arXiv subjects

Tamas Vicsek

Publications and source records attributed to Tamas Vicsek.

At least 19 recordsLinked to original sources

arXiv2026

Spatiotemporal Chaos and Defect Proliferation in Polar-Apolar Active Mixture

Chaotic transitions in inertial fluids typically proceed through a direct energy cascade from large to small scales. In contrast, active systems, composed of self propelled units, inject energy at microscopic scales and therefore exhibit an inverse cascade, giving rise to distinctly unconventional flow patterns. Here, we investigate an active mixture consisting of both apolar and polar self driven components, a setting expected to display richer behaviours than those found in living liquid crystal (LLC) systems, where the apolar constituent is passive. Using numerical solutions of the corresponding hydrodynamic equations, we uncover a variety of complex dynamical states. Our results reveal a non-monotonic response of the apolar species to changes in the density and activity of the polar component. In an intermediate regime, reminiscent of LLC-induced disorder, the system develops a dynamically disordered phase characterised by high-density, chaotically evolving band-like structures and by the continual creation and annihilation of half integer topological defects. We show that this regime exhibits spatiotemporal chaos, which we quantify through two complementary measures: the spectral properties of density fluctuations and the maximal Lyapunov exponent. Together, these findings broaden the understanding of complex transitions in active matter and suggest potential experimental realisations in bacterial suspensions or synthetic microswimmer assemblies.

cond-mat.soft↗

arXiv2024

Long-term tracking of social structure in groups of rats

Rodents serve as an important model for examining both individual and collective behavior. Dominance within rodent social structures can determine access to critical resources, such as food and mating opportunities. Yet, many aspects of the intricate interplay between individual behaviors and the resulting group social hierarchy, especially its evolution over time, remain unexplored. In this study, we utilized an automated tracking system that continuously monitored groups of male rats for over 250 days to enable an in-depth analysis of individual behavior and the overarching group dynamic. We describe the evolution of social structures within a group and additionally investigate how past behaviors influence the emergence of new social hierarchies when group composition and experimental area changes. Notably, we find that conventional individual and pairwise tests exhibit a weak correlation with group behavior, highlighting their limited accuracy in predicting behavioral outcomes in a collective context. These results emphasize the context-dependence of social behavior as an emergent property of interactions within a group and highlight the need to measure and quantify social behavior in more naturalistic environments.

q-bio.QM↗

arXiv2023

Emergence of synchronised rotations in dense active matter with disorder

We consider the rich variety of collective motion patterns emerging when aligning active particles move in the presence of randomly distributed obstacles - representing quenched noise in two dimensions. In order to get insight into the involved complex flows and the transitions between them we use a simple model allowing the observation and analysis of behaviors that are less straightforwardly accessible by experiments or analytic calculations. We find a series of symmetry breaking states in spite of the applied disorder being isotropic. In particular, as the level of perturbations is increased, the system of self-propelled particles changes its collective motion patterns from i) directed flow ii) through a mixed state of locally directed or locally rotating flow to iii) a novel, globally synchronized rotating state thereby the system violating overall chiral symmetry. Finally, this phase crosses over to a state in which iv) clusters of locally synchronized rotations are observed. The way of change from polar flow to overall synchronization can be interpreted as indicating a non-reciprocal phase transition. Our simulations suggest that when both present, quenched rather than shot noise dominates the behaviors.

cond-mat.soft↗

arXiv2021

Anomalous diffusion in the citation time series of scientific publications

We analyze the citation time-series of manuscripts in three different fields of science; physics, social science and technology. The evolution of the time-series of the yearly number of citations, namely the citation trajectories, diffuse anomalously, their variance scales with time $\propto t^{2H}$, where $H\neq 1/2$. We provide detailed analysis of the various factors that lead to the anomalous behavior: non-stationarity, long-ranged correlations and a fat-tailed increment distribution. The papers exhibit high degree of heterogeneity, across the various fields, as the statistics of the highest cited papers is fundamentally different from that of the lower ones. The citation data is shown to be highly correlated and non-stationary; as all the papers except the small percentage of them with high number of citations, die out in time.

cs.DL↗

arXiv2019

Differences in structure and dynamics of networks retrieved from dark and public web forums

