the big ones. However, we also show that for normalized weighted scale-free networks, controlling the big nodes is in fact always better than controlling the small ones.     

Intermittent synchronization in a network of bursting neurons

Synchronized oscillations in networks of inhibitory and excitatory coupled bursting neurons are common in a variety of neural systems from central pattern generators to human brain circuits. One example of the latter is the subcortical network of the basal ganglia, formed by excitatory and inhibitory bursters of the subthalamic nucleus and globus pallidus, involved in motor control and affected in Parkinson's disease. Recent experiments have demonstrated the intermittent nature of the phase-locking of neural activity in this network. Here, we explore one potential mechanism to explain the intermittent phase-locking in a network. We simplify the network to obtain a model of two inhibitory coupled elements and explore its dynamics. We used geometric analysis and singular perturbation methods for dynamical systems to reduce the full model to a simpler set of equations. Mathematical analysis was completed using three slow variables with two different time scales. Intermittently, synchronous oscillations are generated by overlapped spiking which crucially depends on the geometry of the slow phase plane and the interplay between slow variables as well as the strength of synapses. Two slow variables are responsible for the generation of activity patterns with overlapped spiking, and the other slower variable enhances the robustness of an irregular and intermittent activity pattern. While the analyzed network and the explored mechanism of intermittent synchrony appear to be quite generic, the results of this analysis can be used to trace particular values of biophysical parameters (synaptic strength and parameters of calcium dynamics), which are known to be impacted in Parkinson's disease.     

Experimental evidence of synchronization of time-varying dynamical network

We investigate synchronization of time varying networks and stability conditions. We derive interesting relations between the critical coupling constants for synchronization and switching times for time-varying and time average networks. The relations are based on the additive property of Lyapunov exponents and are verified experimentally in electronic circuit.     

无线自组织网络时钟同步系统设计研究

根据在时钟同步方面(Wireless Sensor Network,WSN)无线传感器网络和自组织网络具有的相似属性,WSN时钟同步方法可以运用到自组织网络当中。由于影响时钟同步的要素很多,存在抗干扰性弱、同步精度差等问题。根据主从同步的特点,运用脉冲位置测量法,无线传感器与网络时钟之间的关系,构建出一套相对完整的无线自组织网络时钟同步系统,并通过实验成功实现网络时钟数据的同步。     

A cost-efficient quantum access network with qubit-based synchronization

Quantum key distribution(QKD) is a physical layer encryption technique that enables two distant parties to exchange secure keys with information-theoretic security. In the last two decades, QKD has transitioned from laboratory research to real-world applications, including multi-user quantum access networks(QANs). This network structure allows users to share a single-photon detector at a network node through time-division multiplexing, thereby significantly reducing the network cost. However, cu...     

最优的Newman-Watts网络与遍历网络的同步

在Hindmarsh-Rose神经元动力系统中研究了Newman-Watts （NW）网络的同步,给出了一些最优同步网络的拓扑结构. 数值结果表明：NW网络的同步能力主要由耦合点在耦合空间的分布决定,耦合点分布均匀的NW网络一般具有较强的同步能力;在给定连边数的情况下,可能存在多个结构不同的最优同步网络,最优同步网络具有最强的同步能力、均匀的度分布和较好的对称性,但是其对称性不一定是最好的. 最优同步网络一般是非规则网络,但在少数情况下,规则网络也有可能是最优同步网络. 提出了一种新的网络——遍历网络,该网络具有最优同步网络的特点和很强的同步能力. 关键词： Newman-Watts网络 对称度 耦合空间 同步     

Stochastic resonance and synchronization behaviors of excitatory-inhibitory small-world network subjected to electromagnetic induction

The phenomenon of stochastic resonance and synchronization on some complex neuronal networks have been investigated extensively.These studies are of great significance for us to understand the weak signal detection and information transmission in neural systems.Moreover,the complex electrical activities of a cell can induce time-varying electromagnetic fields,of which the internal fluctuation can change collective electrical activities of neuronal networks.However,in the past there have been a few corresponding research papers on the influence of the electromagnetic induction among neurons on the collective dynamics of the complex system.Therefore,modeling each node by imposing electromagnetic radiation on the networks and investigating stochastic resonance in a hybrid network can extend the interest of the work to the understanding of these network dynamics.In this paper,we construct a small-world network consisting of excitatory neurons and inhibitory neurons,in which the effect of electromagnetic induction that is considered by using magnetic flow and the modulation of magnetic flow on membrane potential is described by using memristor coupling.According to our proposed network model,we investigate the effect of induced electric field generated by magnetic stimulation on the transition of bursting phase synchronization of neuronal system under electromagnetic radiation.It is shown that the intensity and frequency of the electric field can induce the transition of the network bursting phase synchronization.Moreover,we also analyze the effect of magnetic flow on the detection of weak signals and stochastic resonance by introducing a subthreshold pacemaker into a single cell of the network and we find that there is an optimal electromagnetic radiation intensity,where the phenomenon of stochastic resonance occurs and the degree of response to the weak signal is maximized.Simulation results show that the extension of the subthreshold pacemaker in the network also depends greatly on coupling strength.The presented results may have important implications for the theoretical study of magnetic stimulation technology,thus promoting further development of transcranial magnetic stimulation(TMS) as an effective means of treating certain neurological diseases.     

Local effects in synchronization on an extended network model

We investigate collective behaviors of coupled phase oscillators on an extended network model which can develop two fundamentally different topologies, scale-free or exponential. Each component of the network is assumed as an oscillator and that each interacts with the others following the Kuramoto model. The order parameters that measure synchronization of phases and frequencies are computed by means of dynamic simulations. It is found that system's collective behaviors exhibit strong dependence on local events: addition of new links will improve network synchronizability while rewiring of links will decrease synchronization.     

Cluster synchronization in a network of non-identical dynamic systems

Cluster synchronization in a network of non-identical dynamic systems is studied in this paper, using two-cluster synchronization for detailed analysis and discussion. The results show that the common intercluster coupling condition is not always needed for the diffusively coupled network. Several sufficient conditions are obtained by using the Schur unitary triangularization theorem, which extends previous results. Some numerical examples are presented for illustration.     

Burst synchronization transitions in a neuronal network of subnetworks

In this paper, the transitions of burst synchronization are explored in a neuronal network consisting of subnetworks. The studied network is composed of electrically coupled bursting Hindmarsh-Rose neurons. Numerical results show that two types of burst synchronization transitions can be induced not only by the variations of intra- and intercoupling strengths but also by changing the probability of random links between different subnetworks and the number of subnetworks. Furthermore, we find that the underlying mechanisms for these two bursting synchronization transitions are different: one is due to the change of spike numbers per burst, while the other is caused by the change of the bursting type. Considering that changes in the coupling strengths and neuronal connections are closely interlaced with brain plasticity, the presented results could have important implications for the role of the brain plasticity in some functional behavior that are associated with synchronization.