1. Synchronization in simplicial complexes of memristive Rulkov neuronsMahtab Mehrabbeik, Sajad Jafari, Matjaž Perc, 2023, original scientific article Abstract: Simplicial complexes are mathematical constructions that describe higher-order interactions within the interconnecting elements of a network. Such higher-order interactions become increasingly significant in neuronal networks since biological backgrounds and previous outcomes back them. In light of this, the current research explores a higher-order network of the memristive Rulkov model. To that end, the master stability functions are used to evaluate the synchronization of a network with pure pairwise hybrid (electrical and chemical) synapses alongside a network with two-node electrical and multi-node chemical connections. The findings provide good insight into the impact of incorporating higher-order interaction in a network. Compared to two-node chemical synapses, higher-order interactions adjust the synchronization patterns to lower multi-node chemical coupling parameter values. Furthermore, the effect of altering higher-order coupling parameter value on the dynamics of neurons in the synchronization state is researched. It is also shown how increasing network size can enhance synchronization by lowering the value of coupling parameters whereby synchronization occurs. Except for complete synchronization, cluster synchronization is detected for higher electrical coupling strength values wherein the neurons are out of the completed synchronization state.
Keywords: simplicial complex, higher-order network, memristive Rulkov, synchronization, cluster synchronization
Published in DKUM: 11.09.2024; Views: 37; Downloads: 2
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2. Why are there six degrees of separation in a social network?I. Samoylenko, D. Aleja, E. Primo, Karin Alfaro-Bittner, E. Vasilyeva, K. Kovalenko, D. Musatov, A. M. Raigorodskii, R. Criado, M. Romance, David Papo, Matjaž Perc, B. Barzel, Stefano Boccaletti, 2023, original scientific article Abstract: A wealth of evidence shows that real-world networks are endowed with the small-world property, i.e., that the maximal distance between any two of their nodes scales logarithmically rather than linearly with their size. In addition, most social networks are organized so that no individual is more than six connections apart from any other, an empirical regularity known as the six degrees of separation. Why social networks have this ultrasmall-world organization, whereby the graph’s diameter is independent of the network size over several orders of magnitude, is still unknown. We show that the “six degrees of separation” is the property featured by the equilibrium state of any network where individuals weigh between their aspiration to improve their centrality and the costs incurred in forming and maintaining connections. We show, moreover, that the emergence of such a regularity is compatible with all other features, such as clustering and scale-freeness, that normally characterize the structure of social networks. Thus, our results show how simple evolutionary rules of the kind traditionally associated with human cooperation and altruism can also account for the emergence of one of the most intriguing attributes of social networks.
Keywords: degree distribution, network evolution, complex network, small-world network, social physics
Published in DKUM: 16.07.2024; Views: 111; Downloads: 8
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3. Segregation dynamics driven by network leadersWen-Xuan Wang, Yuhao Feng, Siru Chen, Wenzhe Xu, Xinjian Zhuo, Huijia Li, Matjaž Perc, 2022, original scientific article Abstract: Network segregation - a critical problem in real-life networks - can reveal the emergence of conflicts or signal an impending collapse of the whole system. However, the strong heterogeneity of such networks and the various definitions for key nodes continue to pose challenges that limit our ability to foresee segregation and to determine the main drivers behind it. In this paper, we show that a multi-agent leader-follower consensus system can be utilized to define a new index, named leadership, to identify key leaders in real-life networks. And then, this paper explores the emergence of network segregation that is driven by these leaders based on the removal or the rewiring of the relations between different nodes in agreement with their contribution distance. We finally show that the observed leaders-driven segregation dynamics reveals the dynamics of heterogeneous attributes that critically influence network structure and its segregation. Thus, this paper provides a theoretical method to study complex social interactions and their roles in network segregation, which ultimately leads to a closed-form explanation for the emergence of imbalanced network structure from an evolutionary perspective.
