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Theory and Applications of Categories
Article . 2020 . Peer-reviewed
Data sources: Crossref
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zbMATH Open
Article . 2020
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https://dx.doi.org/10.48550/ar...
Article . 2017
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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Network Models

Network models
Authors: Baez, John C; Foley, John; Moeller, Joe; Pollard, Blake S;
Abstract

Networks can be combined in various ways, such as overlaying one on top of another or setting two side by side. We introduce "network models" to encode these ways of combining networks. Different network models describe different kinds of networks. We show that each network model gives rise to an operad, whose operations are ways of assembling a network of the given kind from smaller parts. Such operads, and their algebras, can serve as tools for designing networks. Technically, a network model is a lax symmetric monoidal functor from the free symmetric monoidal category on some set to $\mathbf{Cat}$, and the construction of the corresponding operad proceeds via a symmetric monoidal version of the Grothendieck construction.

46 pages

Country
United States
Keywords

Species, Hopf monoids, operads in combinatorics, operad, Network design and communication in computer systems, General Mathematics, monoidal category, Mathematics - Category Theory, graph, Operads (general), Pure Mathematics, Fibered categories, Grothendieck construction, Communication networks in operations research, network, FOS: Mathematics, Monoidal categories, symmetric monoidal categories, Category Theory (math.CT), Categories of networks and processes, compositionality, 18D30, 18M05, 18M35, 18M60, 18M80, 68M10, 90B18

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green
gold