arXiv subjects

Albert-László Barabási

Publications and source records attributed to Albert-László Barabási.

At least 55 records · Page 3Linked to original sources

arXiv2013

Effect of correlations on network controllability

A dynamical system is controllable if by imposing appropriate external signals on a subset of its nodes, it can be driven from any initial state to any desired state in finite time. Here we study the impact of various network characteristics on the minimal number of driver nodes required to control a network. We find that clustering and modularity have no discernible impact, but the symmetries of the underlying matching problem can produce linear, quadratic or no dependence on degree correlation coefficients, depending on the nature of the underlying correlations. The results are supported by numerical simulations and help narrow the observed gap between the predicted and the observed number of driver nodes in real networks.

physics.soc-ph↗

arXiv2012

Sex differences in intimate relationships

Social networks have turned out to be of fundamental importance both for our understanding human sociality and for the design of digital communication technology. However, social networks are themselves based on dyadic relationships and we have little understanding of the dynamics of close relationships and how these change over time. Evolutionary theory suggests that, even in monogamous mating systems, the pattern of investment in close relationships should vary across the lifespan when post-weaning investment plays an important role in maximising fitness. Mobile phone data sets provide us with a unique window into the structure of relationships and the way these change across the lifespan. We here use data from a large national mobile phone dataset to demonstrate striking sex differences in the pattern in the gender-bias of preferred relationships that reflect the way the reproductive investment strategies of the two sexes change across the lifespan: these differences mainly reflect women's shifting patterns of investment in reproduction and parental care. These results suggest that human social strategies may have more complex dynamics than we have tended to assume and a life-history perspective may be crucial for understanding them.

physics.soc-ph↗

arXiv2012

A universal model for mobility and migration patterns

Introduced in its contemporary form by George Kingsley Zipf in 1946, but with roots that go back to the work of Gaspard Monge in the 18th century, the gravity law is the prevailing framework to predict population movement, cargo shipping volume, inter-city phone calls, as well as bilateral trade flows between nations. Despite its widespread use, it relies on adjustable parameters that vary from region to region and suffers from known analytic inconsistencies. Here we introduce a stochastic process capturing local mobility decisions that helps us analytically derive commuting and mobility fluxes that require as input only information on the population distribution. The resulting radiation model predicts mobility patterns in good agreement with mobility and transport patterns observed in a wide range of phenomena, from long-term migration patterns to communication volume between different regions. Given its parameter-free nature, the model can be applied in areas where we lack previous mobility measurements, significantly improving the predictive accuracy of most of phenomena affected by mobility and transport processes.

physics.soc-ph↗

arXiv2012

Control centrality and hierarchical structure in complex networks

We introduce the concept of control centrality to quantify the ability of a single node to control a directed weighted network. We calculate the distribution of control centrality for several real networks and find that it is mainly determined by the network's degree distribution. We rigorously prove that in a directed network without loops the control centrality of a node is uniquely determined by its layer index or topological position in the underlying hierarchical structure of the network. Inspired by the deep relation between control centrality and hierarchical structure in a general directed network, we design an efficient attack strategy against the controllability of malicious networks.

physics.soc-ph↗

arXiv2011

Universal features of correlated bursty behaviour

Inhomogeneous temporal processes, like those appearing in human communications, neuron spike trains, and seismic signals, consist of high-activity bursty intervals alternating with long low-activity periods. In recent studies such bursty behavior has been characterized by a fat-tailed inter-event time distribution, while temporal correlations were measured by the autocorrelation function. However, these characteristic functions are not capable to fully characterize temporally correlated heterogenous behavior. Here we show that the distribution of the number of events in a bursty period serves as a good indicator of the dependencies, leading to the universal observation of power-law distribution in a broad class of phenomena. We find that the correlations in these quite different systems can be commonly interpreted by memory effects and described by a simple phenomenological model, which displays temporal behavior qualitatively similar to that in real systems.

physics.soc-ph↗

arXiv2011

Flavor network and the principles of food pairing

The cultural diversity of culinary practice, as illustrated by the variety of regional cuisines, raises the question of whether there are any general patterns that determine the ingredient combinations used in food today or principles that transcend individual tastes and recipes. We introduce a flavor network that captures the flavor compounds shared by culinary ingredients. Western cuisines show a tendency to use ingredient pairs that share many flavor compounds, supporting the so-called food pairing hypothesis. By contrast, East Asian cuisines tend to avoid compound sharing ingredients. Given the increasing availability of information on food preparation, our data-driven investigation opens new avenues towards a systematic understanding of culinary practice.