Keywords: complex networks, network segregation, multi-agent leader–follower consensus system, key leaders identification, leader, segregation, social physics
Published in DKUM: 08.07.2024; Views: 122; Downloads: 7
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4. Reputation and reciprocity : reviewChengyi Xia, Juan Wang, Matjaž Perc, Zhen Wang, 2023, review article Abstract: Reputation and reciprocity are key mechanisms for cooperation in human societies, often going hand in hand to favor prosocial behavior over selfish actions. Here we review recent researches at the interface of physics and evolutionary game theory that explored these two mechanisms. We focus on image scoring as the bearer of reputation, as well as on various types of reciprocity, including direct, indirect, and network reciprocity. We review different definitions of reputation and reciprocity dynamics, and we show how these affect the evolution of cooperation in social dilemmas. We consider first-order, second-order, as well as higherorder models in well-mixed and structured populations, and we review experimental works that support and inform the results of mathematical modeling and simulations. We also provide a synthesis of the reviewed researches along with an outlook in terms of six directions that seem particularly promising to explore in the future.
Keywords: pattern formation, Monte Carlo method, complex network, evolutionary game theory, cooperation, social physics
Published in DKUM: 20.06.2024; Views: 154; Downloads: 10
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5. Determinants of collective failure in excitable networksUroš Barać, Matjaž Perc, Marko Gosak, 2023, original scientific article Abstract: We study collective failures in biologically realistic networks that consist of coupled excitable units. The networks have broad-scale degree distribution, high modularity, and small-world properties, while the excitable dynamics is determined by the paradigmatic FitzHugh–Nagumo model. We consider different coupling strengths, bifurcation distances, and various aging scenarios as potential culprits of collective failure. We find that for intermediate coupling strengths, the network remains globally active the longest if the high-degree nodes are first targets for inactivation. This agrees well with previously published results, which showed that oscillatory networks can be highly fragile to the targeted inactivation of low-degree nodes, especially under weak coupling. However, we also show that the most efficient strategy to enact collective failure does not only non-monotonically depend on the coupling strength, but it also depends on the distance from the bifurcation point to the oscillatory behavior of individual excitable units. Altogether, we provide a comprehensive account of determinants of collective failure in excitable networks, and we hope this will prove useful for better understanding breakdowns in systems that are subject to such dynamics.
Keywords: collective behavior, excitable media, complex network, neuronal dynamics
Published in DKUM: 10.06.2024; Views: 163; Downloads: 14
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6. Inheritance patterns in citation networks reveal scientific memesTobias Kuhn, Matjaž Perc, Dirk Helbing, 2014, original scientific article Abstract: Memes are the cultural equivalent of genes that spread across human culture by means of imitation. What makes a meme and what distinguishes it from other forms of information, however, is still poorly understood. Our analysis of memes in the scientific literature reveals that they are governed by a surprisingly simple relationship between frequency of occurrence and the degree to which they propagate along the citation graph. We propose a simple formalization of this pattern and validate it with data from close to 50 million publication records from the Web of Science, PubMed Central, and the American Physical Society. Evaluations relying on human annotators, citation network randomizations, and comparisons with several alternative approaches confirm that our formula is accurate and effective, without a dependence on linguistic or ontological knowledge and without the application of arbitrary thresholds or filters.
Keywords: memes, inheritance, genes, network science, complex systems
Published in DKUM: 03.08.2017; Views: 1545; Downloads: 429
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7. The complexity of porous structure of building materialsMarko Samec, 2011, dissertation Abstract: This thesis seeks to establish the link between the structure (in a topological sense) of porous space and charged particle dynamics in porous matter, specifically in constituent elements of sustainable building materials such as clay, cement and soil. The work done is a combination of experimental research and modelling of analysed data using advanced and expanded network models to model pore structure and generalized conductivity model. The main outcome of this doctoral thesis is the demonstration that there is a correlation between the large scale structure of the pore space and the properties of the motion of charged particles through the pore space. This was achieved by conducting two experiments: the structure of pore space of selected porous materials (soil samples, clays, cements, clay-cement mixtures) was investigated using state-of-the-art X-ray computed microtomography, while the dynamics of charged particles in the samples was probed using low-frequency dielectric spectroscopy. The research done and described in the thesis is directed towards the advancement of understanding the transport phenomena and the structure of porous media which is of paramount importance for solving problems in building physics dealing with moist transport in building's envelope, the building-ground interaction, and in transport of contaminants in the vicinity of the repositories where the transfer of moist through soil can be the source of contamination.
Keywords: porous matter, clay-water system, hydrating cement, fractional dynamics, dielectric response, X-ray computed tomography, image analysis, complex network
Published in DKUM: 11.05.2011; Views: 4887; Downloads: 266
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