Abstract
In many cases the convexity of the image of a linear map with range is is automatic because of the facial structure of the domain of the map. We develop a four step procedure for proving this kind of "automatic convexity". To make this procedure more efficient, we prove two new theorems that identify the facial structure of the intersection of a convex set with a subspace in terms of the facial structure of the original set. Let K be a convex set in a real linear space X and let H be a subspace of X that meets K. In Part I we show that the faces of the intersection of K and H have the form of intersections of F and H for any face F of K. Then we extend our intersection theorem to the case where X is a locally convex linear topological space, K and H are closed, and H has finite codimension in X. In Part II we use our procedure to "explain" the convexity of the numerical range (and some of its generalizations) of a complex matrix. In Part III we use the topological version of our intersection theorem to prove a version of Lyapunov's theorem with finitely many linear constraints. We also extend Samet's continuous lifting theorem to the same constrained siuation
References
- C. Akemann, J. Anderson: Lyapunov Theorems for Operator Algebras, Memoirs of the Amer. Math. Soc. No. 458, v. 94, Providence, November (1991).https://doi.org/10.1090/memo/0458Google Scholar
- C. Akemann, J. Anderson, N. Weaver: A geometric spectral theory for n-tuples of self-adjoint operators in finite von Neumann algebras, J. Funct. Anal. 165 (1999) 258–292.https://doi.org/10.1006/jfan.1999.3414Google Scholar
- C. Akemann, G. K. Pedersen: Facial structure in operator algebra theory, Proc. London Math. Soc. 64(3) (1992) 418–448.https://doi.org/10.1112/plms/s3-64.2.418Google Scholar
- C. Akemann, G. Shell, N. Weaver: Locally nonconical convexity, J. Convex Analysis 8 (2001) 1–21.https://doi.org/10.68381/jca08004Google Scholar
- C. Berger: Normal Dilations, Ph. D. Dissertation, Cornell (1963).Google Scholar
- K. Gustafson, D. Rao: Numerical Range: The Field of Values of Operators and Matrices, Springer, New York (1997).https://doi.org/10.1007/978-1-4613-8498-4_1Google Scholar
- P. Halmos: On the set of values of a finite measure, Bull. Amer. Math. Soc. 53 (1947) 138–141.https://doi.org/10.1090/S0002-9904-1947-08763-2Google Scholar
- P. Halmos: A Hilbert Space Problem Book, Van Nostrand, New York (1967).Google Scholar
- F. Hausdorff: Das algebraische Analogon zu einem Satz von Fejér, Math. Z. 2 (1918) 187–197.https://doi.org/10.1007/BF01212904Google Scholar
- H. Hermes, J. P. LaSalle: Functional Analysis and Time Optimal Control, Academic Press, New York (1969).Google Scholar
- R. Horn, C. Johnson: Topics in Matrix Analysis, Cambridge University Press, Cambridge (1991).https://doi.org/10.1017/CBO9780511840371Google Scholar
- J. Lindenstrauss: A short proof of Lyapunov’s convexity theorem, J. Math. Mech. 15 (1966) 971–972.https://doi.org/10.1512/iumj.1966.15.15064Google Scholar
- A. Lyapunov: On completely additive vector functions, Bull. Akad. Sci. USSR 4 (1940) 465–478 (Russian).Google Scholar
- Y. Poon: Generalized numerical ranges, joint positive definiteness and multiple eigenvalues, Proc. Amer. Math. Soc. 125(6) (1997) 1625–1634.https://doi.org/10.1090/S0002-9939-97-03781-7Google Scholar
- D. Samet: Continuous selections for vector measures, Math. Oper. Res. 12(3) (1987) 536–543.https://doi.org/10.1287/moor.12.3.536Google Scholar
- O. Toeplitz: Der Wertevorrat einer Bilinearform, Math. Z. 3 (1919) 314–316.https://doi.org/10.1007/BF01292610Google Scholar
- R. Webster: Convexity, Oxford University Press, Oxford (1994).https://doi.org/10.1093/oso/9780198531470.001.0001Google Scholar
Suggested citation
Published by Heldermann Verlag, 2003. Rights now held by Banach Press LLC.
