arXiv subjects

Shlomo Havlin

Publications and source records attributed to Shlomo Havlin.

At least 127 records · Page 7Linked to original sources

arXiv2016

Percolation framework to describe El Niño conditions

Complex networks have been used intensively to investigate the flow and dynamics of many natural systems including the climate system. Here, we develop a percolation based measure, the order parameter, to study and quantify climate networks. We find that abrupt transitions of the order parameter usually occur $\sim$1 year before El Niño ~ events, suggesting that they can be used as early warning precursors of El Niño. Using this method we analyze several reanalysis datasets and show the potential for good forecasting of El Niño. The percolation based order parameter exhibits discontinuous features, indicating possible relation to the first order phase transition mechanism.

physics.ao-ph↗

arXiv2016

Stochastic model of financial markets reproducing scaling and memory in volatility return intervals

We investigate the volatility return intervals in the NYSE and FOREX markets. We explain previous empirical findings using a model based on the interacting agent hypothesis instead of the widely-used efficient market hypothesis. We derive macroscopic equations based on the microscopic herding interactions of agents and find that they are able to reproduce various stylized facts of different markets and different assets with the same set of model parameters. We show that the power-law properties and the scaling of return intervals and other financial variables have a similar origin and could be a result of a general class of non-linear stochastic differential equations derived from a master equation of an agent system that is coupled by herding interactions. Specifically, we find that this approach enables us to recover the volatility return interval statistics as well as volatility probability and spectral densities for the NYSE and FOREX markets, for different assets, and for different time-scales. We find also that the historical S\&P500 monthly series exhibits the same volatility return interval properties recovered by our proposed model. Our statistical results suggest that human herding is so strong that it persists even when other evolving fluctuations perturbate the financial system.

q-fin.GN↗

arXiv2016

Crises and Physical Phases of a Bipartite Market Model

We analyze the linear response of a market network to shocks based on the bipartite market model we introduced in an earlier paper, which we claimed to be able to identify the time-line of the 2009-2011 Eurozone crisis correctly. We show that this model has three distinct phases that can broadly be categorized as "stable" and "unstable". Based on the interpretation of our behavioral parameters, the stable phase describes periods where investors and traders have confidence in the market (e.g. predict that the market rebounds from a loss). We show that the unstable phase happens when there is a lack of confidence and seems to describe "boom-bust" periods in which changes in prices are exponential. We analytically derive these phases and where the phase transition happens using a mean field approximation of the model. We show that the condition for stability is $αβ<1$ with $α$ being the inverse of the "price elasticity" and $β$ the "income elasticity of demand", which measures how rash the investors make decisions. We also show that in the mean-field limit this model reduces to the Langevin model by Bouchaud et al. for price returns.

q-fin.RM↗

arXiv2016

Impact of embedding on predictability of failure-recovery dynamics in networks

Failure, damage spread and recovery crucially underlie many spatially embedded networked systems ranging from transportation structures to the human body. Here we study the interplay between spontaneous damage, induced failure and recovery in both embedded and non-embedded networks. In our model the network's components follow three realistic processes that capture these features: (i) spontaneous failure of a component independent of the neighborhood (internal failure), (ii) failure induced by failed neighboring nodes (external failure) and (iii) spontaneous recovery of a component.We identify a metastable domain in the global network phase diagram spanned by the model's control parameters where dramatic hysteresis effects and random switching between two coexisting states are observed. The loss of predictability due to these effects depend on the characteristic link length of the embedded system. For the Euclidean lattice in particular, hysteresis and switching only occur in an extremely narrow region of the parameter space compared to random networks. We develop a unifying theory which links the dynamics of our model to contact processes. Our unifying framework may help to better understand predictability and controllability in spatially embedded and random networks where spontaneous recovery of components can mitigate spontaneous failure and damage spread in the global network.

physics.soc-ph↗

arXiv2016

Climate network suggests enhanced El Niño global impacts in localized areas

We construct directed and weighted climate networks based on near surface air temperature to investigate the global impacts of El Nino and La Nina. We find that regions which are characterized by higher positive or negative network in weighted links, are exhibiting stronger correlations with the El Nino basin and are warmer or cooler during El Nino or La Nina periods. These stronger in-weighted activities are found to be concentrated in localized areas, as compared to non-El Nino periods, whereas a large fraction of the globe is not influenced by the events. The regions of localized activity vary from one El Nino (La Nina) event to another; still some El Nino (La Nina) events are more similar to each other. We quantify this similarity using network community structure. The results and methodology reported here may be used to improve the understanding and prediction of El Nino or La Nina events and also may be applied in the investigation of other climate variables.

