Grassmannians and Gauss maps in piecewise-linear topology
Author(s)
Bibliographic Information
Grassmannians and Gauss maps in piecewise-linear topology
(Lecture notes in mathematics, 1366)
Springer-Verlag, c1989
- : gw
- : us
Available at / 73 libraries
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Library & Science Information Center, Osaka Prefecture University
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Library, Research Institute for Mathematical Sciences, Kyoto University数研
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Kobe University General Library / Library for Intercultural Studies
: U.S410-8-L//1366S061000102798*
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Hokkaido University, Library, Graduate School of Science, Faculty of Science and School of Science図書
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Note
Bibliography: p. 202-203
Description and Table of Contents
Description
The book explores the possibility of extending the notions of "Grassmannian" and "Gauss map" to the PL category. They are distinguished from "classifying space" and "classifying map" which are essentially homotopy-theoretic notions. The analogs of Grassmannian and Gauss map defined incorporate geometric and combinatorial information. Principal applications involve characteristic class theory, smoothing theory, and the existence of immersion satifying certain geometric criteria, e.g. curvature conditions. The book assumes knowledge of basic differential topology and bundle theory, including Hirsch-Gromov-Phillips theory, as well as the analogous theories for the PL category. The work should be of interest to mathematicians concerned with geometric topology, PL and PD aspects of differential geometry and the geometry of polyhedra.
Table of Contents
Local formulae for characteristic classes.- Formal links and the PL grassmannian G n,k.- Some variations of the G n,k construction.- The immersion theorem for subcomplexes of G n,k.- Immersions equivariant with respect to orthogonal actions on Rn+k.- Immersions into triangulated manifolds (with R. Mladineo).- The grassmannian for piecewise smooth immersions.- Some applications to smoothing theory.- Equivariant piecewise differentiable immersions.- Piecewise differentiable immersions into riemannian manifolds.
by "Nielsen BookData"