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The net of N ``physical'' neurons is considered as a dynamical system. These neurons form a complete graph. The state of any neuron is its electric potential. The potential linearly increases until reaches its maximal value. Then it falls…

Dynamical Systems · Mathematics 2025-10-28 S. A. Pirogov , A. N. Rybko , D. D. Pervouchine , E. N. Petrova

The topological structure of complex networks has fascinated researchers for several decades, resulting in the discovery of many universal properties and reoccurring characteristics of different kinds of networks. However, much less is…

Social and Information Networks · Computer Science 2017-06-28 Yvonne Anne Pignolet , Matthieu Roy , Stefan Schmid , Gilles Tredan

The topological structure of complex networks has fascinated researchers for several decades, resulting in the discovery of many universal properties and reoccurring characteristics of different kinds of networks. However, much less is…

Social and Information Networks · Computer Science 2017-03-02 Yvonne Anne Pignolet , Matthieu Roy , Stefan Schmid , Gilles Tredan

Real complex systems are inherently time-varying. Thanks to new communication systems and novel technologies, it is today possible to produce and analyze social and biological networks with detailed information on the time of occurrence and…

Physics and Society · Physics 2012-04-17 V. Nicosia , J. Tang , M. Musolesi , G. Russo , C. Mascolo , V. Latora

Causal Graph Dynamics generalize Cellular Automata, extending them to bounded degree, time varying graphs. The dynamics rewrite the graph at each time step with respect to two physics-like symmetries: causality (bounded speed of…

Discrete Mathematics · Computer Science 2016-02-04 Simon Martiel , Bruno Martin

A finite dynamical system is a system of multivariate functions over a finite alphabet used to model a network of interacting entities. The main feature of a finite dynamical system is its interaction graph, which indicates which local…

Combinatorics · Mathematics 2017-01-12 Maximilien Gadouleau

We study the time-averaged flow in a model of particles that randomly hop on a finite directed graph. In the limit as the number of particles and the time window go to infinity but the graph remains finite, the large-deviation rate…

Statistical Mechanics · Physics 2020-12-02 Davide Gabrielli , D. R. Michiel Renger

Time-continuous dynamical systems defined on graphs are often used to model complex systems with many interacting components in a non-spatial context. In the reverse sense attaching meaningful dynamics to given 'interaction diagrams' is a…

Molecular Networks · Quantitative Biology 2010-07-02 Markus Kirkilionis , Luca Sbano

Cities can be seen as the epitome of complex systems. They arise from a set of interactions and components so diverse that is almost impossible to describe them exhaustively. Amid this diversity, we chose an object which orchestrates the…

Physics and Society · Physics 2015-12-07 Claire Lagesse

Graphs are used in many disciplines to model the relationships that exist between objects in a complex discrete system. Researchers may wish to compare a network of interest to a "typical" graph from a family (or ensemble) of graphs which…

Combinatorics · Mathematics 2025-08-08 Catherine Greenhill

This note aims to bring attention to a simple class of discrete dynamical systems exhibiting some complex behaviour. Each of these systems is defined as a self-mapping of the unit square and is obtained by coupling two families of…

Dynamical Systems · Mathematics 2012-01-20 Chris Preston

Urban mobility forecast and analysis can be addressed through grid-based and graph-based models. However, graph-based representations have the advantage of more realistically depicting the mobility networks and being more robust since they…

Discrete Mathematics · Computer Science 2023-10-11 Rafael Martínez Márquez , Giuseppe Patanè

Understanding and interacting with everyday physical scenes requires rich knowledge about the structure of the world, represented either implicitly in a value or policy function, or explicitly in a transition model. Here we introduce a new…

The theory of graphons has proven to be a powerful tool in many areas of graph theory. In this paper, we introduce several foundational aspects of the theory of digraphons -- asymmetric two-variable functions that arise as limits of…

Combinatorics · Mathematics 2025-12-16 Jan Hladký , Petr Savický

A system of $N$ interacting objects with internal degrees of freedom is considered. Derivation of system of equations for the description of two interacting objects with spin is given. Relations between the parameters describing subsystems…

Classical Physics · Physics 2013-05-08 Alexander N. Tarakanov

Dynamical systems are a broad class of mathematical tools used to describe the evolution of physical and computational processes. Traditionally these processes model changing entities in a static world. Picture a ball rolling on an empty…

Category Theory · Mathematics 2020-07-30 Sophie Libkind

Hypergraphs have emerged as a powerful modeling framework to represent systems with multiway interactions, that is systems where interactions may involve an arbitrary number of agents. Here we explore the properties of real-world…

Social and Information Networks · Computer Science 2023-07-11 Timothy LaRock , Renaud Lambiotte

Dynamic graphs have emerged as an appropriate model to capture the changing nature of many modern networks, such as peer-to-peer overlays and mobile ad hoc networks. Most of the recent research on dynamic networks has only addressed the…

Data Structures and Algorithms · Computer Science 2011-02-02 Oksana Denysyuk , Luis Rodrigues

Many systems comprising entities in interactions can be represented as graphs, whose structure gives significant insights about how these systems work. Network theory has undergone further developments, in particular in relation to…

Data Analysis, Statistics and Probability · Physics 2016-06-14 Ronan Hamon , Pierre Borgnat , Patrick Flandrin , Céline Robardet

Many aspects of graphs have been studied in depth. However, forecasting the structure of a graph at future time steps incorporating unseen, new nodes and edges has not gained much attention. In this paper, we present such an approach. Using…

Machine Learning · Computer Science 2024-07-26 Sevvandi Kandanaarachchi , Ziqi Xu , Stefan Westerlund