arXiv subjects

Tamás Vicsek

Publications and source records attributed to Tamás Vicsek.

At least 19 recordsLinked to original sources

arXiv2026

Two-parameter Family-Vicsek scaling in a dissipative XXZ spin chain

Family-Vicsek (FV) scaling provides an understanding for the growth and finite-size saturation of fluctuations in classical systems. Here, we extend the FV roughness to transferred segment magnetization after quantum quenches in a dissipative XXZ spin chain with homogeneous gain and loss, starting from a nonequilibrium steady state with finite magnetization. In the non-interacting limit, we derive a closed-form expression for the roughness in the presence of dissipation. It displays two-parameter FV scaling and smoothly interpolates between the clean ballistic behavior and the dissipation dominated scalings. For interacting chains, tensor-network simulations show that the non-dissipative ballistic growth at finite magnetization is robust, whereas the full Lindblad evolution is generically controlled by the dissipative relaxation time and exhibits a dissipation-dominated collapse.

quant-ph↗

arXiv2025

Hierarchy and ranking in pairwise sports contests

Ranking athletes by their performance in competitions and tournaments is common in every popular sport and has significant benefits that contribute to both the organization and strategic aspects of competitions. Although rankings are perhaps the most concise and most straightforward representation of the relative strength among the competitors, beyond this one-dimensional characterization, it is also possible to capture the relationships between athletes in greater detail. Following this approach, our study examines the networks between athletes in individual sports such as tennis and fencing, where the nodes are associated with the contestants and the edges are directed from the winner to the loser. We demonstrate that the connections formed through matches arrange themselves into a time-evolving hierarchy, with the top players positioned at its apex. The structure of the resulting networks exhibits detectable differences depending on whether they are constructed purely from round-robin data or from purely elimination-style tournaments. We find that elimination tournaments lead to networks with a smaller level of hierarchy and thus, importantly, to an increased probability of circular win-loss situations (cycles). The position within the hierarchy, along with other network metrics, can be used to predict match outcomes. In the systems studied, these methods provide predictions with an accuracy comparable to that of forecasts based on official sports ranking points or the Elo rating system. A deeper understanding of the delicate aspects of the networks of pairwise contests enhances our ability to model, predict, and optimize the behaviour of many complex systems, whether in sports tournaments, social interactions, or other competitive environments.

physics.soc-ph↗

arXiv2024

CLOVE: Travelling Salesman's approach to hyperbolic embeddings of complex networks with communities

The embedding of complex networks into metric spaces has become a research topic of high interest with a wide variety of proposed methods. Low dimensional hyperbolic spaces offer a natural co-domain for embeddings allowing a roughly uniform spatial distribution of the nodes even for scale-free networks and the efficient navigability and estimation of linking probabilities. According to recent results, the communities of a complex network after optimization can be naturally mapped into well-defined angular sectors of the hyperbolic space. Here we introduce CLOVE, an embedding method exploiting this property based on iterative arrangement of the communities in a hierarchical manner, down to individual nodes. A crucial step in the process is finding the optimal angular order of the communities at a given level of the hierarchy, which is solved based on the Travelling Salesman Problem. Since CLOVE outperforms most of the alternative methods regarding different embedding quality measures and is computationally very efficient, it can be very useful in related down-stream machine learning tasks such as AI based pattern recognition.

physics.soc-ph↗

arXiv2024

Dynamical Swirl Structures Powered by Microswimmers in Active Nematics

Active nematics, in their pure form, have demonstrated a plethora of dynamic and steady state behaviors, including large-scale dynamic structures, collective flows, and intricate multi-spatial temporal dynamics. This complexity further increases in the presence of external polar agents. We investigate active nematics interspersed with polar microswimmers, akin to active apolar cells infused with active impurities, microswimmers. Our comprehensive numerical study reveals that varying the microswimmers' motility induces a novel spatiotemporal state in the active nematics backdrop. This state is marked by macroscopic swirl-like structures and a reduction in the overall order of the active nematics. Interestingly, this state emerges at intermediate motility levels, where microswimmers form local clusters and exhibit coherent motion. However, at higher motility levels, the swirls become less coherent, and microswimmer clustering intensifies. We show that the effect of the polar microswimmers on active nematics can be interpreted as a spatiotemporally correlated colored noise on active nematics, which promotes bend instability in active nematics, leading to the observed swirling dynamics. Our findings indicate that the spatiotemporal states are highly sensitive to the microswimmers' motility, offering potential avenues for pathogen identification based on known motility characteristics