physics.ao-ph↗

arXiv2016

Gravitational scaling in Beijing Subway Network

Recently, with the availability of various traffic datasets, human mobility has been studied in different contexts. Researchers attempt to understand the collective behaviors of human movement with respect to the spatio-temporal distribution in traffic dynamics, from which a gravitational scaling law characterizing the relation between the traffic flow, population and distance has been found. However, most studies focus on the integrated properties of gravitational scaling, neglecting its dynamical evolution during different hours of a day. Investigating the hourly traffic flow data of Beijing subway network, based on the hop-count distance of passengers, we find that the scaling exponent of the gravitational law is smaller in Beijing subway system compared to that reported in Seoul subway system. This means that traffic demand in Beijing is much stronger and less sensitive to the travel distance. Furthermore, we analyzed the temporal evolution of the scaling exponents in weekdays and weekends. Our findings may help to understand and improve the traffic congestion control in different subway systems.

physics.soc-ph↗

arXiv2016

$k$-core percolation on complex networks: Comparing random, localized and targeted attacks

The type of malicious attack inflicting on networks greatly influences their stability under ordinary percolation in which a node fails when it becomes disconnected from the giant component. Here we study its generalization, $k$-core percolation, in which a node fails when it loses connection to a threshold $k$ number of neighbors. We study and compare analytically and by numerical simulations of $k$-core percolation the stability of networks under random attacks (RA), localized attacks (LA) and targeted attacks (TA), respectively. By mapping a network under LA or TA into an equivalent network under RA, we find that in both single and interdependent networks, TA exerts the greatest damage to the core structure of a network. We also find that for Erdős-Rényi (ER) networks, LA and RA exert equal damage to the core structure whereas for scale-free (SF) networks, LA exerts much more damage than RA does to the core structure.

physics.soc-ph↗

arXiv2016

Eradicating Catastrophic Collapse in Interdependent Networks via Reinforced Nodes

In interdependent networks, it is usually assumed, based on percolation theory, that nodes become nonfunctional if they lose connection to the network giant component. However, in reality, some nodes, equipped with alternative resources, together with their connected neighbors can still be functioning once disconnected from the giant component. Here we propose and study a generalized percolation model that introduces a fraction of reinforced nodes in the interdependent networks that can function and support their neighborhood. We analyze, both analytically and via simulations, the order parameter$-$the functioning component$-$comprising both the giant component and smaller components that include at least one reinforced node. Remarkably, we find that for interdependent networks, we need to reinforce only a small fraction of nodes to prevent abrupt catastrophic collapses. Moreover, we find that the universal upper bound of this fraction is 0.1756 for two interdependent Erdős-Rényi (ER) networks, regular-random (RR) networks and scale-free (SF) networks with large average degrees. We also generalize our theory to interdependent networks of networks (NON). Our findings might yield insight for designing resilient interdependent infrastructure networks.

physics.soc-ph↗

arXiv2016

Comparing the diversity of information by word-of-mouth vs. web spread

Many studies have explored spreading and diffusion through complex networks. The following study examines a specific case of spreading of opinions in modern society through two spreading schemes, defined as being either through word-of-mouth (WOM), or through online search engines (WEB). We apply both modelling and real experimental results and compare the opinions people adopt through an exposure to their friend`s opinions, as opposed to the opinions they adopt when using a search engine based on the PageRank algorithm. A simulated study shows that when members in a population adopt decisions through the use of the WEB scheme, the population ends up with a few dominant views, while other views are barely expressed. In contrast, when members adopt decisions based on the WOM scheme, there is a far more diverse distribution of opinions in that population. The simulative results are further supported by an online experiment which finds that people searching information through a search engine end up with far more homogenous opinions as compared to those asking their friends.

physics.soc-ph↗

arXiv2016

Collective behavior in the spatial spreading of obesity

Non-communicable diseases like diabetes, obesity and certain forms of cancer have been increasing in many countries at alarming levels. A difficulty in the conception of policies to reverse these trends is the identification of the drivers behind the global epidemics. Here, we implement a spatial spreading analysis to investigate whether diabetes, obesity and cancer show spatial correlations revealing the effect of collective and global factors acting above individual choices. We adapt a theoretical framework for critical physical systems displaying collective behavior to decipher the laws of spatial spreading of diseases. We find a regularity in the spatial fluctuations of their prevalence revealed by a pattern of scale-free long-range correlations. The fluctuations are anomalous, deviating in a fundamental way from the weaker correlations found in the underlying population distribution. This collective behavior indicates that the spreading dynamics of obesity, diabetes and some forms of cancer like lung cancer are analogous to a critical point of fluctuations, just as a physical system in a second-order phase transition. According to this notion, individual interactions and habits may have negligible influence in shaping the global patterns of spreading. Thus, obesity turns out to be a global problem where local details are of little importance. Interestingly, we find the same critical fluctuations in obesity and diabetes, and in the activities of economic sectors associated with food production such as supermarkets, food and beverage stores--- which cluster in a different universality class than other generic sectors of the economy. These results motivate future interventions to investigate the causality of this relation providing guidance for the implementation of preventive health policies.

