Higher-order systems / Federico Battiston, Giovanni Petri, editors.

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...

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Bibliographic Details
Other Authors: Battiston, Federico (Editor), Petri, Giovanni (Editor)
Format: eBook
Language:English
Published: Cham : Springer, [2022]
Series:Understanding complex systems.
Subjects:
Online Access:Click for online access

MARC

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245 0 0 |a Higher-order systems /  |c Federico Battiston, Giovanni Petri, editors. 
264 1 |a Cham :  |b Springer,  |c [2022] 
264 4 |c ©2022 
300 |a 1 online resource :  |b illustrations (chiefly color). 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Understanding complex systems 
504 |a Includes bibliographical references. 
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. 
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. 
588 0 |a Online resource; title from PDF title page (SpringerLink, viewed May 4, 2022). 
650 0 |a System analysis. 
650 0 |a Simulation methods. 
650 7 |a systems analysis.  |2 aat 
650 7 |a simulation methods.  |2 aat 
650 7 |a Simulation methods  |2 fast 
650 7 |a System analysis  |2 fast 
700 1 |a Battiston, Federico,  |e editor. 
700 1 |a Petri, Giovanni,  |e editor. 
776 0 8 |i Print version:  |z 3030913732  |z 9783030913731  |w (OCoLC)1277276948 
830 0 |a Understanding complex systems. 
856 4 0 |u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-3-030-91374-8  |y Click for online access 
903 |a SPRING-PHYSICS2022 
994 |a 92  |b HCD