cond-mat.stat-mech↗

arXiv2023

Decentralized traffic management of autonomous drones

Coordination of local and global aerial traffic has become a legal and technological bottleneck as the number of unmanned vehicles in the common airspace continues to grow. To meet this challenge, automation and decentralization of control is an unavoidable requirement. In this paper, we present a solution that enables self-organization of cooperating autonomous agents into an effective traffic flow state in which the common aerial coordination task - filled with conflicts - is resolved. Using realistic simulations, we show that our algorithm is safe, efficient, and scalable regarding the number of drones and their speed range, while it can also handle heterogeneous agents and even pairwise priorities between them. The algorithm works in any sparse or dense traffic scenario in two dimensions and can be made increasingly efficient by a layered flight space structure in three dimensions. To support the feasibility of our solution, we experimentally demonstrate coordinated aerial traffic of 100 autonomous drones within a circular area with a radius of 125 meters.

cs.RO↗

arXiv2023

Delays-induced Phase Transitions in Active Matter

We consider the patterns of collective motion emerging when many aligning, self-propelling units move in two dimensions while interacting through a repulsive potential and are also subject to delays and random perturbations. In this approach, delay plays the role analogous to reaction time so that a given particle is influenced by the information about the velocity and the position of the other particles in its vicinity with some time delay. To get insight into the involved complex flows and the transitions between them we use a simple model allowing, by fine-tuning of its few parameters, the observation and analysis of behaviours that are less accessible by experiments or analytic calculations and at the same time make the reproduction of experimental results possible. We report for the first time about a transition from an ordered, polarized collective motion to disorder as a function of the increasing time delay. For a fixed intermediate value of the delay similar transition (from order to disorder) is obtained as the repulsion radius is increased. Our simulations show a transition from total polarization to two kinds of states: fully disordered and a kind of state which is a mixture of patches of fully disordered motion in the background of orderly moving other particles. The transition occurs as the delay time is increased and is sharp, indicating that the nature of this order-disorder transition is either of first-order or is described by a sharply decreasing linear function. Our model is a simplified version of a practical situation of quickly growing interest because time delays are expected to play an increasingly important role when the traffic of many, densely distributed autonomous drones will move around in a quasi-two-dimensional air space.

cond-mat.soft↗

arXiv2019

Emergence of leader-follower hierarchy among players in an on-line experiment

Hierarchical networks are prevalent in nature and society, corresponding to groups of actors - animals, humans or even robots - organised according to a pyramidal structure with decision makers at the top and followers at the bottom. While this phenomenon is seemingly universal, the underlying governing principles are poorly understood. Here we study the emergence of hierarchies in groups of people playing a simple dot guessing game in controlled experiments, lasting for about 40 rounds, conducted over the Internet. During the games, the players had the possibility to look at the answer of a limited number of other players of their choice. This act of asking for advice defines a directed connection between the involved players, and according to our analysis, the initial random configuration of the emerging networks became more structured overt time, showing signs of hierarchy towards the end of the game. In addition, the achieved score of the players appeared to be correlated with their position in the hierarchy. These results indicate that under certain conditions imitation and limited knowledge about the performance of other actors is sufficient for the emergence of hierarchy in a social group.

physics.soc-ph↗

arXiv2017

Why we live in hierarchies: a quantitative treatise

This book is concerned with the various aspects of hierarchical collective behaviour which is manifested by most complex systems in nature. From the many of the possible topics, we plan to present a selection of those that we think are useful from the point of shedding light from very different directions onto our quite general subject. Our intention is to both present the essential contributions by the existing approaches as well as go significantly beyond the results obtained by traditional methods by applying a more quantitative approach then the common ones (there are many books on qualitative interpretations). In addition to considering hierarchy in systems made of similar kinds of units, we shall concentrate on problems involving either dominance relations or the process of collective decision-making from various viewpoints.

physics.soc-ph↗

arXiv2017

Collective motion of groups of self-propelled particles following interacting leaders

In order to keep their cohesiveness during locomotion gregarious animals must make collective decisions. Many species boast complex societies with multiple levels of communities. A common case is when two dominant levels exist, one corresponding to leaders and the other consisting of followers. In this paper we study the collective motion of such two-level assemblies of self-propelled particles. We present a model adapted from one originally proposed to describe the movement of cells resulting in a smoothly varying coherent motion. We shall use the terminology corresponding to large groups of some mammals where leaders and followers form a group called a harem. We study the emergence (self-organization) of sub-groups within a herd during locomotion by computer simulations. The resulting processes are compared with our prior observations of a Przewalski horse herd (Hortobágy, Hungary) which we use as results from a published case study. We find that the model reproduces key features of a herd composed of harems moving on open ground, including fights for followers between leaders and bachelor groups (group of leaders without followers). One of our findings, however, does not agree with the observations. While in our model the emerging group size distribution is normal, the group size distribution of the observed herd based on historical data have been found to follow lognormal distribution. We argue that this indicates that the formation (and the size) of the harems must involve a more complex social topology than simple spatial-distance based interactions.

physics.bio-ph↗

arXiv2017

Group chasing tactics: how to catch a faster prey?