Humans make decisions based on the information they obtain from several major sources, among which the comments of others in Internet forums play an increasing role. Such forums cover a wide spectrum of topics and represent an essential tool in choosing the best products, manipulating views or optimizing our decisions regarding a number of aspects of our everyday life. However, many forums have extremely controversial topics and contents including those which radicalize the readers or spread information about dangerous products and ideas (e.g., drugs, weapons or aggressive ideologies). These just mentioned activities are taking place mainly on the so-called "dark web" allowing the hiding of the identity of members using dark forums. We use network theoretical approaches to analyze the data we obtained by studying the connectivity features of the members and the threads within a wide selection of forums (including dark and semi-dark) and establish several characteristic behavioral patterns. Our findings reveal both common and rather different features in the two types of behavior. In particular, we show that the various distributions of quantities, like the activity of the commenters, the dynamics of the threads (defined using their lifetime) or the degree distributions corresponding to the three major types of forums we have investigated display characteristic deviations. This knowledge can be useful, for example, in identifying an activity typical for the dark web when it appears on the public web (since the public web can be accessed and used much more easily).

physics.soc-ph↗

arXiv2019

Modelling Hierarchical Flocking

We present a general framework for modeling a wide selection of flocking scenarios under free boundary conditions. Several variants have been considered - including examples for the widely observed behavior of hierarchically interacting units. The models we have simulated correspond to classes of various realistic situations. Our primary goal was to investigate the stability of a flock in the presence of noise. Some of our findings are counter-intuitive in the first approximation, e.g., if the hierarchy is based purely on dominance (an uneven contribution of the neighbors to the decision about the direction of flight of a given individual) the flock is more prone to loose coherence due to perturbations even when a comparison with the standard egalitarian flock is made. Thus, we concentrated on building models based on leaderfollower relationships. And, indeed, our findings support the concept that hierarchical organization can be very efficient in important practical cases, especially if the leaderfollower interactions (corresponding to an underlying directed network of interactions) have several levels. Efficiency here is associated with remaining stable (coherent and cohesive) even in cases when collective motion is destroyed by random perturbations. The framework we present allows a the study of several further complex interactions among the members of flocking agents.

physics.soc-ph↗

arXiv2017

Stability of glassy hierarchical networks

The structure of interactions in most of animals and human societies can be best represented by complex hierarchical networks. In order to maintain close to optimal functioning both stability and adaptability are necessary. Here we investigate the stability of hierarchical networks that emerge from the simulations of an organization-type having an efficiency function reminiscent of the Hamiltonian of spin-glasses. Using this quantitative approach we find a number of expected (from everyday observations) and highly non-trivial results for the obtained locally optimal networks, including such as: i) stability increases with growing efficiency and level of hierarchy, ii) the same perturbation results in a larger change for more efficient states, iii) networks with a lower level of hierarchy become more efficient after perturbation, iv) due to the huge number of possible optimal states only a small fraction of them exhibits resilience and, finally, v) "attacks" targeting the nodes selectively (regarding their position in the hierarchy) can result in paradoxical outcomes.

physics.soc-ph↗

arXiv2017

Glassy nature of hierarchical organizations

The question of why and how animal and human groups form temporarily stable hierarchical organizations has long been a great challenge from the point of quantitative interpretations. The prevailing observation/consensus is that a hierarchical social or technological structure is optimal considering a variety of aspects. Here we introduce a simple quantitative interpretation of this situation using an approach reminiscent of those developed for describing complex behaviour in terms of statistical mechanics. We look for the optimum of the efficiency function $E_{\rm eff}=1/N \sum_{i,j} J_{ij} a_i a_j$ with $J_{ij}$ denoting the nature of the interaction between the units $i$ and $j$ and $a_i$ standing for the ability of member $i$ to contribute to the efficiency of the system. Notably, this expression for $E_{\rm eff}$ has a similar structure to that of the energy as defined for spin-glasses. There is, however, an essential and novel feature of our approach: instead of optimizing by looking for a locally optimal state of the units in the nodes of a pre-defined network, we search for extrema in the complex efficiency landscape by finding locally optimal network topologies using a standard Monte Carlo method.