physics.soc-ph↗

arXiv2015

Percolation properties in a traffic model

As a dynamical complex system, traffic is characterized by a transition from free flow to congestions, which is mostly studied in highways. However, despite its importance in developing congestion mitigation strategies, the understanding of this common traffic phenomenon in a city-scale is still missing. An open question is how the traffic in the network collapses from a global efficient traffic to isolated local flows in small clusters, i.e. the question of traffic percolation. Here we study the traffic percolation properties on a lattice by simulation of an agent-based model for traffic. A critical traffic volume in this model distinguishes the free-state from congested state of traffic. Our results show that the threshold of traffic percolation decreases with increasing traffic volume and reaches a minimum value at the critical traffic volume. We show that this minimal threshold is the result of longest spatial correlation between traffic flows at the critical traffic volume. These findings may help to develop congestion mitigation strategies in a network view.

physics.soc-ph↗

arXiv2015

Long-Range Correlations and Memory in the Dynamics of Internet Interdomain Routing

Data transfer is one of the main functions of the Internet. The Internet consists of a large number of interconnected subnetworks or domains, known as Autonomous Systems. Due to privacy and other reasons the information about what route to use to reach devices within other Autonomous Systems is not readily available to any given Autonomous System. The Border Gateway Protocol is responsible for discovering and distributing this reachability information to all Autonomous Systems. Since the topology of the Internet is highly dynamic, all Autonomous Systems constantly exchange and update this reachability information in small chunks, known as routing control packets or Border Gateway Protocol updates. Motivated by scalability and predictability issues with the dynamics of these updates in the quickly growing Internet, we conduct a systematic time series analysis of Border Gateway Protocol update rates. We find that Border Gateway Protocol update time series are extremely volatile, exhibit long-term correlations and memory effects, similar to seismic time series, or temperature and stock market price fluctuations. The presented statistical characterization of Border Gateway Protocol update dynamics could serve as a ground truth for validation of existing and developing better models of Internet interdomain routing.

physics.soc-ph↗

arXiv2015

Debunking in a World of Tribes

Recently a simple military exercise on the Internet was perceived as the beginning of a new civil war in the US. Social media aggregate people around common interests eliciting a collective framing of narratives and worldviews. However, the wide availability of user-provided content and the direct path between producers and consumers of information often foster confusion about causations, encouraging mistrust, rumors, and even conspiracy thinking. In order to contrast such a trend attempts to \textit{debunk} are often undertaken. Here, we examine the effectiveness of debunking through a quantitative analysis of 54 million users over a time span of five years (Jan 2010, Dec 2014). In particular, we compare how users interact with proven (scientific) and unsubstantiated (conspiracy-like) information on Facebook in the US. Our findings confirm the existence of echo chambers where users interact primarily with either conspiracy-like or scientific pages. Both groups interact similarly with the information within their echo chamber. We examine 47,780 debunking posts and find that attempts at debunking are largely ineffective. For one, only a small fraction of usual consumers of unsubstantiated information interact with the posts. Furthermore, we show that those few are often the most committed conspiracy users and rather than internalizing debunking information, they often react to it negatively. Indeed, after interacting with debunking posts, users retain, or even increase, their engagement within the conspiracy echo chamber.

cs.CY↗

arXiv2015

Spatio-temporal propagation of cascading overload failures

Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behavior of cascading overload failures analytically and numerically. The cascading overload failures are found to spread radially from the center of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict and mitigate the dynamics of cascading overload failures in realistic systems.

