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We study the complexity of geometric problems on spaces of low fractal dimension. It was recently shown by [Sidiropoulos & Sridhar, SoCG 2017] that several problems admit improved solutions when the input is a pointset in Euclidean space…

Computational Complexity · Computer Science 2017-12-14 Anastasios Sidiropoulos , Kritika Singhal , Vijay Sridhar

We study density thresholds that force a measurable set $E\subseteq\mathbb{R}^d$ to contain all sufficiently large similar copies of every $n$-point configuration. We prove a lower bound of the form $1-O((\log n)/n)$, which matches the…

Classical Analysis and ODEs · Mathematics 2026-04-21 Vjekoslav Kovač , Adian Anibal Santos Sepčić

Oblivious low-distortion subspace embeddings are a crucial building block for numerical linear algebra problems. We show for any real $p, 1 \leq p < \infty$, given a matrix $M \in \mathbb{R}^{n \times d}$ with $n \gg d$, with constant…

Data Structures and Algorithms · Computer Science 2014-03-19 David P. Woodruff , Qin Zhang

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

A classical theorem of Macbeath states that for any integers $d \geq 2$, $n \geq d+1$, $d$-dimensional Euclidean balls are hardest to approximate, in terms of volume difference, by inscribed convex polytopes with $n$ vertices. In this paper…

Metric Geometry · Mathematics 2025-12-30 Z. Lángi , S. Wang

Erd\"{o}s proved that for every infinite $X \subseteq \mathbb{R}^d$ there is $Y \subseteq X$ with $|Y|=|X|$, such that all pairs of points from $Y$ have distinct distances, and he gave partial results for general $a$-ary volume. In this…

Logic · Mathematics 2018-07-19 William Gasarch , Douglas Ulrich

There is a constant c > 0 such that for every $\epsilon \in (0,1)$ and $n \geq 1/\epsilon^2$, the following holds. Any mapping from the $n$-point star metric into $\ell_1^d$ with bi-Lipschitz distortion $1+\epsilon$ requires dimension $$d…

Metric Geometry · Mathematics 2013-02-28 James R. Lee , Mohammad Moharrami

We study open point sets in Euclidean spaces $\mathbb{R}^d$ without a pair of points an integral distance apart. By a result of Furstenberg, Katznelson, and Weiss such sets must be of Lebesgue upper density zero. We are interested in how…

Metric Geometry · Mathematics 2015-03-20 Sascha Kurz , Valery Mishkin

Let $\Delta_n$ and $Q_n$ denote the regular $n$-simplex of side length $\sqrt{2}$ embedded in $\mathbb{R}^{n+1}$ and the volume one cube in $\mathbb{R}^n$, respectively. We derive a closed-form formula for the hyperplane volume projections…

Metric Geometry · Mathematics 2026-01-27 Christos Pandis

Consider a set $P$ of $n$ points in $\mathbb{R}^d$. In the discrete median line segment problem, the objective is to find a line segment bounded by a pair of points in $P$ such that the sum of the Euclidean distances from $P$ to the line…

Computational Geometry · Computer Science 2022-02-16 Ovidiu Daescu , Ka Yaw Teo

We show that for every $\alpha > 0$, there exist $n$-point metric spaces (X,d) where every "scale" admits a Euclidean embedding with distortion at most $\alpha$, but the whole space requires distortion at least $\Omega(\sqrt{\alpha \log…

Metric Geometry · Mathematics 2015-05-14 Alexander Jaffe , James R. Lee , Mohammad Moharrami

The commonly used spatial entropy $h_{r}(\mathcal{U})$ of the multi-dimensional shift space $\mathcal{U}$ is the limit of growth rate of admissible local patterns on finite rectangular sublattices which expands to whole space…

Dynamical Systems · Mathematics 2014-12-23 Wen-Guei Hu , Song-Sun Lin

Weil-Petersson volumes are the volumes of the moduli spaces of bordered Riemann surfaces and have played an important role in the relationship between two-dimensional quantum gravity and algebraic geometry. In the last couple years progress…

High Energy Physics - Theory · Physics 2024-07-24 Ashton Lowenstein

The main goal of this paper is to develop a new embedding method which we use to show that some finite metric spaces admit low-distortion embeddings into all non-superreflexive spaces. This method is based on the theory of…

Functional Analysis · Mathematics 2018-11-13 Mikhail I. Ostrovskii , Beata Randrianantoanina

Suppose that a metric space $X$ is the union of two metric subspaces $A$ and $B$ that embed into Euclidean space with distortions $D_A$ and $D_B$, respectively. We prove that then $X$ embeds into Euclidean space with a bounded distortion…

Metric Geometry · Mathematics 2017-01-25 Konstantin Makarychev , Yury Makarychev

We give a dimensionality reduction procedure to approximate the sum of distances of a given set of $n$ points in $R^d$ to any "shape" that lies in a $k$-dimensional subspace. Here, by "shape" we mean any set of points in $R^d$. Our…

Data Structures and Algorithms · Computer Science 2021-06-25 Zhili Feng , Praneeth Kacham , David P. Woodruff

We extend the Theory of Computation on real numbers, continuous real functions, and bounded closed Euclidean subsets, to compact metric spaces $(X,d)$: thereby generically including computational and optimization problems over higher types,…

Logic in Computer Science · Computer Science 2017-03-28 Chansu Park , Ji-Won Park , Sewon Park , Dongseong Seon , Martin Ziegler

Gr\"unbaum's inequality guarantees that the centroid of a convex body has halfspace depth at least $1/e$: every halfspace containing the centroid captures at least a $1/e$ fraction of the body's volume. For mixed-integer convex sets…

Optimization and Control · Mathematics 2026-03-03 Hongyu Cheng , Amitabh Basu

Dimensional regularization of Euclidean momentum space integrals is a highly successful technique in renormalization of quantum field theories. While it yields a straightforward algorithmic method, with which to evaluate diagrams beyond…

Mathematical Physics · Physics 2020-09-03 Juuso Österman

The embedding of finite metrics in $\ell_1$ has become a fundamental tool for both combinatorial optimization and large-scale data analysis. One important application is to network flow problems in which there is close relation between…

Metric Geometry · Mathematics 2014-04-21 David Bryant , Paul F. Tupper