physics.soc-ph↗

arXiv2011

Collective response of human populations to large-scale emergencies

Despite recent advances in uncovering the quantitative features of stationary human activity patterns, many applications, from pandemic prediction to emergency response, require an understanding of how these patterns change when the population encounters unfamiliar conditions. To explore societal response to external perturbations we identified real-time changes in communication and mobility patterns in the vicinity of eight emergencies, such as bomb attacks and earthquakes, comparing these with eight non-emergencies, like concerts and sporting events. We find that communication spikes accompanying emergencies are both spatially and temporally localized, but information about emergencies spreads globally, resulting in communication avalanches that engage in a significant manner the social network of eyewitnesses. These results offer a quantitative view of behavioral changes in human activity under extreme conditions, with potential long-term impact on emergency detection and response.

physics.soc-ph↗

arXiv2011

Geographic constraints on social network groups

Social groups are fundamental building blocks of human societies. While our social interactions have always been constrained by geography, it has been impossible, due to practical difficulties, to evaluate the nature of this restriction on social group structure. We construct a social network of individuals whose most frequent geographical locations are also known. We also classify the individuals into groups according to a community detection algorithm. We study the variation of geographical span for social groups of varying sizes, and explore the relationship between topological positions and geographic positions of their members. We find that small social groups are geographically very tight, but become much more clumped when the group size exceeds about 30 members. Also, we find no correlation between the topological positions and geographic positions of individuals within network communities. These results suggest that spreading processes face distinct structural and spatial constraints.

physics.soc-ph↗

arXiv2010

New generation of mobile phone viruses and corresponding countermeasures

The fast growing market for smart phones coupled with their almost continuous online presence makes these devices the new targets of virus writers. It has been recently found that the topological spread of MMS (Multimedia Message Services) viruses is highly restricted by the underlying fragmentation of the call graph. In this paper, we study MMS viruses under another type of spreading behavior: scanning. We find that hybrid MMS viruses including some level of scanning are more dangerous to the mobile community than their standard topological counterparts. However, the effectiveness of both scanning and topological behaviors in MMS viruses can generally be limited by two controlling methods: (i) decreasing susceptible handsets' market share (OS it runs) and (ii) improving monitoring capacity to limit the frequency in which MMS messages can be sent by the mobile viruses.

cs.NI↗

arXiv2010

Modeling the scaling properties of human mobility

While the fat tailed jump size and the waiting time distributions characterizing individual human trajectories strongly suggest the relevance of the continuous time random walk (CTRW) models of human mobility, no one seriously believes that human traces are truly random. Given the importance of human mobility, from epidemic modeling to traffic prediction and urban planning, we need quantitative models that can account for the statistical characteristics of individual human trajectories. Here we use empirical data on human mobility, captured by mobile phone traces, to show that the predictions of the CTRW models are in systematic conflict with the empirical results. We introduce two principles that govern human trajectories, allowing us to build a statistically self-consistent microscopic model for individual human mobility. The model not only accounts for the empirically observed scaling laws but also allows us to analytically predict most of the pertinent scaling exponents.

cond-mat.dis-nn↗

arXiv2005

The origin of bursts and heavy tails in human dynamics

The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behavior into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes. In contrast, there is increasing evidence that the timing of many human activities, ranging from communication to entertainment and work patterns, follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity. Here we show that the bursty nature of human behavior is a consequence of a decision based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, most tasks being rapidly executed, while a few experience very long waiting times. In contrast, priority blind execution is well approximated by uniform interevent statistics. These findings have important implications from resource management to service allocation in both communications and retail.

cond-mat.stat-mech↗

arXiv2004

Two-dimensional particle motion in a random potential under ac bias

We study the Brownian motion of a single particle coupled to an external ac field in a two-dimensional random potential. We find that for small fields a large-scale vorticity pattern of the steady-state net currents emerges, a consequence of local symmetry breaking. In this regime the net currents are highly correlated, the spatial correlation function follows a logarithmic dependence, and the correlation length is of the order of the system size. For large external fields correlations disappear and only random net currents patterns are observed. The numerical analysis indicates that the correlation length scales as a power law with both the size of the system and the amplitude of the ac field.

