2012
DOI: 10.1090/s0002-9947-2012-05626-1
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Generically stable and smooth measures in NIP theories

Abstract: We formulate the measure analogue of generically stable types in first order theories with N IP (without the independence property), giving several characterizations, answering some questions from [9], and giving another treatment of uniqueness results from [9]. We introduce a notion of "generic compact domination", relating it to stationarity of Keisler measures, and also giving group versions. We also prove the "approximate definability" of arbitrary Borel probability measures on definable sets in the real a… Show more

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Cited by 51 publications
(130 citation statements)
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“…The following summarizes the situation, where the reader is referred to Proposition 4.2 of [2] for (i) and Theorem 7.7 of [3] and Theorem 4.3 of [4] for (ii), (iii), and (iv).…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The following summarizes the situation, where the reader is referred to Proposition 4.2 of [2] for (i) and Theorem 7.7 of [3] and Theorem 4.3 of [4] for (ii), (iii), and (iv).…”
Section: Resultsmentioning
confidence: 99%
“…We briefly recall some definitions and properties of Keisler measures, refer-ring the reader to [4] for more details.…”
Section: Introductionmentioning
confidence: 99%
“…For the other direction we will make use of "generic compact domination" from [6], as well as the following result proved in [7] …”
Section: Measure-stable Groupsmentioning
confidence: 99%
“…If µ(x) and λ(y) are both global Aut(M /M 0 )-invariant measures, then so are µ(x) ⊗ λ(y) and λ(y) ⊗ µ(x). Moreover from [5], if at least one of µ(x), λ(y) is generically stable then…”
Section: Preliminariesmentioning
confidence: 99%
“…One direction of the proof of Theorem 1.1 will make heavy use of a special class of generically stable measures, which we call average measures and were introduced in [5]. So we will give the definition again here and record a few facts concerning nonforking products (or amalgams) which will be needed later.…”
Section: Average Measuresmentioning
confidence: 99%