Search arXiv⌕ Search

arXiv · 2610.17909

Geometry and barycenters in large $\CAT(κ)$ spaces

Abstract

We study the geometry and resulting properties of Fréchet functions and barycenters in metric spaces with curvature bounded above by a positive constant in the sense of Alexandrov. Existing results typically rely on the assumption that the support is small enough that the squared distance, and thus the Fréchet function, is strongly geodesically convex. We work in the sharper regime where existence and uniqueness of the barycenter are guaranteed, but where convexity typically fails. We develop new geometric properties of these spaces, including a quantitative four-point inequality and a geodesic stability result. Using these tools, we establish new finite sample error bounds for two statistical estimators: the empirical barycenter and the iterated barycenter, as well as new results on sparse representations and approximations of barycenters.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Yassine Boukhateb, Victor-Emmanuel Brunel, Austin J. Stromme. 2026-10-13. Geometry and barycenters in large $\CAT(κ)$ spaces. https://arxiv.org/abs/2610.17909

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Simultaneous random polytope approximation characterizes the Euclidean ball

In this work, we present a new geometric characterization of the Euclidean ball based on approximation by random polytopes. We investigate when a single boundary sampling density is asymptotically optimal for two random polytope approximation problems, and show that for a convex body in $\R^d$ with $C^2$ boundary and everywhere positive principal curvatures, one fixed density minimizes the leading expected errors for any two distinct intrinsic volume differences of inscribed random polytopes if and only if the body is a Euclidean ball. We show that an analogous characterization holds for the volume and mean width differences of circumscribed random polytopes, and that uniform sampling gives the converse statement in both models. We also determine the unique density minimizing the average of two normalized leading errors, and obtain an explicit positive gap for every nonball. The proofs combine classical random polytope asymptotics, Hölder's inequality, and a curvature rigidity argument based on the Hsiung--Minkowski identities and Newton--Maclaurin inequalities.

math.MG↗

Non-smooth sub-Riemannian manifolds with non-integer dimension and a Poincaré inequality

For every integer $d\geq 3$ and real number $Q\in \left(d,\frac{d(d-1)+2}{2}\right]$, we construct a $Q$-Ahlfors regular metric measure manifold $(M,\mathbf{d},μ)$ of topological dimension $d$ and analytic dimension $2$ that satisfies a Poincaré inequality. For every $Q>\frac{d(d-1)+2}{2}$, the construction yields a metric measure manifold $(M,\mathbf{d},μ)$ that is doubling, satisfies a Poincaré inequality, and for which $M$ has $μ$-essential Hausdorff dimension $Q$. The manifold is $\mathbb{R}^d$ equipped with Lebesgue measure and a sub-Riemannian distance given by vector fields that are locally Hölder continuous but not Lipschitz continuous. These metrics give an uncountable family of new models that are genuinely distinct from the only known families of metric manifolds satisfying a Poincaré inequality: weighted and deformed Carnot groups and smooth sub-Riemannian spaces. The construction is modeled on a singular variant of a filiform Carnot group.

math.MG↗

Excess inertia of finite metric spaces

This paper classifies the possible inertias that are realized by an excess matrix of a finite metric space with at most nine points. For the classification, we make use of relationships between finite metric spaces and non-obtuse and acute sets in classical geometry. As an application, we prove that the small-scale limit of the magnitude function of any six-point metric space is at least one whenever this limit exists.

math.MG↗