2006
DOI: 10.4310/sdg.2006.v11.n1.a6
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Semiconcave Functions in Alexandrov’s Geometry

Abstract: Abstract. The following is a compilation of some techniques in Alexandrov's geometry which are directly connected to convexity.

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Cited by 125 publications
(216 citation statements)
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“…Distance functions are also particular cases of the so-called semiconcave functions. Many of the results presented in this section can be deduced from general properties of semiconcave functions [117]. This allows in particular to extend most of the results given in this section to compact subsets of Riemannian manifolds.…”
Section: Bibliographical Notesmentioning
confidence: 87%
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“…Distance functions are also particular cases of the so-called semiconcave functions. Many of the results presented in this section can be deduced from general properties of semiconcave functions [117]. This allows in particular to extend most of the results given in this section to compact subsets of Riemannian manifolds.…”
Section: Bibliographical Notesmentioning
confidence: 87%
“…The notion of critical point introduced in this chapter coincides with the notion of critical point for distance function used in riemannian geometry and non-smooth analysis where the notion of Clarke gradient [57] is closely related to the above defined gradient. The general properties of the gradient of d K and of its trajectories given in Section 9.2, are established in [101] or, in a more general setting, in [117]. Distance functions are also particular cases of the so-called semiconcave functions.…”
Section: Bibliographical Notesmentioning
confidence: 99%
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“…We cannot expect these properties in the lower curvature bound case, the injectivity radius can be 0 even locally. Then it is difficult to control the behavior of discrete-time flows and there are no investigation in this direction as far as the authors know, while continuous-time gradient flows are intensively studied in [37,38,29,35,19].…”
Section: Introductionmentioning
confidence: 99%
“…An Alexandrov space is a metric space whose sectional curvature is bounded above or below by some constant in the sense of triangle comparison theorem (see Section 2). The where g-exp is the gradient exponential map and ∇(−f )(x) denotes the gradient vector of −f (see [37,38] and Sections 3, 4 for these notions). Before discussing the reason why we use these different resolvents, we present our results in this paper.…”
Section: Introductionmentioning
confidence: 99%