arXiv subjects

Changsong Zhou

Publications and source records attributed to Changsong Zhou.

At least 37 records · Page 2Linked to original sources

arXiv2015

Unfolding large-scale online collaborative human dynamics

Large-scale interacting human activities underlie all social and economic phenomena, but quantitative understanding of regular patterns and mechanism is very challenging and still rare. Self-organized online collaborative activities with precise record of event timing provide unprecedented opportunity. Our empirical analysis of the history of millions of updates in Wikipedia shows a universal double power-law distribution of time intervals between consecutive updates of an article. We then propose a generic model to unfold collaborative human activities into three modules: (i) individual behavior characterized by Poissonian initiation of an action, (ii) human interaction captured by a cascading response to others with a power-law waiting time, and (iii) population growth due to increasing number of interacting individuals. This unfolding allows us to obtain analytical formula that is fully supported by the universal patterns in empirical data. Our modeling approaches reveal "simplicity" beyond complex interacting human activities.

physics.soc-ph↗

arXiv2015

Spike Pattern Structure Influences Efficacy Variability under STDP and Synaptic Homeostasis

In neural systems, synaptic plasticity is usually driven by spike trains. Due to the inherent noises of neurons, synapses and networks, spike trains typically exhibit externally uncontrollable variability such as spatial heterogeneity and temporal stochasticity, resulting in variability of synapses, which we call efficacy variability. Spike patterns with the same population rate but inducing different efficacy variability may result in neuronal networks with sharply different structures and functions. However, how the variability of spike trains influences the efficacy variability remains unclear. Here, we systematically study this influence when spike patterns possess four aspects of statistical features, i.e. synchronous firing, auto-temporal structure, heterogeneity of rates and heterogeneity of cross-correlations, under spike-timing dependent plasticity (STDP) after dynamically bounding the mean strength of plastic synapses into or out of a neuron (synaptic homeostasis). We then show the functional importance of efficacy variability on the encoding and maintenance of connection patterns and on the early development of primary visual systems driven by retinal waves. We anticipate our work brings a fresh perspective to the understanding of the interaction between synaptic plasticity and dynamical spike patterns in functional processes of neural systems.

q-bio.NC↗

arXiv2011

Relative clock demonstrates the endogenous heterogeneity of human dynamics

The heavy-tailed inter-event time distributions are widely observed in many human-activated systems, which may result from both endogenous mechanisms like the highest-priority-first protocol and exogenous factors like the varying global activity versus time. To distinguish the effects on temporal statistics from different mechanisms is this of theoretical significance. In this Letter, we propose a new timing method by using a relative clock, where the time length between two consecutive events of an individual is counted as the number of other individuals' events appeared during this interval. We propose a model, in which agents act either in a constant rate or with a power-law inter-event time distribution, and the global activity either keeps unchanged or varies periodically versus time. Our analysis shows that the heavy tails caused by the heterogeneity of global activity can be eliminated by setting the relative clock, yet the heterogeneity due to real individual behaviors still exists. We perform extensive experiments on four large-scale systems, the search engine by AOL, a social bookmarking system--Delicious, a short-message communication network, and a microblogging system--Twitter. Strong heterogeneity and clear seasonality of global activity are observed, but the heavy tails cannot be eliminated by using the relative clock. Our results suggest the existence of endogenous heterogeneity of human dynamics.

physics.soc-ph↗

arXiv2011

Competition between Intra-community and Inter-community Synchronization

In this paper the effects of external links on the synchronization performance of community networks, especially on the competition between individual community and the whole network, are studied in detail. The study is organized from two aspects: the number or portion of external links and the connecting strategy of external links between different communities. It is found that increasing the number of external links will enhance the global synchronizability but degrade the ynchronization performance of individual community before some critical point. After that the individual community will synchronize better and better as part of the whole network because the community structure is not so prominent. Among various connection strategies, connecting nodes belonging to different communities randomly rather than connecting nodes with larger degrees is the most efficient way to enhance global synchronization of the network. However, a preferential connection scheme linking most of the hubs from the communities will allow rather efficient global synchronization while maintaining strong dynamical clustering of the communities. Interestingly, the observations are found to be relevant in a realistic network of cat cortex. The synchronization state is just at the critical point, which shows a reasonable combination of segregated function in individual communities and coordination among them. Our work sheds light on principles underlying the emergence of modular architectures in real network systems and provides guidance for the manipulation of synchronization in community networks.

