arXiv subjects

R. E. Amritkar

Publications and source records attributed to R. E. Amritkar.

At least 37 records · Page 2Linked to original sources

arXiv2008

Coupled Dynamics on Networks

We study the synchronization of coupled dynamical systems on a variety of networks. The dynamics is governed by a local nonlinear map or flow for each node of the network and couplings connecting different nodes via the links of the network. For small coupling strengths nodes show turbulent behavior but form synchronized clusters as coupling increases. When nodes show synchronized behaviour, we observe two interesting phenomena. First, there are some nodes of the floating type that show intermittent behaviour between getting attached to some clusters and evolving independently. Secondly, we identify two different ways of cluster formation, namely self-organized clusters which have mostly intra-cluster couplings and driven clusters which have mostly inter-cluster couplings.

nlin.CD↗

arXiv2006

Spatial synchronization and extinction of species under external forcing

We study the interplay between synchronization and extinction of a species. Using a general model we show that under a common external forcing, the species with a quadratic saturation term in the population dynamics first undergoes spatial synchronization and then extinction, thereby avoiding the rescue effect. This is because the saturation term reduces the synchronization time scale but not the extinction time scale. The effect can be observed even when the external forcing acts only on some locations provided there is a synchronizing term in the dynamics. Absence of the quadratic saturation term can help the species to avoid extinction.

nlin.CD↗

arXiv2006

Analysis of delay correlation matrices

We construct and analyze symmetrized delay correlation matrices for empirical data sets for atmopheric and financial data to derive information about correlation between different entities of the time series over time. The information about correlations is obtained by comparing the results for the eigenvalue distribution with the analytical results for the independent, identically distributed random data sets. For the atmospheric case we find long term correlations between different entities of the multivariable time series. For the financial time series we find little correlations between different entities over a time delay beyond about two days. Most of the eigenvalues for the symmetrized delay correlation matrices for the financial data are symmetrically distributed about zero. The delay correlation results for the financial data are similar to the analytical results for the random data sets. However there are considerable deviations for the atmospheric data from the random case.

cond-mat.stat-mech↗

arXiv2005

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.

nlin.CD↗

arXiv2003

Synchronized clusters in coupled map networks: Self-organized and driven phase synchronization

We study the synchronization of coupled maps on a variety of networks including regular one and two dimensional networks, scale free networks, small world networks, tree networks, and random networks. For small coupling strengths nodes show turbulent behavior but form phase synchronized clusters as coupling increases. We identify two different ways of cluster formation, self-organized clusters which have mostly intra-cluster couplings and driven clusters which have mostly inter-cluster couplings. The synchronized clusters may be of dominant self-organized type, dominant driven type or mixed type depending on the type of network and the parameters of the dynamics. There are some nodes of the floating type that show intermittent behaviour between getting attached to some clusters and evolving independently. The residence times of a floating node in a synchronized cluster show an exponential distribution. We define different states of the coupled dynamics by considering the number and type of synchronized clusters. For the local dynamics governed by the logistic map we study the phase diagram in the plane of the coupling constant ($ε$) and the logistic map parameter ($μ$). For large coupling strengths and nonlinear coupling we find that the scale free networks and the Caley tree networks lead to better cluster formation than the other types of networks with the same average connectivity. For most of our study we use the number of connections of the order of the number of nodes which allows us to distinguish between the two mechanisms of cluster formation. As the number of connections increases the number of nodes forming clusters and the size of the clusters in general increase.

nlin.CD↗

arXiv2003

Synchronized clusters in coupled map networks: Stability analysis

We study self-organized (s-) and driven (d-) synchronization in coupled map networks for some simple networks, namely two and three node networks and their natural generalization to globally coupled and complete bipartite networks. We use both linear stability analysis and Lyapunov function approach for this study and determine stability conditions for synchronization. We see that most of the features of coupled dynamics of small networks with two or three nodes, are carried over to the larger networks of the same type. The phase diagrams for the networks studied here have features very similar to the different kinds of networks studied in Ref. \cite{sarika-REA2}. The analysis of the dynamics of the difference variable corresponding to any two nodes shows that when the two nodes are in driven synchronization, all the coupling terms cancel out whereas when they are in self-organized synchronization, the direct coupling term between the two nodes adds an extra decay term while the other couplings cancel out.

