We prove a hyperplane separation theorem for disjoint and convex sets in two-dimensional Hadamard manifolds. Furthermore, in higher dimensions we prove such a theorem if additionally the two involved sets are closed. This extends a recent generalization of J. Shenawy [Horosphere slab separation theorems in manifolds without conjugate points, J. Egyptian Math. Soc. 27 (2019)] and R. Bergmann et al. [Fenchel duality and a separation theorem on Hadamard manifolds, SIAM J. Optimization (2022)] of the hyperplane separation theorem in Euclidean space to Hadamard manifolds at which one of the disjoint sets is assumed to be convex and compact and the other convex and closed; the proof relies on results of these references. Note that generalizations of the hyperplane separation theorem from Euclidean space to topological vector spaces are the classical and well-known Hahn-Banach separation theorems.

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  1. W. Ballmann, M. Gromov, V. Schroeder: Manifolds of Nonpositive Curvature, Progress in Mathematics 61, Birkhäuser, Boston (1985).https://doi.org/10.1007/978-1-4684-9159-3Google Scholar
  2. M. Bačák: Convex Analysis and Optimization in Hadamard Spaces, De Gruyter Series in Nonlinear Analysis and Applications 22, De Gruyter, Berlin (2014).Google Scholar
  3. R. Bergmann, R. Herzog, M. S. Louzeiro: Fenchel duality and a separation theorem on Hadamard manifolds, SIAM J. Optimization (2022), to appear.https://doi.org/10.1137/21M1400699Google Scholar
  4. R. Bergmann, R. Herzog, M. S. Louzeiro, D. Tenbrinck J. Vidal-Núñez: Fenchel duality theory and a primal-dual algorithm on Riemannian manifolds, Found. Comput. Math. 21/6 (2021) 1465–1504.https://doi.org/10.1007/s10208-020-09486-5Google Scholar
  5. R. Bergmann, J. Persch, G. Steidl: A parallel Douglas-Rachford algorithm for minimizing ROF-like functionals on images with values in symmetric Hadamard manifolds, SIAM J. Imaging Sci. 9/3 (2016) 901–937.https://doi.org/10.1137/15M1052858Google Scholar
  6. S. Boyd, L. Vandenberghe: Convex Optimization, Cambridge University Press, Cambridge (2004).https://doi.org/10.1017/CBO9780511804441Google Scholar
  7. O. P. Ferreira, P. R. Oliveira: Proximal point algorithm on Riemannian manifolds, Optimization 51/2 (2002) 257–270.https://doi.org/10.1080/02331930290019413Google Scholar
  8. J. M. Lee: Introduction to Riemannian Manifolds, 2nd ed., Graduate Texts in Mathematics 176, Springer, Cham (2018).https://doi.org/10.1007/978-3-319-91755-9Google Scholar
  9. P. Petersen: Riemannian Geometry, 3rd ed., Graduate Texts in Mathematics 171, Springer, Cham (2016).https://doi.org/10.1007/978-3-319-26654-1Google Scholar
  10. W. Rudin: Functional Analysis, McGraw-Hill Series in Higher Mathematics, McGraw-Hill, New York (1973).Google Scholar
  11. S. Shenawy: Horosphere slab separation theorems in manifolds without conjugate points, J. Egyptian Math. Soc. 27/1 (2019), art. no. 35.https://doi.org/10.1186/s42787-019-0038-5Google Scholar
  12. L.-w. Zhou, Y.-b. Xiao, and N.-j. Huang: New characterization of geodesic convexity on Hadamard manifolds with applications, J. Optimization Theory Appl. 172/3 (2017) 824–844.https://doi.org/10.1007/s10957-016-1012-0Google Scholar

A. Kröner, H. Kröner. “Hyperplane Separation Type Theorems in Hadamard Manifolds.” Journal of Convex Analysis 29 (2022), No. 2, 519–529. https://doi.org/10.68381/jca29030