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010   $a3-030-91374-0
024 7 $a10.1007/978-3-030-91374-8
035   $a(MiAaPQ)EBC6963490
035   $a(Au-PeEL)EBL6963490
035   $a(CKB)21672598000041
035   $a(PPN)262168081
035   $a(OCoLC)1313480436
035   $a(DE-He213)978-3-030-91374-8
035   $a(EXLCZ)9921672598000041
100   $a20220426d2022      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aHigher-Order Systems /$fedited by Federico Battiston, Giovanni Petri
205   $a1st ed. 2022.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022.
215   $a1 online resource (436 pages)
225 1 $aUnderstanding Complex Systems,$x1860-0840
311 08$aPrint version: Battiston, Federico Higher-Order Systems Cham : Springer International Publishing AG,c2022 9783030913731 
320   $aIncludes bibliographical references.
327   $aHigher-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.
330   $aThe book discusses the potential of higher-order interactions to model real-world relational systems. Over the last decade, networks have emerged as the paradigmatic framework to model complex systems. Yet, as simple collections of nodes and links, they are intrinsically limited to pairwise interactions, limiting our ability to describe, understand, and predict complex phenomena which arise from higher-order interactions. Here we introduce the new modeling framework of higher-order systems, where hypergraphs and simplicial complexes are used to describe complex patterns of interactions among any number of agents. This book is intended both as a first introduction and an overview of the state of the art of this rapidly emerging field, serving as a reference for network scientists interested in better modeling the interconnected world we live in.
410  0$aUnderstanding Complex Systems,$x1860-0840
606   $aSystem theory
606   $aMathematical physics
606   $aBiophysics
606   $aSocial sciences$xNetwork analysis
606   $aComplex Systems
606   $aTheoretical, Mathematical and Computational Physics
606   $aBiophysics
606   $aMathematical Methods in Physics
606   $aNetwork Research
615  0$aSystem theory.
615  0$aMathematical physics.
615  0$aBiophysics.
615  0$aSocial sciences$xNetwork analysis.
615 14$aComplex Systems.
615 24$aTheoretical, Mathematical and Computational Physics.
615 24$aBiophysics.
615 24$aMathematical Methods in Physics.
615 24$aNetwork Research.
676   $a001.434
676   $a003
702   $aBattiston$b Federico
702   $aPetri$b Giovanni
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910568289503321
996   $aHigher-order systems$92965881
997   $aUNINA