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FLAG AREA MEASURES

Part of: General convexity Polytopes and polyhedra

Published online by Cambridge University Press:  23 July 2019

Judit Abardia-Evéquoz ,
Andreas Bernig  and
Susanna Dann
Judit Abardia-Evéquoz
Affiliation:
Institut für Mathematik, Goethe-Universität Frankfurt am Main, Robert-Mayer-Str. 10, 60054 Frankfurt, Germany email [email protected]
Andreas Bernig
Affiliation:
Institut für Mathematik, Goethe-Universität Frankfurt am Main, Robert-Mayer-Str. 10, 60054 Frankfurt, Germany email [email protected]
Susanna Dann
Affiliation:
Departamento de Matemáticas, Universidad de los Andes, Carrera 1 No 18A-12, 111711 Bogotá, Colombia email [email protected]
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Abstract

A flag area measure on an $n$-dimensional euclidean vector space is a continuous translation-invariant valuation with values in the space of signed measures on the flag manifold consisting of a unit vector $v$ and a $(p+1)$-dimensional linear subspace containing $v$ with $0\leqslant p\leqslant n-1$. Using local parallel sets, Hinderer constructed examples of $\text{SO}(n)$-covariant flag area measures. There is an explicit formula for his flag area measures evaluated on polytopes, which involves the squared cosine of the angle between two subspaces. We construct a more general sequence of smooth $\text{SO}(n)$-covariant flag area measures via integration over the normal cycle of appropriate differential forms. We provide an explicit description of our measures on polytopes, which involves an arbitrary elementary symmetric polynomial in the squared cosines of the principal angles between two subspaces. Moreover, we show that these flag area measures span the space of all smooth $\text{SO}(n)$-covariant flag area measures, which gives a classification result in the spirit of Hadwiger’s theorem.

MSC classification

Primary: 52A39: Mixed volumes and related topics
Secondary: 52B45: Dissections and valuations (Hilbert's third problem, etc.)
Type
Research Article
Information
Mathematika , Volume 65 , Issue 4 , 2019 , pp. 958 - 989
Copyright
Copyright © University College London 2019 

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