nlin.CD↗

arXiv2003

Self-organized and driven phase synchronization in coupled maps

We study the phase synchronization and cluster formation in coupled maps on different networks. We identify two different mechanisms of cluster formation; (a) {\it Self-organized} phase synchronization which leads to clusters with dominant intra-cluster couplings and (b) {\it driven} phase synchronization which leads to clusters with dominant inter-cluster couplings. In the novel driven synchronization the nodes of one cluster are driven by those of the others. We also discuss the dynamical origin of these two mechanisms for small networks with two and three nodes.

nlin.CD↗

arXiv2002

Self-organized and driven phase synchronization in coupled map scale free networks

As a model of evolving networks, we study coupled logistic maps on scale free networks. For small coupling strengths nodes show turbulent behavior but form phase synchronized clusters as coupling increases. We identify two different ways of cluster formation. For small coupling strengths we get {\it self-organized clusters} which have mostly intra-cluster couplings and for large coupling strengths there is a crossover and reorganization to {\it driven clusters} which have mostly inter-cluster couplings. In the novel driven synchronization the nodes of one cluster are driven by those of the others.

nlin.AO↗

arXiv2001

Estimation of Initial Conditions and Secure Communication

We estimate the initial conditions of a multivariable dynamical system from a scalar signal, using a modified Newton-Raphson method incorporating the time evolution. We can estimate initial conditions of periodic and chaotic systems and the required length of scalar signal is very small. We also find that the information flow from one variable to the other has logarithmic dependence on time. An important application of the method is in secure communications. The communication procedure has several advantages as compared to others using dynamical systems.

nlin.CD↗

arXiv2000

Random spread on the family of small-world networks

We present the analytical and numerical results of a random walk on the family of small-world graphs. The average access time shows a crossover from the regular to random behavior with increasing distance from the starting point of the random walk. We introduce an {\em independent step approximation}, which enables us to obtain analytic results for the average access time. We observe a scaling relation for the average access time in the degree of the nodes. The behavior of average access time as a function of $p$, shows striking similarity with that of the {\em characteristic length} of the graph. This observation may have important applications in routing and switching in networks with large number of nodes.

cond-mat.stat-mech↗

arXiv2000

Estimation of initial conditions from a scalar time series

We introduce a method to estimate the initial conditions of a mutivariable dynamical system from a scalar signal. The method is based on a modified multidimensional Newton-Raphson method which includes the time evolution of the system. The method can estimate initial conditions of periodic and chaotic systems and the required length of scalar signal is very small. Also, the method works even when the conditional Lyapunov exponent is positive. An important application of our method is that synchronization of two chaotic signals using a scalar signal becomes trivial and instantaneous.

nlin.CD↗

arXiv2000

Dynamic Algorithm for Parameter Estimation and Its Applications

We consider a dynamic method, based on synchronization and adaptive control, to estimate unknown parameters of a nonlinear dynamical system from a given scalar chaotic time series. We present an important extension of the method when time series of a scalar function of the variables of the underlying dynamical system is given. We find that it is possible to obtain synchronization as well as parameter estimation using such a time series. We then consider a general quadratic flow in three dimensions and discuss applicability of our method of parameter estimation in this case. In practical situations one expects only a finite time series of a system variable to be known. We show that the finite time series can be repeatedly used to estimate unknown parameters with an accuracy which improves and then saturates to a constant value with repeated use of the time series. Finally we propose that the method can be used to confirm the correctness of a trial function modeling an external unknown perturbation to a known system. We show that our method produces exact synchronization with the given time series only when the trial function has a form identical to that of the perturbation.

