Long transients dynamics in biochemical networks

Summary  A Coupled Map Lattice, which simulates gene expression dynamics inside cells and cellular interactions on a regular lattice, shows a complex pattern of temporal behaviour. The model is represented as a network of genes interacting through their products in space and time in a lattice of genetically identical cells. Despite the fact that the system is described through a step function that imposes a simple repertoire of constant or oscillatory steady states, the dynamics over the lattice are extremely complex. One of the main feature of the asymptotic dynamics is the appearance of long transients in certain regions of parameter space, before the attainment of the final stable attractor. These dynamics, that can grow linearly or exponentially with lattice size, can become the only dynamics computationally observable. The study of the global dynamics-i.e. the average value of the variable over the lattice-shows a qualitative different behaviour depending on the region of the parameter space observed. In the case of the linear transient-growth region the system shows an average that falls quickly on a periodic attractor. In the exponential region values of the average quantities show a behaviour that has stochastic properties. At the boundary of these two regimes the system has an average that shows a complex behaviour before attainment of the final attractor. The possible implications of these results for the study of the dynamical aspects of gene regulation, biochemical pathways and in signal transduction in experimental systems are discussed. This work has been partially supported by CNR grant No. 95.01751.CT14 “Studio analitico della dinamica della regolazione genica e della morfogenesi#x201C;, and by funds from the National Ministry of Public Health. FB and RL would like to thank I.S.I., Torino, for the kind hospitality during the workshop of the EEC Network “Complexity and Chaos#x201D;, contract No. ERBCHRX-CT940546, in 1995 and 1996, during which part of this research has been done.     

Synchronizability of chaotic logistic maps in delayed complex networks

We study a network of coupled logistic maps whose interactions occur with a certain distribution of delay times. The local dynamics is chaotic in the absence of coupling and thus the network is a paradigm of a complex system. There are two regimes of synchronization, depending on the distribution of delays: when the delays are sufficiently heterogeneous the network synchronizes on a steady-state (that is unstable for the uncoupled maps); when the delays are homogeneous, it synchronizes in a time-dependent state (that is either periodic or chaotic). Using two global indicators we quantify the synchronizability on the two regimes, focusing on the roles of the network connectivity and the topology. The connectivity is measured in terms of the average number of links per node, and we consider various topologies (scale-free, small-world, star, and nearest-neighbor with and without a central hub). With weak connectivity and weak coupling strength, the network displays an irregular oscillatory dynamics that is largely independent of the topology and of the delay distribution. With heterogeneous delays, we find a threshold connectivity level below which the network does not synchronize, regardless of the network size. This minimum average number of neighbors seems to be independent of the delay distribution. We also analyze the effect of self-feedback loops and find that they have an impact on the synchronizability of small networks with large coupling strengths. The influence of feedback, enhancing or degrading synchronization, depends on the topology and on the distribution of delays.     

The chaotic phase synchronization in adaptively coupled-delayed complex networks

The notion of chaotic phase synchronization (CPS) in the large-scale delayed scale-free network is discussed in this Letter. The amplitude death (AD) phenomenon is observed and analyzed in terms of energy. AD occurs when the time-delay becomes long enough. The adaptive coupling scheme has better performance in CPS and AD compared with the constant scheme, and simulation results confirm conclusions.     

Multiple attractors, long chaotic transients, and failure in small-world networks of excitable neurons

We study the dynamical states of a small-world network of recurrently coupled excitable neurons, through both numerical and analytical methods. The dynamics of this system depend mostly on both the number of long-range connections or "shortcuts", and the delay associated with neuronal interactions. We find that persistent activity emerges at low density of shortcuts, and that the system undergoes a transition to failure as their density reaches a critical value. The state of persistent activity below this transition consists of multiple stable periodic attractors, whose number increases at least as fast as the number of neurons in the network. At large shortcut density and for long enough delays the network dynamics exhibit exceedingly long chaotic transients, whose failure times follow a stretched exponential distribution. We show that this functional form arises for the ensemble-averaged activity if the failure time for each individual network realization is exponentially distributed.     

Experimental observation of superpersistent chaotic transients

We present the first experimental observation of superpersistent chaotic transients. In particular, we investigate the effect of noise on phase synchronization in coupled chaotic electronic circuits and obtain the scaling relation that is characteristic of those extremely long chaotic transients.     

Explosive synchronization of complex networks with different chaotic oscillators

Recent studies have shown that explosive synchronization transitions can be observed in networks of phase oscillators [Gómez-Garden es J,Gómez S,Arenas A and Moreno Y 2011 Phys.Rev.Lett.106 128701] and chaotic oscillators [Leyva I,Sevilla-Escoboza R,BuldúJ M,Sendin a-Nadal I,Gómez-Garden es J,Arenas A,Moreno Y,Gómez S,Jaimes-Reátegui R and Boccaletti S 2012 Phys.Rev.Lett.108 168702].Here,we study the effect of different chaotic dynamics on the synchronization transitions in small world networks and scale free networks.The continuous transition is discovered for Rssler systems in both of the above complex networks.However,explosive transitions take place for the coupled Lorenz systems,and the main reason is the abrupt change of dynamics before achieving complete synchronization.Our results show that the explosive synchronization transitions are accompanied by the change of system dynamics.     

