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Many geometric optimization problems can be reduced to finding points in space (centers) minimizing an objective function which continuously depends on the distances from the centers to given input points. Examples are $k$-Means, Geometric…

Computational Geometry · Computer Science 2021-08-26 Vladimir Shenmaier

The main goal of this note is to develop a metrical theory of Diophantine approximation within the framework of the de Mathan-Teulie Conjecture, also known as the `Mixed Littlewood Conjecture'. Let p be a prime. A consequence of our main…

Number Theory · Mathematics 2010-05-12 Yann Bugeaud , Alan Haynes , Sanju Velani

Let $M$ be a pinched negatively curved Riemannian manifold, whose unit tangent bundle is endowed with a Gibbs measure $m_F$ associated to a potential $F$. We compute the Hausdorff dimension of the conditional measures of $m_F$. We study the…

Dynamical Systems · Mathematics 2014-05-12 Frédéric Paulin , Mark Pollicott

In the setting of a metric space equipped with a doubling measure that supports a Poincar\'e inequality, we show that any set of finite perimeter can be approximated in the BV norm by a set whose topological and measure theoretic boundaries…

Metric Geometry · Mathematics 2016-11-21 Panu Lahti

Following Schmidt, Thurnheer and Bugeaud-Kristensen, we study how Dirichlet's theorem on linear forms needs to be modified when one requires that the vectors of coefficients of the linear forms make a bounded acute angle with respect to a…

Number Theory · Mathematics 2022-12-09 Jérémy Champagne , Damien Roy

We observe that embeddings into random metrics can be fruitfully used to study the $L_1$-embeddability of lamplighter graphs or groups, and more generally lamplighter metric spaces. Once this connection has been established, several new…

Metric Geometry · Mathematics 2020-05-26 Florent P. Baudier , Pavlos Motakis , Thomas Schlumprecht , András Zsák

The paper is devoted to a categorical study of the category of probabilistic metric spaces. The study is based on an isomorphic description of the category of probabilistic metric spaces. The isomorphic description was obtained in [3] and…

General Topology · Mathematics 2026-04-02 Eva Colebunders , Robert Lowen

The simulation of physical phenomena with computer models relies on the estimation of physical and/or numerical parameters calibrated to fit experimental data. The approximations within the computer model and the errors in the measurements…

Methodology · Statistics 2026-05-12 Paul Lartaud , Gwenaël Salin

We study the subsets of metric spaces that are negligible for the infimal length of connecting curves; such sets are called metrically removable. In particular, we show that every totally disconnected set with finite Hausdorff measure of…

Complex Variables · Mathematics 2021-08-10 Sergei Kalmykov , Leonid V. Kovalev , Tapio Rajala

We study the size of \emph{dynamical covering sets} on a self-similar set. Dynamical covering sets are limsup sets generated by placing shrinking target sets around points along an orbit in a dynamical system. In the case when the target…

Dynamical Systems · Mathematics 2025-06-24 Balazs Barany , Henna Koivusalo , Sascha Troscheit

We determine the complete space-time metric from the bootstrapped Newtonian potential generated by a static spherically symmetric source in the surrounding vacuum. This metric contains post-Newtonian parameters which can be further used to…

General Relativity and Quantum Cosmology · Physics 2021-03-10 Roberto Casadio , Andrea Giusti , Iberê Kuntz , Giulio Neri

We consider the question of how well points in a quadric hypersurface $M\subset\mathbb R^d$ can be approximated by rational points of $\mathbb Q^d\cap M$. This contrasts with the more common setup of approximating points in a manifold by…

Number Theory · Mathematics 2021-01-14 Lior Fishman , Dmitry Kleinbock , Keith Merrill , David Simmons

This paper deals with the Gaussian and bootstrap approximations to the distribution of the max statistic in high dimensions. This statistic takes the form of the maximum over components of the sum of independent random vectors and its…

Statistics Theory · Mathematics 2022-05-31 Victor Chernozhukov , Denis Chetverikov , Kengo Kato , Yuta Koike

We obtain a criterion for an analytic subset of a Euclidean space to contain points of differentiability of a typical Lipschitz function, namely, that it cannot be covered by countably many sets, each of which is closed and purely…

Functional Analysis · Mathematics 2020-11-11 Michael Dymond , Olga Maleva

We construct bi-Lipschitz embeddings into Euclidean space for manifolds and orbifolds of bounded diameter and curvature. The distortion and dimension of such embeddings is bounded by diameter, curvature and dimension alone. Our results also…

Metric Geometry · Mathematics 2018-04-18 Sylvester Eriksson-Bique

Using lattice approximations of Euclidean space, we develop a way to approximate stable processes that are represented by stochastic integrals over Euclidean space. Via a stable version of the Lindeberg-Feller Theorem we show that the…

Probability · Mathematics 2013-02-19 Clément Dombry , Paul Jung

The overall aim of this note is to initiate a "manifold" theory for metric Diophantine approximation on the limit sets of Kleinian groups. We investigate the notions of singular and extremal limit points within the geometrically finite…

Number Theory · Mathematics 2018-04-03 Victor Beresnevich , Anish Ghosh , David Simmons , Sanju Velani

As a continuation of \cite{NSY:local}, we mainly discuss the global structure of two-dimensional locally compact geodesically complete metric spaces with curvature bounded above. We first obtain the result on the Lipschitz homotopy…

Metric Geometry · Mathematics 2023-09-01 Koichi Nagano , Takashi Shioya , Takao Yamaguchi

Thanks to recent advances in parametric geometry of numbers, we know that the spectrum of any set of $m$ exponents of Diophantine approximation to points in $\mathbb{R}^n$ (in a general abstract setting) is a compact connected subset of…

Number Theory · Mathematics 2022-02-02 Martin Rivard-Cooke , Damien Roy

We devise a new embedding technique, which we call measured descent, based on decomposing a metric space locally, at varying speeds, according to the density of some probability measure. This provides a refined and unified framework for the…

Data Structures and Algorithms · Computer Science 2007-05-23 Robert Krauthgamer , James R. Lee , Manor Mendel , Assaf Naor