We propose a bio-inspired, agent-based approach to describe the natural phenomenon of group chasing in both two and three dimensions. Using a set of local interaction rules we created a continuous-space and discrete-time model with time delay, external noise and limited acceleration. We implemented a unique collective chasing strategy, optimized its parameters and studied its properties when chasing a much faster, erratic escaper. We show that collective chasing strategies can significantly enhance the chasers' success rate. Our realistic approach handles group chasing within closed, soft boundaries - contrasting most of those published in the literature with periodic ones -- and resembles several properties of pursuits observed in nature, such as the emergent encircling or the escaper's zigzag motion.

physics.bio-ph↗

arXiv2016

Phenomenological theory of collective decision-making

An essential task of groups is to provide efficient solutions for the complex problems they face. Indeed, considerable efforts have been devoted to the question of collective decision-making related to problems involving a single dominant feature. Here we introduce a quantitative formalism for finding the optimal distribution of the group members' competences in the more typical case when the underlying problem is complex, i.e., multidimensional. Thus, we consider teams that are aiming at obtaining the best possible answer to a problem having a number of independent sub-problems. Our approach is based on a generic scheme for the process of evaluating the proposed solutions (i.e., negotiation). We demonstrate that the best performing groups have at least one specialist for each sub-problem -- but a far less intuitive result is that finding the optimal solution by the interacting group members requires that the specialists also have some insight into the sub-problems beyond their unique field(s). We present empirical results obtained by using a large-scale database of citations being in good agreement with the above theory. The framework we have developed can easily be adapted to a variety of realistic situations since taking into account the weights of the sub-problems, the opinions or the relations of the group is straightforward. Consequently, our method can be used in several contexts, especially when the optimal composition of a group of decision-makers is designed.

physics.soc-ph↗

arXiv2016

Robustness of flight leadership relations in pigeons

Collective animal movements produce spectacular natural phenomena that arise from simple local interactions among group members. Flocks of homing pigeons, Columba livia, provide a useful model for the study of collective motion and decision making. During homing flights, flock members are forced to resolve potentially divergent navigational preferences in order to stay together and benefit from flying in a group. Recent work has demonstrated that some individuals consistently contribute more to the movement decisions of the flock than others do, thereby generating stable hierarchical leader/follower networks. Yet, what attributes of a flying pigeon reliably predict leadership remains an open question. We examined the flexibility of an individual's hierarchical leadership rank (i.e. its ordinal position when flock members are ranked according to the average time differences with which they lead or follow others) as a function of changes in its navigational knowledge. We manipulated already established hierarchical networks in three different flocks, by providing certain individuals with additional homing experience. We found that such training did not consistently lead to an increase in birds' leadership ranks, and that, in general, the nature of leader/follower interactions between trained and untrained birds remained unaffected. Thus, leadership hierarchies in pigeon flocks appear resistant to changes in the navigational knowledge of a subset of their members, at least when these changes are relatively small. We discuss the implications of our results in light of the potential benefits of structural stability in decision-making networks.

physics.bio-ph↗

arXiv2015

Dimensionality constraints of light induced rotation

We have studied the conditions of rotation induced by collimated light carrying no angular momentum. Objects of different shapes and optical properties were examined in the nontrivial case where the rotation axis is perpendicular to the direction of light propagation. This geometry offers important advantages for application as it fundamentally broadens the possible practical arrangements to be realised. We found that collimated light cannot drive permanent rotation of 2D or prism-like 3D objects (i.e. fixed cross-sectional profile along the rotation axis) in the case of fully reflective or fully transparent materials. Based on both geometrical optics simulations and theoretical analysis, we derived a general condition for rotation induced by collimated light carrying no angular momentum valid for any arrangement: Permanent rotation is not possible if the scattering interaction is two-dimensional and lossless. In contrast, light induced rotation can be sustained if partial absorption is present or the object has specific true 3D geometry. We designed, simulated, fabricated, and experimentally tested a microscopic rotor capable of rotation around an axis perpendicular to the illuminating light.

