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.
Definitions
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 unique minimizing geodesic contained within C that joins those two points.
- Let C be a geodesically convex subset of M. A function 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 : → M contained within C.
Properties
- A geodesically convex (subset of a) Riemannian manifold is also a convex metric space with respect to the geodesic distance.
Examples
- A subset of n-dimensional Euclidean space E 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 S with its usual metric is geodesically convex. However, the subset A of S consisting of those points with latitude further north than 45° south is not geodesically convex, since the minimizing geodesic (great circle) arc joining two distinct points on the southern boundary of A leaves A (e.g. in the case of two points 180° apart in longitude, the geodesic arc passes over the south pole).
References
- Rapcsák, Tamás (1997). Smooth nonlinear optimization in R. Nonconvex Optimization and its Applications. Vol. 19. Dordrecht: Kluwer Academic Publishers. ISBN 0-7923-4680-7. MR 1480415.
- Udriste, Constantin (1994). Convex functions and optimization methods on Riemannian manifolds. Mathematics and its Applications. Vol. 297. Dordrecht: Kluwer Academic Publishers. ISBN 0-7923-3002-1.