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Shlomo Havlin

Publications and source records attributed to Shlomo Havlin.

At least 37 records · Page 2Linked to original sources
PubMed2005

Long-term memory: a natural mechanism for the clustering of extreme events and anomalous residual times in climate records.

We study the statistics of the return intervals between extreme events above a certain threshold in long-term persistent records. We find that the long-term memory leads (i) to a stretched exponential distribution of the return intervals, (ii) to a pronounced clustering of extreme events, and (iii) to an anomalous behavior of the mean residual time to the next event that depends on the history and increases with the elapsed time in a counterintuitive way. We present an analytical scaling approach and demonstrate that all these features can be seen in long climate records. The phenomena should also occur in heartbeat records, Internet traffic, and stock market volatility and have to be taken into account for an efficient risk evaluation.

Algorithms↗
PubMed2005

Self-similarity of complex networks.

Complex networks have been studied extensively owing to their relevance to many real systems such as the world-wide web, the Internet, energy landscapes and biological and social networks. A large number of real networks are referred to as 'scale-free' because they show a power-law distribution of the number of links per node. However, it is widely believed that complex networks are not invariant or self-similar under a length-scale transformation. This conclusion originates from the 'small-world' property of these networks, which implies that the number of nodes increases exponentially with the 'diameter' of the network, rather than the power-law relation expected for a self-similar structure. Here we analyse a variety of real complex networks and find that, on the contrary, they consist of self-repeating patterns on all length scales. This result is achieved by the application of a renormalization procedure that coarse-grains the system into boxes containing nodes within a given 'size'. We identify a power-law relation between the number of boxes needed to cover the network and the size of the box, defining a finite self-similar exponent. These fundamental properties help to explain the scale-free nature of complex networks and suggest a common self-organization dynamics.

Journal Article↗
PubMed2005

Phase-synchronization decay of fixational eye movements.

In nonstationary noisy systems the traditional cross-correlation method may not appropriately detect all cases of interdependencies between coupled systems. The phase-synchronization method was previously found useful in detecting synchronization in several systems. We here applied the phase-synchronization decay to study the synchronization between six combinations of binocular fixational eye movement components. We found that only two components were synchronized: the right and left horizontal with each other and the right and left vertical. Furthermore, the vertical-vertical components were much more synchronized than the horizontal.

Eye Movements↗
PubMed2004

Effect of disorder strength on optimal paths in complex networks.

We study the transition between the strong and weak disorder regimes in the scaling properties of the average optimal path l(opt) in a disordered Erdos-Rényi (ER) random network and scale-free (SF) network. Each link i is associated with a weight tau(i) identical withexp (a r(i) ) , where r(i) is a random number taken from a uniform distribution between 0 and 1 and the parameter a controls the strength of the disorder. We find that for any finite a , there is a crossover network size N* (a) at which the transition occurs. For N< /=4 , and l(opt) approximately N (lambda-3) (/ (lambda-1) ) for SF networks with 3 >N* (a) the scaling behavior is in the weak disorder regime, with l(opt) approximately ln N for ER networks and SF networks with lambda>3 . In order to study the transition we propose a measure which indicates how close or far the disordered network is from the limit of strong disorder. We propose a scaling ansatz for this measure and demonstrate its validity. We proceed to derive the scaling relation between N* (a) and a . We find that N* (a) approximately a(3) for ER networks and for SF networks with lambda>/=4 , and N* (a) approximately a (lambda-1) (/ (lambda-3) ) for SF networks with 3<lambda<4 .

Journal Article↗
PubMed2004

Universality of the optimal path in the strong disorder limit.

We study numerically the optimal paths in two and three dimensions on various disordered lattices in the limit of strong disorder. We find that the length l of the optimal path scales with geometric distance r , as l approximately r (d(opt) ) with d(opt) =1.22+/-0.01 for d=2 and 1.44+/-0.02 for d=3 , independent of whether the optimization is on a path of weighted bonds or sites, and independent of the lattice or its coordination number. Our finding suggests that the exponent d(opt) is universal, depending only on the dimension of the system.

Journal Article↗
PubMed2004

Percolation transition in a two-dimensional system of Ni granular ferromagnets.

We model magnetotransport features of the quenched condensed granular Ni thin films by a random two-dimensional resistor network in order to test the condition where a single bond dominates the system. The hopping conductivity is assumed to depend on the distance between neighboring ferromagnetic grains and the mutual orientation of the magnetic moments of these grains. We find that the quantity characterizing the transition from weak disorder (not sensitive to a change of a single bond resistivity) to strong disorder (very sensitive to such changes) scales as kappa/L(1/1.3), where L is the size of the system and kappa is a measure of disorder.