physics.optics↗

arXiv2015

Hierarchical networks of scientific journals

Scientific journals are the repositories of the gradually accumulating knowledge of mankind about the world surrounding us. Just as our knowledge is organised into classes ranging from major disciplines, subjects and fields to increasingly specific topics, journals can also be categorised into groups using various metrics. In addition to the set of topics characteristic for a journal, they can also be ranked regarding their relevance from the point of overall influence. One widespread measure is impact factor, but in the present paper we intend to reconstruct a much more detailed description by studying the hierarchical relations between the journals based on citation data. We use a measure related to the notion of m-reaching centrality and find a network which shows the level of influence of a journal from the point of the direction and efficiency with which information spreads through the network. We can also obtain an alternative network using a suitably modified nested hierarchy extraction method applied to the same data. The results are weakly methodology-dependent and reveal non-trivial relations among journals. The two alternative hierarchies show large similarity with some striking differences, providing together a complex picture of the intricate relations between scientific journals.

physics.soc-ph↗

arXiv2014

Modeling the emergence of modular leadership hierarchy during the collective motion of herds made of harems

Gregarious animals need to make collective decisions in order to keep their cohesiveness. Several species of them live in multilevel societies, and form herds composed of smaller communities. We present a model for the development of a leadership hierarchy in a herd consisting of loosely connected sub-groups (e.g. harems) by combining self organization and social dynamics. It starts from unfamiliar individuals without relationships and reproduces the emergence of a hierarchical and modular leadership network that promotes an effective spreading of the decisions from more capable individuals to the others, and thus gives rise to a beneficial collective decision. Our results stemming from the model are in a good agreement with our observations of a Przewalski horse herd (Hortobágy, Hungary). We find that the harem-leader to harem-member ratio observed in Przewalski horses corresponds to an optimal network in this approach regarding common success, and that the observed and modeled harem size distributions are close to a lognormal.

physics.bio-ph↗

arXiv2014

Outdoor flocking and formation flight with autonomous aerial robots

We present the first decentralized multi-copter flock that performs stable autonomous outdoor flight with up to 10 flying agents. By decentralized and autonomous we mean that all members navigate themselves based on the dynamic information received from other robots in the vicinity. We do not use central data processing or control; instead, all the necessary computations are carried out by miniature on-board computers. The only global information the system exploits is from GPS receivers, while the units use wireless modules to share this positional information with other flock members locally. Collective behavior is based on a decentralized control framework with bio-inspiration from statistical physical modelling of animal swarms. In addition, the model is optimized for stable group flight even in a noisy, windy, delayed and error-prone environment. Using this framework we successfully implemented several fundamental collective flight tasks with up to 10 units: i) we achieved self-propelled flocking in a bounded area with self-organized object avoidance capabilities and ii) performed collective target tracking with stable formation flights (grid, rotating ring, straight line). With realistic numerical simulations we demonstrated that the local broadcast-type communication and the decentralized autonomous control method allows for the scalability of the model for much larger flocks.

cs.RO↗

arXiv2014

Anomalous segregation dynamics of self-propelled particles

A number of novel experimental and theoretical results have recently been obtained on active soft matter, demonstrating the various interesting universal and anomalous features of this kind of driven systems. Here we consider a fundamental but still unexplored aspect of the patterns arising in the system of actively moving units, i.e., their segregation taking place when two kinds of them with different adhesive properties are present. The process of segregation is studied by a model made of self-propelled particles such that the particles have a tendency to adhere only to those which are of the same kind. The calculations corresponding to the related differential equations can be made in parallel, thus a powerful GPU card allows large scale simulations. We find that the segregation kinetics is very different from the non-driven counterparts and is described by the new scaling exponents $z\simeq 1$ and $z\simeq 0.8$ for the 1:1 and the non-equal ratio of the two constituents, respectively. Our results are in agreement with a recent observation of segregating tissue cells \emph{in vitro}.

cond-mat.soft↗

arXiv2014

Flocking algorithm for autonomous flying robots

Animal swarms displaying a variety of typical flocking patterns would not exist without underlying safe, optimal and stable dynamics of the individuals. The emergence of these universal patterns can be efficiently reconstructed with agent-based models. If we want to reproduce these patterns with artificial systems, such as autonomous aerial robots, agent-based models can also be used in the control algorithm of the robots. However, finding the proper algorithms and thus understanding the essential characteristics of the emergent collective behaviour of robots requires the thorough and realistic modeling of the robot and the environment as well. In this paper, first, we present an abstract mathematical model of an autonomous flying robot. The model takes into account several realistic features, such as time delay and locality of the communication, inaccuracy of the on-board sensors and inertial effects. We present two decentralized control algorithms. One is based on a simple self-propelled flocking model of animal collective motion, the other is a collective target tracking algorithm. Both algorithms contain a viscous friction-like term, which aligns the velocities of neighbouring agents parallel to each other. We show that this term can be essential for reducing the inherent instabilities of such a noisy and delayed realistic system. We discuss simulation results about the stability of the control algorithms, and perform real experiments to show the applicability of the algorithms on a group of autonomous quadcopters.

nlin.AO↗