physics.soc-ph↗

arXiv2009

Synchronization on Effective Networks

The study of network synchronization has attracted increasing attention recently. In this paper, we strictly define a class of networks, namely effective networks, which are synchronizable and orientable networks. We can prove that all the effective networks with the same size have the same spectra, and are of the best synchronizability according to the master stability analysis. However, it is found that the synchronization time for different effective networks can be quite different. Further analysis show that the key ingredient affecting the synchronization time is the maximal depth of an effective network: the larger depth results in a longer synchronization time. The secondary factor is the number of links. The more links connecting the nodes in the same layer (horizontal links) will lead to longer synchronization time, while the increasing number of links connecting nodes in neighboring layers (vertical links) will accelerate the synchronization. Our findings provide insights into the roles of horizontal and vertical links in synchronizing process, and suggest that the spectral analysis is helpful yet insufficient for the understanding of network synchronization.

cond-mat.stat-mech↗

arXiv2009

Mapping from Architecture to Dynamics: A Unified View of Dynamical Processes on Networks

Although it is unambiguously agreed that structure plays a fundamental role in shaping the dynamics of complex systems, this intricate relationship still remains unclear. We investigate a general computational transformation by which we can map the network topology directly to the dynamical patterns emergent on it -- independent of the nature of the dynamical process. We find that many seemingly diverse dynamical processes such as coupled oscillators and diffusion phenomena can all be understood and unified through this same procedure. Using the multiscale complexity measure derived form the structure-dynamics transformation, we find that the topological features like hierarchy, heterogeneity and modularity all result in higher complexity. This result suggests a universal principle: it is the desire for functional diversity that drives the evolution of network architecture.

cond-mat.dis-nn↗

arXiv2009

Optimal transport on supply-demand networks

Previously, transport networks are usually treated as homogeneous networks, that is, every node has the same function, simultaneously providing and requiring resources. However, some real networks, such as power grid and supply chain networks, show a far different scenario in which the nodes are classified into two categories: the supply nodes provide some kinds of services, while the demand nodes require them. In this paper, we propose a general transport model for those supply-demand networks, associated with a criterion to quantify their transport capacities. In a supply-demand network with heterogenous degree distribution, its transport capacity strongly depends on the locations of supply nodes. We therefore design a simulated annealing algorithm to find the optimal configuration of supply nodes, which remarkably enhances the transport capacity, and outperforms the degree target algorithm, the betweenness target algorithm, and the greedy method. This work provides a start point for systematically analyzing and optimizing transport dynamics on supply-demand networks.

physics.data-an↗

arXiv2009

Effective leadership in competition

Among natural biological flocks/swarms or even mass social activities, when the collective behaviors of the followers has been dominated by the moving direction or opinion of one leader group, it seems very difficult for later-coming leaders to reverse the orientation of the mass followers, especially when they are in quantitative minority. This Letter reports a counter-intuitive phenomenon, Following the Later-coming Minority, provided that the late-comers obey a favorable distribution pattern which enables them to spread their influence to as many followers as possible in a given time and to accumulate enough power to govern these followers. We introduce a discriminant index to quantify the whole group's orientation under competing leadership, which helps to design an economic way for the minority later-coming leaders to defeat the dominating majority leaders solely by optimizing their distribution pattern. Our investigation provides new insights into the effective leadership in biological systems, with meaningful implication to social and industrial applications.

physics.soc-ph↗

arXiv2008

Synchronization in complex networks

Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analytical approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.

physics.soc-ph↗

arXiv2007

Reciprocity of Networks with Degree Correlations and Arbitrary Degree Sequences

Although most of the real networks contain a mixture of directed and bidirectional (reciprocal) connections, the reciprocity $r$ has received little attention as a subject of theoretical understanding. We study the expected reciprocity of networks with an arbitrary degree sequence and a broad class of degree correlations by means of statistical ensemble approach. We demonstrate that degree correlations are crucial to understand the reciprocity in real networks and a hierarchy of correlation contributions to $r$ is revealed. Numerical experiments using novel network randomization methods show very good agreement to our analytical estimations.

cond-mat.stat-mech↗

arXiv2006

Universality in the synchronization of weighted random networks

Realistic networks display not only a complex topological structure, but also a heterogeneous distribution of weights in the connection strengths. Here we study synchronization in weighted complex networks and show that the synchronizability of random networks with large minimum degree is determined by two leading parameters: the mean degree and the heterogeneity of the distribution of node's intensity, where the intensity of a node, defined as the total strength of input connections, is a natural combination of topology and weights. Our results provide a possibility for the control of synchronization in complex networks by the manipulation of few parameters.

