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Related papers: Average Gromov hyperbolicity and the Parisi ansatz

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Many complex networks exhibit hierarchical, tree-like structures, making hyperbolic space a natural candidate wherein to learn representations of them. Based on this observation, Hyperbolic Graph Neural Networks (HGNNs) have been widely…

Machine Learning · Computer Science 2026-05-15 Dionisia Naddeo , Jonas Linkerhägner , Nicola Toschi , Geri Skenderi , Veronica Lachi

In this paper we prove that the support of a random measure on the unit ball of a separable Hilbert space that satisfies the Ghirlanda-Guerra identities must be ultrametric with probability one. This implies the Parisi ultrametricity…

Probability · Mathematics 2015-03-03 Dmitry Panchenko

For any non-elementary hyperbolic group $\Gamma$, we find an outer automorphism invariant geodesic bicombing for the space of metric structures on $\Gamma$ equipped with a symmetrized version of the Thurston metric on Techim\"uller space.…

Geometric Topology · Mathematics 2025-03-31 Stephen Cantrell , Eduardo Reyes

This is the first article of a series of our recent works, addressing an open question of Bonk-Heinonen-Koskela [5], to study the relationship between (inner) uniformality and Gromov hyperbolicity in infinite dimensional spaces. Our main…

Complex Variables · Mathematics 2026-03-05 Chang-Yu Guo , Manzi Huang , Xiantao Wang

This work considers the problem of computing distances between structured objects such as undirected graphs, seen as probability distributions in a specific metric space. We consider a new transportation distance (i.e. that minimizes a…

Machine Learning · Statistics 2019-05-14 Titouan Vayer , Laetitia Chapel , Rémi Flamary , Romain Tavenard , Nicolas Courty

This paper demonstrates that every ultrametric space is homeomorphic to a clade space of a pruned tree, i.e., a subspace of a tree's canopy. Furthermore, it characterizes several topological properties of ultrametrizable spaces through the…

General Topology · Mathematics 2024-08-01 Itamar Bellaïche

Stable subgroups and the Morse boundary are two systematic approaches to collect and study the hyperbolic aspects of finitely generated groups. In this paper we unify and generalize these strategies by viewing any geodesic metric space as a…

Metric Geometry · Mathematics 2017-06-14 Matthew Cordes , David Hume

WWe define the notion of a random metric space and prove that with probability one such a space is isometricto the Urysohn universal metric space. The main technique is the study of universal and random distance matrices; we relate the…

Representation Theory · Mathematics 2015-06-26 A. M. Vershik

The Gromov--Hausdorff distance (hereinafter referred to as the GH-distance) is a measure of non-isometricity of metric spaces. In this paper, we study a modification of this distance that also takes topological differences into account. The…

Metric Geometry · Mathematics 2025-12-03 Semeon A. Bogaty , Alexey A. Tuzhilin

Hilbert space fragmentation refers to exponential growth in the number of dynamically disconnected Krylov sectors with system size. It is taken as evidence of ergodicity breaking, since conventional symmetries generate at most a polynomial…

High Energy Physics - Lattice · Physics 2026-04-15 Thea Budde , Marina Kristć Marinković , Joao C. Pinto Barros

We prove that any action of a higher rank lattice on a Gromov-hyperbolic space is elementary. More precisely, it is either elliptic or parabolic. This is a large generalization of the fact that any action of a higher rank lattice on a tree…

Geometric Topology · Mathematics 2016-10-27 Thomas Haettel

This work introduces a complexity measure which addresses some conflicting issues between existing ones by using a new principle - measuring the average amount of symmetry broken by an object. It attributes low (although different)…

Statistical Mechanics · Physics 2015-03-26 Roberto C. Alamino

Reeb graphs are a fundamental structure for analyzing the topological and geometric properties of scalar fields. Comparing Reeb graphs is crucial for advancing research in this domain, yet existing metrics are often computationally…

Computational Geometry · Computer Science 2025-07-03 Erin W. Chambers , Guangyu Meng

We investigate conformal dimension for the class of infinite hyperbolic groups in the Gromov density model $\mathcal{G}^d_{m,l}$ of random groups with $m \geq 2$ fixed generators, density $0 < d < 1/2$ and relator length $l \to \infty$. Our…

Group Theory · Mathematics 2022-04-12 Jordan Frost

In this paper we present with algebraic trees a novel notion of (continuum) trees which generalizes countable graph-theoretic trees to (potentially) uncountable structures. For that purpose we focus on the tree structure given by the branch…

Probability · Mathematics 2021-04-29 Wolfgang Löhr , Anita Winter

We introduce a distance in the space of fully-supported probability measures on one-dimensional symbolic spaces. We compare this distance to the $\bar{d}$-distance and we prove that in general they are not comparable. Our projective…

Dynamical Systems · Mathematics 2015-03-04 Liliana Trejo-Valencia , Edgardo Ugalde

We prove the equivalence between a relative bottleneck property and being quasi-isometric to a tree-graded space. As a consequence, we deduce that the quasi-trees of spaces defined axiomatically by Bestvina-Bromberg-Fujiwara are…

Metric Geometry · Mathematics 2017-01-26 David Hume

The rapid advancement of large language models (LLMs) has enabled significant strides in various fields. This paper introduces a novel approach to evaluate the effectiveness of LLM embeddings in the context of inherent geometric properties.…

Computational Geometry · Computer Science 2025-12-29 Prakash Chourasia , Sarwan Ali , Murray Patterson

In the paper we are dealing with metric measure spaces of diameter at most one and of total measure one. Gromov introduced the sampling compactification of the set of these spaces. He asked whether the metric measure space invariants extend…

Metric Geometry · Mathematics 2012-07-24 Gabor Elek

Hyperbolic representations have shown remarkable efficacy in modeling inherent hierarchies and complexities within data structures. Hyperbolic neural networks have been commonly applied for learning such representations from data, but they…

Machine Learning · Computer Science 2024-07-16 Yifei Yang , Wonjun Lee , Dongmian Zou , Gilad Lerman
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