physics.soc-ph↗

arXiv2014

Collective motion of cells: from experiments to models

Swarming or collective motion of living entities is one of the most common and spectacular manifestations of living systems having been extensively studied in recent years. A number of general principles have been established. The interactions at the level of cells are quite different from those among individual animals therefore the study of collective motion of cells is likely to reveal some specific important features which are overviewed in this paper. In addition to presenting the most appealing results from the quickly growing related literature we also deliver a critical discussion of the emerging picture and summarize our present understanding of collective motion at the cellular level. Collective motion of cells plays an essential role in a number of experimental and real-life situations. In most cases the coordinated motion is a helpful aspect of the given phenomenon and results in making a related process more efficient (e.g., embryogenesis or wound healing), while in the case of tumor cell invasion it appears to speed up the progression of the disease. In these mechanisms cells both have to be motile and adhere to one another, the adherence feature being the most specific to this sort of collective behavior. One of the central aims of this review is both presenting the related experimental observations and treating them in the light of a few basic computational models so as to make an interpretation of the phenomena at a quantitative level as well.

q-bio.CB↗

arXiv2014

Scientometrics: Untangling the topics

Measuring science is based on comparing articles to similar others. However, keyword-based groups of thematically similar articles are dominantly small. These small sizes keep the statistical errors of comparisons high. With the growing availability of bibliographic data such statistical errors can be reduced by merging methods of thematic grouping, citation networks and keyword co-usage.

cs.DL↗

arXiv2013

Group performance is maximized by hierarchical competence distribution

Groups of people or even robots often face problems they need to solve together. Examples include collectively searching for resources, choosing when and where to invest time and effort, and many more. Although a hierarchical ordering of the relevance of the group members' inputs during collective decision making is abundant, a quantitative demonstration of its origin and advantages using a generic approach has not been described yet. Here we introduce a family of models based on the most general features of group decision making to show that the optimal distribution of competences is a highly skewed function with a structured fat tail. Our results have been obtained by optimizing the groups' compositions through identifying the best performing distributions for both the competences and for the members' flexibilities/pliancies. Potential applications include choosing the best composition for a group intended to solve a given task.

physics.soc-ph↗

arXiv2013

Overlapping modularity at the critical point of k-clique percolation

One of the most remarkable social phenomena is the formation of communities in social networks corresponding to families, friendship circles, work teams, etc. Since people usually belong to several different communities at the same time, the induced overlaps result in an extremely complicated web of the communities themselves. Thus, uncovering the intricate community structure of social networks is a non-trivial task with great potential for practical applications, gaining a notable interest in the recent years. The Clique Percolation Method (CPM) is one of the earliest overlapping community finding methods, which was already used in the analysis of several different social networks. In this approach the communities correspond to k-clique percolation clusters, and the general heuristic for setting the parameters of the method is to tune the system just below the critical point of k-clique percolation. However, this rule is based on simple physical principles and its validity was never subject to quantitative analysis. Here we examine the quality of the partitioning in the vicinity of the critical point using recently introduced overlapping modularity measures. According to our results on real social- and other networks, the overlapping modularities show a maximum close to the critical point, justifying the original criteria for the optimal parameter settings.

physics.soc-ph↗

arXiv2012

Clustering of tag-induced sub-graphs in complex networks

We study the behavior of the clustering coefficient in tagged networks. The rich variety of tags associated with the nodes in the studied systems provide additional information about the entities represented by the nodes which can be important for practical applications like searching in the networks. Here we examine how the clustering coefficient changes when narrowing the network to a sub-graph marked by a given tag, and how does it correlate with various other properties of the sub-graph. Another interesting question addressed in the paper is how the clustering coefficient of the individual nodes is affected by the tags on the node. We believe these sort of analysis help acquiring a more complete description of the structure of large complex systems.

physics.soc-ph↗

arXiv2012

Parallel clustering with CFinder

The amount of available data about complex systems is increasing every year, measurements of larger and larger systems are collected and recorded. A natural representation of such data is given by networks, whose size is following the size of the original system. The current trend of multiple cores in computing infrastructures call for a parallel reimplementation of earlier methods. Here we present the grid version of CFinder, which can locate overlapping communities in directed, weighted or undirected networks based on the clique percolation method (CPM). We show that the computation of the communities can be distributed among several CPU-s or computers. Although switching to the parallel version not necessarily leads to gain in computing time, it definitely makes the community structure of extremely large networks accessible.

physics.soc-ph↗

arXiv2012

Landing together: how flocks arrive at a coherent action in time and space in the presence of perturbations