cond-mat.dis-nn↗

arXiv2005

Weighted networks are more synchronizable: how and why

Most real-world networks display not only a heterogeneous distribution of degrees, but also a heterogeneous distribution of weights in the strengths of the connections. Each of these heterogeneities alone has been shown to suppress synchronization in random networks of dynamical systems. Here we review our recent findings that complete synchronization is significantly enhanced and becomes independent of both distributions when the distribution of weights is suitably combined with the distribution of degrees. We also present new results addressing the optimality of our findings and extending our analysis to phase synchronization in networks of non-identical dynamical units.

cond-mat.dis-nn↗

arXiv2005

Network Synchronization, Diffusion, and the Paradox of Heterogeneity

Many complex networks display strong heterogeneity in the degree (connectivity) distribution. Heterogeneity in the degree distribution often reduces the average distance between nodes but, paradoxically, may suppress synchronization in networks of oscillators coupled symmetrically with uniform coupling strength. Here we offer a solution to this apparent paradox. Our analysis is partially based on the identification of a diffusive process underlying the communication between oscillators and reveals a striking relation between this process and the condition for the linear stability of the synchronized states. We show that, for a given degree distribution, the maximum synchronizability is achieved when the network of couplings is weighted and directed, and the overall cost involved in the couplings is minimum. This enhanced synchronizability is solely determined by the mean degree and does not depend on the degree distribution and system size. Numerical verification of the main results is provided for representative classes of small-world and scale-free networks.

cond-mat.dis-nn↗

arXiv2004

Enhancing complex-network synchronization

Heterogeneity in the degree (connectivity) distribution has been shown to suppress synchronization in networks of symmetrically coupled oscillators with uniform coupling strength (unweighted coupling). Here we uncover a condition for enhanced synchronization in directed networks with weighted coupling. We show that, in the optimum regime, synchronizability is solely determined by the average degree and does not depend on the system size and the details of the degree distribution. In scale-free networks, where the average degree may increase with heterogeneity, synchronizability is drastically enhanced and may become positively correlated with heterogeneity, while the overall cost involved in the network coupling is significantly reduced as compared to the case of unweighted coupling.

cond-mat.dis-nn↗

arXiv2003

Synchronization and oscillator death in oscillatory media with stirring

The effect of stirring in an inhomogeneous oscillatory medium is investigated. We show that the stirring rate can control the macroscopic behavior of the system producing collective oscillations (synchronization) or complete quenching of the oscillations (oscillator death). We interpret the homogenization rate due to mixing as a measure of global coupling and compare the phase diagrams of stirred oscillatory media and of populations of globally coupled oscillators.

nlin.CD↗

arXiv2000

Coherence resonance near blowout bifurcation in nonlinear dynamical systems

Previous studies have shown that noise can induce coherence resonance in some nonlinear dynamical systems close to a bifurcation of a periodic motion, such as in excitable systems. We demonstrate that coherence resonance can be observed in systems close to a {\sl blowout bifurcation}. It is shown that for dynamical systems with an invariant subspace in which there is a phase-coherent chaotic attractor, the interplay among the oscillation of local transverse stability, noise and nonlinearity can lead to coherence resonance phenomenon. The mechanism of coherence resonance in this type of system is different from that in previously studied systems.

nlin.CD↗

arXiv2000

Symmetry-breaking on-off intermittency under modulation: Robustness of supersensitivity, resonance and information gain

Nonlinear dynamical systems possessing an invariant subspace in the phase space and chaotic or stochastic motion within the subspace often display on-off intermittency close to the threshold of stability of the subspace. In a class of symmetric systems, the intermittency is symmetry-breaking [Ying-Cheng Lai, Phys. Rev. E {\bf 53}. R4267 (1996)]. We report interesting and practically important universal behavior of robustness of supersensitivity, resonance and information gain in this class of systems when subjected to a weak modulation. While intermittent loss of synchronization may be harmful to application of high-quality synchronization of coupled chaotic systems, the features reported here may lead to interesting application of on-off intermittency.

nlin.CD↗

arXiv2000

Amplification of weak signals and stochastic resonance via on-off intermittency with symmetry breaking

Nonlinear dynamical systems possessing reflection symmetry have an invariant subspace in the phase space. The dynamics within the invariant subspace can be random or chaotic. As a system parameter changes, the motion transverse to the invariant subspace can lose stability, leading to on-off intermittency. Under certain conditions, the bursting behavior is symmetry-breaking. We demonstrate the possibility of observing multiplicative noise(chaos)-induced amplification of weak signal and stochastic resonance via on-off intermittency with symmetry breaking in a general class of symmetrical systems. Differences of this mechanism of stochastic resonance to that in noisy bistable or threshold systems are discussed

nlin.CD↗