Warped geometries of Segre-Veronese manifolds
Simon Jacobsson, Lars Swijsen, Joeri Van der Veken, Nick Vannieuwenhoven
TL;DR
This work develops and analyzes alpha-warped geometries for Segre--Veronese manifolds, providing closed-form exponential and logarithmic maps and explicit intrinsic distances that enable efficient Riemannian computations on partially symmetric rank-1 tensors. By showing that a normal Riemannian covering relates the Segre--Veronese manifold to a warped pre-Segre--Veronese product, the authors derive practical geodesic formulas, compatibility criteria, and a linear-time matching algorithm to obtain geodesics between rank-1 tensors. They establish geodesic connectivity criteria dependent on the warping parameter $\alpha$, compute sectional curvatures, and illustrate a concrete application to Fréchet means for tensor averaging. The numerical experiments, implemented in Julia and integrated with Manifolds.jl, demonstrate robust intrinsic averaging and efficient computation, highlighting the practical impact for tensor decomposition and aggregation tasks in high-dimensional data.
Abstract
Segre-Veronese manifolds are smooth submanifolds of tensors comprising the partially symmetric rank-1 tensors. We investigate a one-parameter family of warped geometries of Segre-Veronese manifolds, which includes the standard Euclidean geometry. This parameter controls by how much spherical tangent directions are weighted relative to radial tangent directions. We present closed expressions for the exponential map, the logarithmic map, and the intrinsic distance on these warped Segre-Veronese manifolds, which can be computed efficiently numerically. It is shown that Segre-Veronese manifolds are not geodesically connected in the Euclidean geometry, while they are for some values of the warping parameter. The benefits of geodesics connectedness may outweigh using the Euclidean geometry in certain applications. One such application is presented: numerically computing the Riemannian center of mass for averaging rank-1 tensors.