nlin.CD↗

arXiv1999

Characterization and control of small-world networks

Recently Watts and Strogatz have given an interesting model of small-world networks. Here we concretise the concept of a ``far away'' connection in a network by defining a {\it far edge}. Our definition is algorithmic and independent of underlying topology of the network. We show that it is possible to control spread of an epidemic by using the knowledge of far edges. We also suggest a model for better advertisement using the far edges. Our findings indicate that the number of far edges can be a good intrinsic parameter to characterize small-world phenomena.

chao-dyn↗

arXiv1998

Use of synchronization and adaptive control in parameter estimation from a time series

A technique is introduced for estimating unknown parameters when time series of only one variable from a multivariate nonlinear dynamical system is given. The technique employs a combination of two different control methods, a linear feedback for synchronizing system variables and an adaptive control. The technique is shown to work even when the unknown parameter appears in the evolution equations of the variables other than the one for which the time series is given. The technique not only esablishes that explicit detailed information about all system variables and parameters is contained in a scalar time series, but also gives a way to exract it out under suitable conditions. Illustrations are presented and effect of noise is studied.

chao-dyn↗

arXiv1998

Stochastic Coherence in Coupled Map Lattices

We report in details the observations of structures in coupled map lattice during its chaotic evolution, both in one and two dimension, driven by identical noise on each site (by a structure we mean a group of neighboring lattice-sites for whom values of dynamical variable follow certain prespecified pattern). It is observed that the number of these structures decays with their size following a power-law, for a given noise-strength. The number of structures decays with their lifetime following a stretched exponential. We have seen an interesting phenomenon, which we call stochastic coherence, in which the average length as well as the average lifetime of these structures exhibit bell-shaped maxima for some intermediate range of noise-strength values. Similar features have also been observed for `spatio-temporal structures'.

chao-dyn↗

arXiv1998

Effect of noise on coupled chaotic systems

Effect of noise in inducing order on various chaotically evolving systems is reviewed, with special emphasis on systems consisting of coupled chaotic elements. In many situations it is observed that the uncoupled elements when driven by identical noise, show synchronization phenomena where chaotic trajectories exponentially converge towards a single noisy trajectory, independent of the initial conditions. In a random neural network, with infinite range coupling, chaos is suppressed due to noise and the system evolves towards a fixed point. Spatiotemporal stochastic resonance phenomenon has been observed in a square array of coupled threshold devices where a temporal characteristic of the system resonates at a given noise strength. In a chaotically evolving coupled map lattice with logistic map as local dynamics and driven by identical noise at each site, we report that the number of structures (a structure is a group of neighbouring lattice sites for whom values of the variable follow certain predefined pattern) follow a power-law decay with the length of the structure. An interesting phenomenon, which we call stochastic coherence, is also reported in which the abundance and lifetimes of these structures show characteristic peaks at some intermediate noise strength.

chao-dyn↗

arXiv1998

Percolation of finite-sized objects on a lattice

We study the percolation of FINITE-SIZED objects on two- and three-dimensional lattices. Our motivation stems, on one hand from some recent interesting experimental results on transport properties of impurity-doped oxide perovskites and on the other hand from the theoretical appeal that this problem presents. Our system exhibits a well-defined percolation threshold. We estimate the size of magnetic polarons, believed to be the carriers of the abovementioned transport. We have also obtained two critical exponents for our model, which characterize its universality class.

cond-mat.stat-mech↗

arXiv1998

Observation of stochastic coherence in coupled map lattices

Chaotic evolution of structures in Coupled map lattice driven by identical noise on each site is studied (a structure is a group of neighbouring lattice-sites for whom values of dynamical variable follow certain predefined pattern). Number of structures is seen to follow a power-law decay with length of the structure for a given noise-strength. An interesting phenomenon, which we call stochastic coherence, is reported in which a rise of bell-shaped type in abundance and lifetimes of these structures is observed for a range of noise-strength values.

chao-dyn↗