Journal Article↗
PubMed2003

Efficient immunization strategies for computer networks and populations.

We present an effective immunization strategy for computer networks and populations with broad and, in particular, scale-free degree distributions. The proposed strategy, acquaintance immunization, calls for the immunization of random acquaintances of random nodes (individuals). The strategy requires no knowledge of the node degrees or any other global knowledge, as do targeted immunization strategies. We study analytically the critical threshold for complete immunization. We also study the strategy with respect to the susceptible-infected-removed epidemiological model. We show that the immunization threshold is dramatically reduced with the suggested strategy, for all studied cases.

Computer Communication Networks↗
PubMed2003

Optimal paths in disordered complex networks.

We study the optimal distance in networks, l(opt), defined as the length of the path minimizing the total weight, in the presence of disorder. Disorder is introduced by assigning random weights to the links or nodes. For strong disorder, where the maximal weight along the path dominates the sum, we find that l(opt) approximately N(1/3) in both Erdos-Rényi (ER) and Watts-Strogatz (WS) networks. For scale-free (SF) networks, with degree distribution P(k) approximately k(-lambda), we find that l(opt) scales as N((lambda-3)/(lambda-1)) for 3 or =4. Thus, for these networks, the small-world nature is destroyed. For 2<lambda<3, our numerical results suggest that l(opt) scales as ln(lambda-1N. We also find numerically that for weak disorder l(opt) approximately ln(N for both the ER and WS models as well as for SF networks.

Communication↗
PubMed2003

Scaling law in sizes of protein sequence families: from super-families to orphan genes.

It has been observed that the size of protein sequence families is unevenly distributed, with few super families with a large number of members and many "orphan" proteins that do not belong to any family. Here it is shown that the distribution of sizes of protein families in different databases and classifications (Protomap, Prodom, Cog) follows a power-law behavior with similar scaling exponents, which is characteristic of self-organizing systems. Since large databases are used in this study, a more detailed analysis of the data than in previous studies was possible. Hence, it is shown that the size distribution is governed by two exponents, different for the super families and the orphan proteins. A simple model of protein evolution is proposed, in which proteins are dynamically generated and clustered into families. The model yields a scaling behavior very similar to the distribution observed in the actual sequence databases, including the two distinct regimes for the large and small families, and thus suggests that the existence of "super families" of proteins and "orphan" proteins are two manifestations of the same evolutionary process.

Algorithms↗
PubMed2003

Postbreakthrough behavior in flow through porous media.

We numerically simulate the traveling time of a tracer in convective flow between two points (injection and extraction) separated by a distance r in a model of porous media, d=2 percolation. We calculate and analyze the traveling time probability density function for two values of the fraction of connecting bonds p: the homogeneous case p=1 and the inhomogeneous critical threshold case p=p(c). We analyze both constant current and constant pressure conditions at p=p(c). The homogeneous p=1 case serves as a comparison base for the more complicated p=p(c) situation. We find several regions in the probability density of the traveling times for the homogeneous case (p=1) and also for the critical case (p=p(c)) for both constant pressure and constant current conditions. For constant pressure, the first region I(P) corresponds to the short times before the flow breakthrough occurs, when the probability distribution is strictly zero. The second region II(P) corresponds to numerous fast flow lines reaching the extraction point, with the probability distribution reaching its maximum. The third region III(P) corresponds to intermediate times and is characterized by a power-law decay. The fourth region IV(P) corresponds to very long traveling times, and is characterized by a different power-law decaying tail. The power-law characterizing region IV(P) is related to the multifractal properties of flow in percolation, and an expression for its dependence on the system size L is presented. The constant current behavior is different from the constant pressure behavior, and can be related analytically to the constant pressure case. We present theoretical arguments for the values of the exponents characterizing each region and crossover times. Our results are summarized in two scaling assumptions for the traveling time probability density; one for constant pressure and one for constant current. We also present the production curve associated with the probability of traveling times, which is of interest to oil recovery.

Journal Article↗
PubMed2003

Directed random walks on directed percolation clusters.

The characteristics of directed random walks on directed percolation clusters are numerically studied. For two-dimensional clusters grown at the critical probability p(c), it is shown that the distance d of the directed random walkers from their most probable end point is determined by a probability distribution p(d) approximately d(-(1+w/nu)), where the values of w and nu are close to the values of the known exponents: w approximately 0.50 and nu approximately 0.63. This probability distribution is independent of the cluster's length t up to d values comparable to the cluster's width approximately t(nu). The results are shown to be consistent with a tree description of the directed percolation clusters.

