2019
DOI: 10.1215/00294527-2019-0002
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On n-Dependence

Abstract: In this note we develop and clarify some of the basic combinatorial properties of the new notion of n-dependence (for 1 ≤ n < ω) recently introduced by Shelah [She07]. In the same way as dependence of a theory means its inability to encode a bipartite random graph with a definable edge relation, n-dependence corresponds to the inability to encode a random (n + 1)-partite (n + 1)-hypergraph with a definable edge relation. Most importantly, we characterize n-dependence by counting ϕ-types over finite sets (gener… Show more

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Cited by 20 publications
(47 citation statements)
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“…In Theorem 3.15, we generalize this to simply Ramseyexpandable classes. This partially captures a generalization of the standard collapse-of-indiscernible results found in the literature [2,4,17]. Theorem 3.14.…”
Section: Collapse Of Indiscerniblessupporting
confidence: 63%
See 2 more Smart Citations
“…In Theorem 3.15, we generalize this to simply Ramseyexpandable classes. This partially captures a generalization of the standard collapse-of-indiscernible results found in the literature [2,4,17]. Theorem 3.14.…”
Section: Collapse Of Indiscerniblessupporting
confidence: 63%
“…Though Theorem 3.14 is certainly an interesting result in its own right, it does not match the flavor of collapse-of-indiscernible results discovered thus far (in, say, [2], [4], and [17]). "Natural" dividing-lines typically do not involve linear orders.…”
Section: Collapse Of Indiscerniblesmentioning
confidence: 81%
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“…This shows in particular that T +,P r is unstable. We will recall the definition in the proof of Theorem 3.7, but the interested reader may find more in [Sim15] (about NIP) and [CPT14] (on n-dependence).…”
Section: Decidability and Classificationmentioning
confidence: 99%
“…[42] for an introduction to the area). Basic properties of -dependent theories are investigated in [14]. Roughly speaking, -dependence of a theory guarantees that the edge relation of an infinite generic ( + 1)-hypergraph is not definable in its models (see Definition 2.1).…”
Section: Introductionmentioning
confidence: 99%