Log-Euclidean Lie Groups
Olivier Bisson, Xavier Pennec
TL;DR
This work develops a rigorous log-Euclidean Lie group framework for manifolds diffeomorphic to vector spaces, with $\mathcal{S}^+(n)$ and $\mathrm{Cor}^+(n)$ as central examples. It proves that all log-Euclidean metrics on equal-dimension manifolds are isometrically isomorphic and provides explicit isometries between SPD and correlation geometries via the diffeomorphisms $\log$, $\mathrm{Log}$, and $\log^{\bullet}$. A principal-bundle viewpoint yields a quotient geometry where the canonical section yields an orthogonal metric splitting, and the quotient metric aligns with the off-log metric on correlation matrices; however, for $n\ge 3$ no metric pair makes $\mathrm{Cor}^+(n)$ an isometric embedding in $\mathcal{S}^+(n)$. Altogether, the paper unifies disparate log-Euclidean metrics and supplies concrete, structure-preserving maps for geometric statistics on SPD and correlation manifolds.
Abstract
We develop a self-contained comprehensive theory of log-Euclidean Lie groups: smooth manifolds diffeomorphic to finite-dimensional vector spaces; extending existing results for symmetric positive-definite (SPD) matrices S+(n) and full-rank correlation matrices Cor+(n). We specify an isometric isomorphism theorem, showing that all log-Euclidean metrics on manifolds of identical dimension are isomorphically Riemannian isometric. Explicit isometries are constructed, linking SPD and correlation matrix manifolds. We further characterize quotient log-Euclidean metrics within a principal-bundle framework. We show that for any n $\ge$ 3, there is no choice of log-Euclidean metrics on S+(n) and on Cor+(n) for which the inclusion i\,: Cor+(n) $\rightarrow$ S+(n) becomes an isometric embedding. These results unify several disparate metrics in geometric statistics.
