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Temporal networks model how the interaction between elements in a complex system evolve over time. Just like complex systems display collective dynamics, here we interpret temporal networks as trajectories performing a collective motion in…

Social and Information Networks · Computer Science 2022-10-18 Lucas Lacasa , Jorge P. Rodriguez , Victor M. Eguiluz

A nonsplit graph is a directed graph where each pair of nodes has a common incoming neighbor. We show that the radius of such graphs is in $O(\log \log n)$, where $n$ is the number of nodes. We then generalize the result to products of…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-01-23 Matthias Függer , Thomas Nowak , Kyrill Winkler

The modeling of diffusion processes on graphs is the basis for many network science and machine learning approaches. Entropic measures of network-based diffusion have recently been employed to investigate the reversibility of these…

Dynamical Systems · Mathematics 2025-10-23 Samuel Koovely , Alexandre Bovet

Temporal graphs represent the dynamic relationships among entities and occur in many real life application like social networks, e commerce, communication, road networks, biological systems, and many more. They necessitate research beyond…

Machine Learning · Computer Science 2022-08-26 Shubham Gupta , Srikanta Bedathur

Understanding how cities transition from free-flowing to congested traffic remains a central open problem in urban science. Here we show that city-scale congestion undergoes a reproducible nonlinear transition analogous to an order-disorder…

Physics and Society · Physics 2026-05-06 Luis E. Olmos

We explore the interplay of network structure, topology, and dynamic interactions between nodes using the paradigm of distributed synchronization in a network of coupled oscillators. As the network evolves to a global steady state,…

Disordered Systems and Neural Networks · Physics 2015-06-04 Kristina Lerman , Rumi Ghosh

Modelling long-range dependencies is critical for scene understanding tasks in computer vision. Although convolution neural networks (CNNs) have excelled in many vision tasks, they are still limited in capturing long-range structured…

Computer Vision and Pattern Recognition · Computer Science 2022-09-21 Li Zhang , Mohan Chen , Anurag Arnab , Xiangyang Xue , Philip H. S. Torr

Much recent research has dealt with the identifiability of a dynamical network in which the node signals are connected by causal linear transfer functions and are excited by known external excitation signals and/or unknown noise signals. A…

Optimization and Control · Mathematics 2018-03-18 Julien M. Hendrickx , Michel Gevers , Alexandre S. Bazanella

Given a weighted graph, we introduce a partition of its vertex set such that the distance between any two clusters is bounded from below by a power of the minimum weight of both clusters. This partition is obtained by recursively merging…

Probability · Mathematics 2020-03-16 Laurent Ménard , Arvind Singh

In the modeling, monitoring, and control of complex networks, a fundamental problem concerns the comprehensive determination of the state of the system from limited measurements. Using power grids as example networks, we show that this…

Physics and Society · Physics 2013-01-28 Yang Yang , Jianhui Wang , Adilson E. Motter

Percolation is perhaps the simplest example of a process exhibiting a phase transition and one of the most studied phenomena in statistical physics. The percolation transition is continuous if sites/bonds are occupied independently with the…

Statistical Mechanics · Physics 2015-05-27 Santo Fortunato , Filippo Radicchi

Introduced the quantitative measure of the structural complexity of the graph (complex network, etc.) based on a procedure similar to the renormalization process, considering the difference between actual and averaged graph structures on…

Physics and Society · Physics 2024-06-05 A. A. Snarskii

This paper develops a neural jamming phase diagram that interprets the emergence of consciousness in large language models as a critical phenomenon in high-dimensional disordered systems.By establishing analogies with jamming transitions in…

Disordered Systems and Neural Networks · Physics 2025-07-14 Kaichen Ouyang

Networks are useful for describing systems of interacting objects, where the nodes represent the objects and the edges represent the interactions between them. The applications include chemical and metabolic systems, food webs as well as…

Computational Physics · Physics 2009-10-20 Baruch Barzel , Ofer Biham

Inflection graphs are highly complex networks representing relationships between inflectional forms of words in human languages. For so-called synthetic languages, such as Latin or Polish, they have particularly interesting structure due to…

Cellular Automata and Lattice Gases · Physics 2023-12-18 Henryk Fukś , Babak Farzad , Yi Cao

We consider systems that are well modelled as a networks that evolve in time, which we call {\it Moving Neighborhood Networks}. These models are relevant in studying cooperative behavior of swarms and other phenomena where emergent…

Chaotic Dynamics · Physics 2007-05-23 Joseph D. Skufca , Erik M. Bollt

Many real-world interactions (e.g., researcher collaborations and email communication) occur among multiple entities. These group interactions are naturally modeled as hypergraphs. In graphs, transitivity is helpful to understand the…

Social and Information Networks · Computer Science 2023-10-27 Sunwoo Kim , Fanchen Bu , Minyoung Choe , Jaemin Yoo , Kijung Shin

Many real-world systems can be modeled as interconnected multilayer networks, namely a set of networks interacting with each other. Here we present a perturbative approach to study the properties of a general class of interconnected…

Physics and Society · Physics 2018-07-10 Giacomo Rapisardi , Alex Arenas , Guido Caldarelli , Giulio Cimini

The intrinsically secure communications graph (iS-graph) is a random graph which captures the connections that can be securely established over a large-scale network, in the presence of eavesdroppers. It is based on principles of…

Information Theory · Computer Science 2016-11-18 Pedro C. Pinto , Moe Z. Win

Percolation theory has been largely used in the study of structural properties of complex networks such as the robustness, with remarkable results. Nevertheless, a purely topological description is not sufficient for a correct…

Statistical Mechanics · Physics 2016-08-31 Luca Dall'Asta