physics.soc-ph↗

arXiv2015

Resilience of Networks Formed of Interdependent Modular Networks

Many infrastructure networks have a modular structure and are also interdependent. While significant research has explored the resilience of interdependent networks, there has been no analysis of the effects of modularity. Here we develop a theoretical framework for attacks on interdependent modular networks and support our results by simulations. We focus on the case where each network has the same number of communities and the dependency links are restricted to be between pairs of communities of different networks. This is very realistic for infrastructure across cities. Each city has its own infrastructures and different infrastructures are dependent within the city. However, each infrastructure is connected within and between cities. For example, a power grid will connect many cities as will a communication network, yet a power station and communication tower that are interdependent will likely be in the same city. It has been shown that single networks are very susceptible to the failure of the interconnected nodes (between communities) Shai et al. and that attacks on these nodes are more crippling than attacks based on betweenness da Cunha et al. In our example of cities these nodes have long range links which are more likely to fail. For both treelike and looplike interdependent modular networks we find distinct regimes depending on the number of modules, $m$. (i) In the case where there are fewer modules with strong intraconnections, the system first separates into modules in an abrupt first-order transition and then each module undergoes a second percolation transition. (ii) When there are more modules with many interconnections between them, the system undergoes a single transition. Overall, we find that modular structure can influence the type of transitions observed in interdependent networks and should be considered in attempts to make interdependent networks more resilient.

physics.soc-ph↗

arXiv2015

Oceanic El-Niño wave dynamics and climate networks

Oceanic Kelvin and Rossby waves play an important role in tropical climate and \en dynamics. Here we develop and apply a climate network approach to quantify the characteristics of \en related oceanic waves, based on sea surface height satellite data. We associate the majority of dominant long distance ($\geq 500$ km) links of the network with (i) equatorial Kelvin waves, (ii) off-equatorial Rossby waves, and (iii) tropical instability waves. Notably, we find that the location of the hubs of out-going ($\sim 180^{\circ}\rm{E}$) and in-coming ($\sim 140^{\circ}\rm{W}$) links of the climate network coincide with the locations of the Kelvin wave initiation and dissipation, respectively. We also find that this dissipation at $\sim 140^{\circ}\rm{W}$ is much weaker during \en times. Moreover, the hubs of the off-equatorial network coincide with the locations of westerly wind burst activity and high wind vorticity, two mechanisms that were associated with Rossby waves activity. The quantitative methodology and measures developed here can improve the understanding of \en dynamics and possibly its prediction.

physics.ao-ph↗

arXiv2015

The influence of the broadness of the degree distribution on network's robustness: comparing localized attack and random attack

The stability of networks is greatly influenced by their degree distributions and in particular by their broadness. Networks with broader degree distributions are usually more robust to random failures but less robust to localized attacks. To better understand the effect of the broadness of the degree distribution we study here two models where the broadness is controlled and compare their robustness against localized attacks (LA) and random attacks (RA). We study analytically and by numerical simulations the cases where the degrees in the networks follow a Bi-Poisson distribution $P(k)=αe^{-λ_1}\frac{λ_1^k}{k!}+(1-α) e^{-λ_2}\frac{λ_2^k}{k!},α\in[0,1]$, and a Gaussian distribution $P(k)=A \cdot exp{(-\frac{(k-μ)^2}{2σ^2})}$ with a normalization constant $A$ where $k\geq 0$. In the Bi-Poisson distribution the broadness is controlled by the values of $α$, $λ_1$ and $λ_2$, while in the Gaussian distribution it is controlled by the standard deviation, $σ$. We find that only for $α=0$ or $α=1$, namely degrees obeying a pure Poisson distribution, LA and RA are the same but for all other cases networks are more vulnerable under LA compared to RA. For Gaussian distribution, with an average degree $μ$ fixed, we find that when $σ^2$ is smaller than $μ$ the network is more vulnerable against random attack. However, when $σ^2$ is larger than $μ$ the network becomes more vulnerable against localized attack. Similar qualitative results are also shown for interdependent networks.

physics.soc-ph↗

arXiv2015

Two distinct transitions in spatially embedded multiplex networks

Multilayer infrastructure is often interdependent, with nodes in one layer depending on nearby nodes in another layer to function. The links in each layer are often of limited length, due to the construction cost of longer links. Here, we model such systems as a multiplex network composed of two or more layers, each with links of characteristic geographic length, embedded in 2-dimensional space. This is equivalent to a system of interdependent spatially embedded networks in two dimensions in which the connectivity links are constrained in length but varied while the length of the dependency links is always zero. We find two distinct percolation transition behaviors depending on the characteristic length, $ζ$, of the links. When $ζ$ is longer than a certain critical value, $ζ_c$, abrupt, first-order transitions take place, while for $ζ<ζ_c$ the transition is continuous. We show that, though in single-layer networks increasing $ζ$ decreases the percolation threshold $p_c$, in multiplex networks it has the opposite effect: increasing $p_c$ to a maximum at $ζ=ζ_c$. By providing a more realistic topological model for spatially embedded interdependent and multiplex networks and highlighting its similarities to lattice-based models, we provide a new direction for more detailed future studies.

physics.soc-ph↗