cond-mat.stat-mech↗

arXiv2000

Morphology of Ion-Sputtered Surfaces

We derive a stochastic nonlinear continuum theory to describe the morphological evolution of amorphous surfaces eroded by ion bombardment. Starting from Sigmund's theory of sputter erosion, we calculate the coefficients appearing in the continuum equation in terms of the physical parameters characterizing the sputtering process. We analyze the morphological features predicted by the continuum theory, comparing them with the experimentally reported morphologies. We show that for short time scales, where the effect of nonlinear terms is negligible, the continuum theory predicts ripple formation. We demonstrate that in addition to relaxation by thermal surface diffusion, the sputtering process can also contribute to the smoothing mechanisms shaping the surface morphology. We explicitly calculate an effective surface diffusion constant characterizing this smoothing effect, and show that it is responsible for the low temperature ripple formation observed in various experiments. At long time scales the nonlinear terms dominate the evolution of the surface morphology. The nonlinear terms lead to the stabilization of the ripple wavelength and we show that, depending on the experimental parameters such as angle of incidence and ion energy, different morphologies can be observed: asymptotically, sputter eroded surfaces could undergo kinetic roughening, or can display novel ordered structures with rotated ripples. Finally, we discuss in detail the existing experimental support for the proposed theory, and uncover novel features of the surface morphology and evolution, that could be directly tested experimentally.

cond-mat.mtrl-sci↗

arXiv1997

Self-assembled island formation in heteroepitaxial growth

We investigate island formation during heteroepitaxial growth using an atomistic model that incorporates deposition, activated diffusion and stress relaxation. For high misfit the system naturally evolves into a state characterized by a narrow island size distribution. The simulations indicate the existence of a strain assisted kinetic mechanism responsible for the self-assembling process, involving enhanced detachment of atoms from the edge of large islands and biased adatom diffusion.

cond-mat.stat-mech↗

arXiv1997

Self-organized superlattice formation in II-VI and III-V semiconductors

There is extensive recent experimental evidence of spontaneous superlattice (SL) formation in various II-VI and III-V semiconductors. Here we propose an atomistic mechanism responsible for SL formation, and derive a relation predicting the temperature, flux and miscut dependence of the SL layer thickness. Moreover, the model explains the existence of a critical miscut angle below which no SL is formed, in agreement with results on ZnSeTe, and predicts the formation of a platelet structure for deposition onto high symmetry surfaces, similar to that observed in InAsSb.

cond-mat.stat-mech↗

arXiv1995

Elastic String in a Random Medium

We consider a one dimensional elastic string as a set of massless beads interacting through springs characterized by anisotropic elastic constants. The string, driven by an external force, moves in a medium with quenched disorder. We present evidence that the consideration of longitudinal fluctuations leads to nonlinear behavior in the equation of motion which is {\it kinematically} generated by the motion of the string. The strength of the nonlinear effects depends on the anisotropy of the medium and the distance from the depinning transition. On the other hand the consideration of restricted solid on solid conditions imposed to the growth of the string leads to a nonlinear term in the equation of motion with a {\it diverging} coefficient at the depinning transition.

cond-mat↗

arXiv1995

Dynamics of Random Networks: Connectivity and First Order Phase Transitions

The connectivity of individual neurons of large neural networks determine both the steady state activity of the network and its answer to external stimulus. Highly diluted random networks have zero activity. We show that increasing the network connectivity the activity changes discontinuously from zero to a finite value as a critical value in the connectivity is reached. Theoretical arguments and extensive numerical simulations indicate that the origin of this discontinuity in the activity of random networks is a first order phase transition from an inactive to an active state as the connectivity of the network is increased.

cond-mat↗

arXiv1995

A fractal model for the first stages of thin film growth

In this paper we briefly review a model that describes the diffusion-controlled aggregation exhibited by particles as they are deposited on a surface. This model allows to understand many experiments of thin film deposition. In the first part, we describe the model, which incorporates deposition, particle and cluster diffusion, and aggregation. In a second part, we study the dynamical evolution of the model. Finally, we analyze the effects of small cluster mobility, and we show that the introduction of cluster diffusion dramatically affects the dynamics of film growth. Some of these effects can be tested experimentally.

cond-mat↗