Chaos and chaotic transients in an aeroelastic system

Chaotic motions of a two dimensional airfoil with coupled structural nonlinearities, both in pitch as well as plunge degrees of freedom, are investigated via a numerical integration method. The original system of coupled integro-differential equations governing the motion of the present aeroelastic model is transformed into a simple system of six ordinary differential equations (ODEs), rather than the previously frequently used eight ODEs. Complex dynamical behaviors are revealed and identified through the means of bifurcation diagrams, the phase portraits, the amplitude spectra and the Poincare maps. Besides, a more quantitative method, namely that of observing the evolution of the largest Lyapunov exponent (LLE) is also applied to diagnose the motions. Two peculiar phenomena, namely, long (perhaps super-persistent) chaotic transients, and fluctuating Lyapunov exponents, are observed; in the two such cases the LLE method fails to work. In addition, the effects of various system parameters, namely, the position of the elastic axis, the frequency ratio, the airfoil/air mass ratio, the viscous damping ratios, and the location of the center of mass, on the response of the aeroelastic system, are investigated.     

Repellers,semi-attractors,and long-lived chaotic transients

We study the chaotic transients observed in many deterministic systems. In general, they are related to strange repellers (or “semi-attractors”, if they are repelling in some and attracting in other directions). We propose formulas relating the average life time of the transient to dimensions of the repeller, and to Lyapunov exponents of the flow on it. The formulas are tested numerically in a number of cases.     

基于低阶矩阵最大特征值的复杂网络牵制混沌同步

虽已对复杂网络牵制同步需要牵制结点数量及牵制结点数量与耦合强度的关系进行了研究,然而快速计算牵制结点数量仍是大规模复杂网络面临的一个重要问题.研究发现了复杂网络耦合矩阵主子阵最大值递减规律,由此提出了快速计算复杂网络牵制结点数量的方法,揭示了不同的牵制策略与牵制结点数量之间的关系.数值仿真显示了在无标度网络和小世界网络上三种不同的牵制策略下,牵制结点数与主子阵最大特征值的变化规律;最后给出了一个在无标度网络上采用随机选择结点策略的牵制同步实例.     

Coherent atomic beam splitter using transients of a chaotic system

A coherent atomic beam splitter can be realized using the transient dynamics of a chaotic system. We have experimentally observed such an effect using ultracold rubidium atoms. Our experimental results are in good agreement with numerical simulations of the Schrodinger equation for the system.     

Superpersistent chaotic transients in physical space: advective dynamics of inertial particles in open chaotic flows under noise

Superpersistent chaotic transients are characterized by an exponential-like scaling law for their lifetimes where the exponent in the exponential dependence diverges as a parameter approaches a critical value. So far this type of transient chaos has been illustrated exclusively in the phase space of dynamical systems. Here we report the phenomenon of noise-induced superpersistent transients in physical space and explain the associated scaling law based on the solutions to a class of stochastic differential equations. The context of our study is advective dynamics of inertial particles in open chaotic flows. Our finding makes direct experimental observation of superpersistent chaotic transients feasible. It also has implications to problems of current concern such as the transport and trapping of chemically or biologically active particles in large-scale flows.     

Chemical transients in closed chaotic flows: the role of effective dimensions

We investigate chemical activity in hydrodynamical flows in closed containers. In contrast to open flows, in closed flows the chemical field does not show a well-defined fractal property; nevertheless, there is a transient filamentary structure present. We show that the effect of the filamentary patterns on the chemical activity can be modeled by the use of time-dependent effective dimensions. We derive a new chemical rate equation, which turns out to be coupled to the dynamics of the effective dimension, and predicts an exponential convergence. Previous results concerning activity in open flows are special cases of this new rate equation.     

Long time tail correlations in discrete chaotic dynamics

A scaling relation is derived connecting the exponent of the algebraically decaying correlation and response functions with the degree of intermittency and the order of the maximum. It is universal, i.e. within a large class independent of the correlated variables. This implies universal 1/f-like spectra. The corrections to scaling are investigated, too.     

混沌时滞神经网络系统的反同步

利用状态观测器方法研究了一类带时滞的混沌神经网络系统的反同步问题.与应用于其他混沌系统的反同步方法相比,提出的方法更为简便,并且利用极点配置技术,只要通过调整特征值来实现反同步速率的快慢.最后,给出了数值例子和计算机仿真结果来验证该方案的有效性. 关键词： 混沌神经网络 状态观测器 极点配置技术 反同步     

Synchronization and coherence resonance in chaotic neural networks

Synchronization and coherence of chaotic Morris--Lecar (ML) neural networks have been investigated by numerical methods. The synchronization of the neurons can be enhanced by increasing the number of the shortcuts, even though all neurons are chaotic when uncoupled. Moreover, the coherence of the neurons exhibits a non-monotonic dependence on the density of shortcuts. There is an optimal number of shortcuts at which the neurons' motion is most ordered, i.e. the order parameter (the characteristic correlation time) that is introduced to measure the coherence of the neurons has a maximum. These phenomena imply that stochastic shortcuts can tame spatiotemporal chaos. The effects of the coupling strength have also been studied. The value of the optimal number of shortcuts goes down as the coupling strength increases.     

Accessibility in complex networks

This Letter describes a method for the quantification of the diversity of non-linear dynamics in complex networks as a consequence of self-avoiding random walks. The methodology is analyzed in the context of theoretical models and illustrated with respect to the characterization of the accessibility in urban streets.     

Synchronization in complex networks

Synchronization processes in populations of locally interacting elements are the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understanding synchronization phenomena in natural systems now take 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 take an overview of the new emergent features coming out from the interplay between the structure and the function of the underlying patterns 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.     

Synchronization of coupled chaotic dynamics on networks

We review some recent work on the synchronization of coupled dynamical systems on a variety of networks. When nodes show synchronized behaviour, two interesting phenomena can be observed. First, there are some nodes of the floating type that show intermittent behaviour between getting attached to some clusters and evolving independently. Secondly, two different ways of cluster formation can be identified, namely self-organized clusters which have mostly intra-cluster couplings and driven clusters which have mostly inter-cluster couplings.