Collective motion is abundant in nature, producing a vast amount of phenomena which have been studied in recent years, including the landing of flocks of birds. We investigate the collective decision making scenario where a flock of birds decides the optimal time of landing in the absence of a global leader. We introduce a simple phenomenological model in the spirit of the statistical mechanics-based self-propelled particles (SPP-s) approach to interpret this process. We expect that our model is applicable to a larger class of spatiotemporal decision making situations than just the landing of flocks (which process is used as a paradigmatic case). In the model birds are only influenced by observable variables, like position and velocity. Heterogeneity is introduced in the flock in terms of a depletion time after which a bird feels increasing bias to move towards the ground. Our model demonstrates a possible mechanism by which animals in a large group can arrive at an egalitarian decision about the time of switching from one activity to another in the absence of a leader. In particular, we show the existence of a paradoxical effect where noise enhances the coherence of the landing process.

physics.bio-ph↗

arXiv2012

Ontologies and tag-statistics

Due to the increasing popularity of collaborative tagging systems, the research on tagged networks, hypergraphs, ontologies, folksonomies and other related concepts is becoming an important interdisciplinary topic with great actuality and relevance for practical applications. In most collaborative tagging systems the tagging by the users is completely "flat", while in some cases they are allowed to define a shallow hierarchy for their own tags. However, usually no overall hierarchical organisation of the tags is given, and one of the interesting challenges of this area is to provide an algorithm generating the ontology of the tags from the available data. In contrast, there are also other type of tagged networks available for research, where the tags are already organised into a directed acyclic graph (DAG), encapsulating the "is a sub-category of" type of hierarchy between each other. In this paper we study how this DAG affects the statistical distribution of tags on the nodes marked by the tags in various real networks. We analyse the relation between the tag-frequency and the position of the tag in the DAG in two large sub-networks of the English Wikipedia and a protein-protein interaction network. We also study the tag co-occurrence statistics by introducing a 2d tag-distance distribution preserving both the difference in the levels and the absolute distance in the DAG for the co-occurring pairs of tags. Our most interesting finding is that the local relevance of tags in the DAG, (i.e., their rank or significance as characterised by, e.g., the length of the branches starting from them) is much more important than their global distance from the root. Furthermore, we also introduce a simple tagging model based on random walks on the DAG, capable of reproducing the main statistical features of tag co-occurrence.

physics.soc-ph↗

arXiv2010

Hierarchical group dynamics in pigeon flocks

Animals that travel together in groups display a variety of fascinating motion patterns thought to be the result of delicate local interactions among group members. Although the most informative way of investigating and interpreting collective movement phenomena would be afforded by the collection of high-resolution spatiotemporal data from moving individuals, such data are scarce and are virtually non-existent for long-distance group motion within a natural setting because of the associated technological difficulties. Here we present results of experiments in which track logs of homing pigeons flying in flocks of up to 10 individuals have been obtained by high-resolution lightweight GPS devices and analyzed using a variety of correlation functions inspired by approaches common in statistical physics. We find a well-defined hierarchy among flock members from data concerning leading roles in pairwise interactions, defined on the basis of characteristic delay times between birds' directional choices. The average spatial position of a pigeon within the flock strongly correlates with its place in the hierarchy, and birds respond more quickly to conspecifics perceived primarily through the left eye - both results revealing differential roles for birds that assume different positions with respect to flock-mates. From an evolutionary perspective, our results suggest that hierarchical organisation of group flight may be more efficient than an egalitarian one, at least for those flock sizes that permit regular pairwise interactions among group members, during which leader-follower relationships are consistently manifested.

physics.bio-ph↗

arXiv2009

Comparing bird and human soaring strategies

Gliding saves much energy, and to make large distances using only this form of flight represents a great challenge for both birds and people. The solution is to make use of the so-called thermals, which are localized, warmer regions in the atmosphere moving upwards with a speed exceeding the descent rate of bird and plane. Whereas birds use this technique mainly for foraging, humans do it as a sporting activity. Thermalling involves efficient optimization including the skilful localization of thermals, trying to guess the most favorable route, estimating the best descending rate, etc. In this study, we address the question whether there are any analogies between the solutions birds and humans find to handle the above task. High-resolution track logs were taken from thermalling falcons and paraglider pilots to determine the essential parameters of the flight patterns. We find that there are relevant common features in the ways birds and humans use thermals. In particular, falcons seem to reproduce the MacCready formula widely used by gliders to calculate the best slope to take before an upcoming thermal.

physics.bio-ph↗