Journal Article↗
PubMed2003

Nonlinear volatility of river flux fluctuations.

We study the spectral properties of the magnitudes of daily river flux increments, the volatility. The volatility series exhibits (i) strong seasonal periodicity and (ii) power-law correlations for time scales less than 1 yr. We test the nonlinear properties of the river flux increment series by randomizing its Fourier phases and find that the surrogate volatility series (i) has almost no seasonal periodicity and (ii) is weakly correlated for time scales less than 1 yr. We quantify the degree of nonlinearity by measuring (i) the amplitude of the power spectrum at the seasonal peak and (ii) the correlation power-law exponent of the volatility series.

Journal Article↗
PubMed2003

Detecting scaling in the period dynamics of multimodal signals: application to Parkinsonian tremor.

Patients with Parkinson's disease exhibit tremor, involuntary movement of the limbs. The frequency spectrum of tremor typically has broad peaks at "harmonic" frequencies, much like that seen in other physical processes. In general, this type of harmonic structure in the frequency domain may be due to two possible mechanisms: a nonlinear oscillation or a superposition of (multiple) independent modes of oscillation. A broad peak spectrum generally indicates that a signal is semiperiodic with a fluctuating period. These fluctuations may posses intrinsic order that can be quantified using scaling analysis. We propose a method to extract the correlation (scaling) properties in the period dynamics of multimodal oscillations, in order to distinguish between a nonlinear oscillation and a superposition of individual modes of oscillation. The method is based on our finding that the information content of the temporal correlations in a fluctuating period of a single oscillator is contained in a finite frequency band in the power spectrum, allowing for decomposition of modes by bandpass filtering. Our simulations for a nonlinear oscillation show that harmonic modes possess the same scaling properties. In contrast, when the method is applied to tremor records from patients with Parkinson's disease, the first two modes of oscillations yield different scaling patterns, suggesting that these modes may not be simple harmonics, as might be initially assumed.

Humans↗
PubMed2003

Scale-free networks are ultrasmall.

We study the diameter, or the mean distance between sites, in a scale-free network, having N sites and degree distribution p(k) proportional, variant k(-lambda), i.e., the probability of having k links outgoing from a site. In contrast to the diameter of regular random networks or small-world networks, which is known to be d approximately ln(N, we show, using analytical arguments, that scale-free networks with 2 3, d approximately ln(N. We also show that, for any lambda>2, one can construct a deterministic scale-free network with d approximately ln(ln(N, which is the lowest possible diameter.

Cell Physiological Phenomena↗
PubMed2002

Correlation differences in heartbeat fluctuations during rest and exercise.

We study the heartbeat activity of healthy individuals at rest and during exercise. We focus on correlation properties of the intervals formed by successive peaks in the pulse wave and find significant scaling differences between rest and exercise. For exercise the interval series is anticorrelated at short-time scales and correlated at intermediate-time scales, while for rest we observe the opposite crossover pattern--from strong correlations in the short-time regime to weaker correlations at larger scales. We also suggest a physiologically motivated stochastic scenario to provide an intuitive explanation of the scaling differences between rest and exercise.

Biophysical Phenomena↗
PubMed2002

Scale-free networks on lattices.

We suggest a method for embedding scale-free networks, with degree distribution Pk approximately k(-lambda), in regular Euclidean lattices accounting for geographical properties. The embedding is driven by a natural constraint of minimization of the total length of the links in the system. We find that all networks with lambda>2 can be successfully embedded up to a (Euclidean) distance xi which can be made as large as desired upon the changing of an external parameter. Clusters of successive chemical shells are found to be compact (the fractal dimension is df=d), while the dimension of the shortest path between any two sites is smaller than 1: dmin=(lambda-2)/(lambda-1-1/d), contrary to all other known examples of fractals and disordered lattices.

Computer Communication Networks↗
PubMed2002

Optimization of congested traffic by controlling stop-and-go waves.

We propose a new optimization strategy based on inducing stop-and-go waves on the main road and controlling their wavelength. Using numerical simulations of a recent stochastic car-following model we show that this strategy yields optimization of traffic flow when implemented in systems with a localized periodic inhomogeneity, such as signalized intersections and entry ramps. The optimization process is explained by our finding of a generalized fundamental diagram (GFD) for traffic, namely a flux-density-wavelength relation. Projecting the GFD on the density-flux plane yields a two-dimensional region of stable states, qualitatively similar to that found empirically [Kerner, Phys. Rev. Lett. 81, 3797 (1998)] in synchronized traffic.

Journal Article↗