Maximizing expected powers of the angle between pairs of points in projective space
Tongseok Lim, Robert J. McCann

TL;DR
This paper investigates probability measures on real projective space that maximize the expected angle between points, verifying a conjecture for certain exponents and establishing uniqueness and stability properties of these measures.
Contribution
It verifies a milder version of a conjecture about maximizing expected angles in projective space for a range of exponents and proves uniqueness and local optimality of the maximizers.
Findings
Confirmed the conjecture for ppa > lpha_{\u2206^d} and established measure uniqueness.
Showed the measure no longer maximizes when lpha < lpha_{\u2206^d}.
Proved local maximality in the Kantorovich-Rubinstein-Wasserstein metric for lpha > 1.
Abstract
Among probability measures on -dimensional real projective space, one which maximizes the expected angle between independently drawn projective points and was conjectured to equidistribute its mass over the standard Euclidean basis by Fejes T\'oth \cite{FT59}. If true, this conjecture evidently implies the same measure maximizes the expectation of for any exponent . The kernel represents the objective of an infinite-dimensional quadratic program. We verify discrete and continuous versions of this {milder} conjecture in a non-empty range , and establish uniqueness of the resulting maximizer up to rotation. We show no longer maximizes when…
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Taxonomy
TopicsComputational Geometry and Mesh Generation · Point processes and geometric inequalities · Mathematical Approximation and Integration
