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Higher-order systems

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Higher-order systemsedited by Federico Battiston, Giovanni Petri.
其他作者:	Battiston, Federico.
出版者:	Cham :Springer International Publishing :2022.
面頁冊數:	x, 433 p. :ill. (chiefly col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	System analysis.
電子資源:	https://doi.org/10.1007/978-3-030-91374-8
ISBN:	9783030913748$q(electronic bk.)

Higher-order systems
Higher-order systems[electronic resource] /edited by Federico Battiston, Giovanni Petri. - Cham :Springer International Publishing :2022. - x, 433 p. :ill. (chiefly col.), digital ;24 cm. - Understanding complex systems,1860-0840. - Understanding complex systems..

Higher-order systems as a modelling framework -- Graphs, simplicial complexes and hypergraphs: Spectral theory and topology -- Random Simplicial Complexes: Models and Phenomena -- Topological Data Analysis -- Flow-based Community Detection in Hypergraphs -- Pattern formation on hypergraphs -- Non-pairwise interaction in oscillatory ensembles: From theory to data analysis -- From symmetric networks to heteroclinic dynamics and chaos in coupled phase oscillators with higher-order interactions -- Explosive synchronization and multistability in large systems of Kuramoto oscillators with higher-order interactions -- Multiorder Laplacian for Kuramoto dynamics with higher-order interactions -- The Master Stability Function for Synchronization in Simplicial Complexes -- Geometry, Topology and Simplicial Synchronization -- Signal processing on simplicial complexes -- Social contagion on higher order structures -- Consensus Dynamics and Opinion Formation on Hypergraphs -- Collective games on hypergraphs -- Topological Data Analysis of Spatial Systems -- Higher-order description of brain function -- Higher-Order Interactions in Biology: The Curious Case of Epistasis.

This book discusses its potential to model real-world systems and how considering their higher-order organization can lead to the emergence of novel dynamical behavior. Over the last decades, networks have emerged as the paradigmatic framework to model complex systems. Yet, as simple collections of nodes and links, they are intrinsically limited to pairwise interactions, limiting our ability to describe, understand, and predict complex phenomena which arise from higher-order interactions. Here we introduce the new modeling framework of higher-order systems, where hypergraphs and simplicial complexes are used to describe complex patterns of interactions among any number of agents. This book is intended both as a first introduction and an overview of the state of the art of this rapidly emerging field, serving as a reference for network scientists interested in better modeling the interconnected world we live in.

ISBN: 9783030913748$q(electronic bk.)

Standard No.: 10.1007/978-3-030-91374-8doiSubjects--Topical Terms:

182013
System analysis.

LC Class. No.: QA402 / .H54 2022

Dewey Class. No.: 003

Higher-order systems
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505 0 $a Higher-order systems as a modelling framework -- Graphs, simplicial complexes and hypergraphs: Spectral theory and topology -- Random Simplicial Complexes: Models and Phenomena -- Topological Data Analysis -- Flow-based Community Detection in Hypergraphs -- Pattern formation on hypergraphs -- Non-pairwise interaction in oscillatory ensembles: From theory to data analysis -- From symmetric networks to heteroclinic dynamics and chaos in coupled phase oscillators with higher-order interactions -- Explosive synchronization and multistability in large systems of Kuramoto oscillators with higher-order interactions -- Multiorder Laplacian for Kuramoto dynamics with higher-order interactions -- The Master Stability Function for Synchronization in Simplicial Complexes -- Geometry, Topology and Simplicial Synchronization -- Signal processing on simplicial complexes -- Social contagion on higher order structures -- Consensus Dynamics and Opinion Formation on Hypergraphs -- Collective games on hypergraphs -- Topological Data Analysis of Spatial Systems -- Higher-order description of brain function -- Higher-Order Interactions in Biology: The Curious Case of Epistasis.
520 $a This book discusses its potential to model real-world systems and how considering their higher-order organization can lead to the emergence of novel dynamical behavior. Over the last decades, networks have emerged as the paradigmatic framework to model complex systems. Yet, as simple collections of nodes and links, they are intrinsically limited to pairwise interactions, limiting our ability to describe, understand, and predict complex phenomena which arise from higher-order interactions. Here we introduce the new modeling framework of higher-order systems, where hypergraphs and simplicial complexes are used to describe complex patterns of interactions among any number of agents. This book is intended both as a first introduction and an overview of the state of the art of this rapidly emerging field, serving as a reference for network scientists interested in better modeling the interconnected world we live in.
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