|This article's factual accuracy is disputed. (April 2009)|
In mathematics — specifically, in Riemannian geometry — geodesic convexity is a natural generalization of convexity for sets and functions to Riemannian manifolds. It is common to drop the prefix "geodesic" and refer simply to "convexity" of a set or function.
Let (M, g) be a Riemannian manifold.
- A subset C of M is said to be a geodesically convex set if, given any two points in C, there is a minimizing geodesic contained within C that joins those two points.
- Let C be a geodesically convex subset of M. A function f : C → R is said to be a (strictly) geodesically convex function if the composition
- is a (strictly) convex function in the usual sense for every unit speed geodesic arc γ : [0, T] → M contained within C.
- A geodesically convex (subset of a) Riemannian manifold is also a convex metric space with respect to the geodesic distance.
- A subset of n-dimensional Euclidean space En with its usual flat metric is geodesically convex if and only if it is convex in the usual sense, and similarly for functions.
- The "northern hemisphere" of the 2-dimensional sphere S2 with its usual metric is geodesically convex. However, the subset A of S2 consisting of those points with latitude further north than 45° south is not geodesically convex, since the geodesic (great circle) joining two points on the southern boundary of A may well leave A (e.g. in the case of two points 180° apart in longitude, in which case the geodesic arc passes over the south pole).
- Rapcsák, Tamás (1997). Smooth nonlinear optimization in Rn. Nonconvex Optimization and its Applications 19. Dordrecht: Kluwer Academic Publishers. pp. xiv+374. ISBN 0-7923-4680-7. MR 1480415
- Udriste, Constantin (1994). Convex functions and optimization methods on Riemannian manifolds. Mathematics and its Applications 297. Dordrecht: Kluwer Academic Publishers. pp. xvi+348. ISBN 0-7923-3002-1.