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The assumptions that "light propagates along null geodesics of the spacetime metric" and "the number of photons is conserved along the light path" lead to the distance duality relation (DDR), $\eta = D_L(z) (1 + z)^{-2}/D_A(z) = 1$, with…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-05 Vincenzo F. Cardone , Susanna Spiro , Isobel Hook , Roberto Scaramella

In the work by M. C. Lee, A. Naber, and R. Neumayer a beautiful $\varepsilon$-regularity theorem is proved under small negative scalar curvature and entropy bounds. In that paper, the $d_p$ distance for Riemannian manifolds is introduced…

Differential Geometry · Mathematics 2024-06-25 Brian Allen , Edward Bryden

All parallel algorithms for directed reachability and shortest paths crucially rely on efficient shortcut constructions. These constructions find directed paths and shortcut them by adding edges, with the goal to reduce the diameter of the…

Data Structures and Algorithms · Computer Science 2026-05-06 Bernhard Haeupler , Antti Roeyskoe , Zhijun Zhang

A set N is called a "weak epsilon-net" (with respect to convex sets) for a finite set X in R^d if N intersects every convex set that contains at least epsilon*|X| points of X. For every fixed d>=2 and every r>=1 we construct sets X in R^d…

Combinatorics · Mathematics 2013-03-25 Boris Bukh , Jiří Matoušek , Gabriel Nivasch

The Johnson-Lindenstrauss transform is a fundamental method for dimension reduction in Euclidean spaces, that can map any dataset of $n$ points into dimension $O(\log n)$ with low distortion of their distances. This dimension bound is tight…

Data Structures and Algorithms · Computer Science 2026-02-20 Shaofeng H. -C. Jiang , Robert Krauthgamer , Shay Sapir , Sandeep Silwal , Di Yue

We construct quasiconformal mappings in Euclidean spaces by integration of a discontinuous kernel against doubling measures with suitable decay. The differentials of mappings that arise in this way satisfy an isotropic form of the doubling…

Classical Analysis and ODEs · Mathematics 2007-09-03 Leonid V. Kovalev , Diego Maldonado , Jang-Mei Wu

We study the family of vertical projections whose fibers are right cosets of horizontal planes in the Heisenberg group, $\mathbb{H}^n$. We prove lower bounds for Hausdorff dimension distortion of sets under these mappings, with respect to…

Metric Geometry · Mathematics 2022-10-11 Terence L. J. Harris , Chi N. Y. Huynh , Fernando Roman-Garcia

Recently, the first author together with Jens Marklof studied generalizations of the classical three distance theorem to higher dimensional toral rotations, giving upper bounds in all dimensions for the corresponding numbers of distances…

Number Theory · Mathematics 2020-12-08 Alan Haynes , Juan J. Ramirez

The Gromov-Hausdorff distance $(d_{GH})$ proves to be a useful distance measure between shapes. In order to approximate $d_{GH}$ for compact subsets $X,Y\subset\mathbb{R}^d$, we look into its relationship with $d_{H,iso}$, the infimum…

Metric Geometry · Mathematics 2024-05-28 Sushovan Majhi , Jeffrey Vitter , Carola Wenk

We generalize upper bounds for constant dimension codes containing a lifted maximum rank distance code first studied by Etzion and Silberstein. The proof allows to construct several improved codes.

Combinatorics · Mathematics 2018-01-16 Daniel Heinlein

Spanners for low dimensional spaces (e.g. Euclidean space of constant dimension, or doubling metrics) are well understood. This lies in contrast to the situation in high dimensional spaces, where except for the work of Har-Peled, Indyk and…

Data Structures and Algorithms · Computer Science 2018-04-23 Arnold Filtser , Ofer Neiman

Sliced Wasserstein distances preserve properties of classic Wasserstein distances while being more scalable for computation and estimation in high dimensions. The goal of this work is to quantify this scalability from three key aspects: (i)…

Machine Learning · Statistics 2022-10-18 Sloan Nietert , Ritwik Sadhu , Ziv Goldfeld , Kengo Kato

In 1984, Johnson and Lindenstrauss proved that any finite set of data in a high-dimensional space can be projected to a lower-dimensional space while preserving the pairwise Euclidean distance between points up to a bounded relative error.…

Discrete Mathematics · Computer Science 2018-03-15 Michael Burr , Shuhong Gao , Fiona Knoll

We generalized to higher dimensions the notions of optical orthogonal codes. We establish uper bounds on the capacity of general $ n $-dimensional OOCs, and on specific types of ideal codes (codes with zero off-peak autocorrelation). The…

Combinatorics · Mathematics 2022-07-18 Tim Alderson

We study a finite-field analogue of the Erd\H{o}s distinct distances problem under the Hamming metric. For a set \(S\subseteq \mathbb{F}_q^n\) let $\Delta(S)$ denote the set of Hamming distances determined by \(S\). We prove the lower bound…

Combinatorics · Mathematics 2025-10-14 Nataly Brukhim , Ariel Bruner , Orit E. Raz

The construction of $r$-nets offers a powerful tool in computational and metric geometry. We focus on high-dimensional spaces and present a new randomized algorithm which efficiently computes approximate $r$-nets with respect to Euclidean…

Computational Geometry · Computer Science 2017-05-09 Georgia Avarikioti , Ioannis Z. Emiris , Loukas Kavouras , Ioannis Psarros

In the first paper of this series [S. Torquato, J. Chem. Phys. {\bf 136}, 054106 (2012)], analytical results concerning the continuum percolation of overlapping hyperparticles in $d$-dimensional Euclidean space $\mathbb{R}^d$ were obtained,…

Statistical Mechanics · Physics 2012-08-21 Salvatore Torquato , Yang Jiao

Quantum correlations described by quantum discord and one-way quantum deficit can contain ordinary regions with {\em constant} (i.e., universal) optimal measurement angle $0$ or $\pi/2$ with respect to the $z$-axis and regions with a {\em…

Quantum Physics · Physics 2019-04-05 Ekaterina V. Moreva , Marco Gramegna , Mikhail A. Yurischev

Discrepancy measures how uniformly distributed a point set is with respect to a given set of ranges. There are two notions of discrepancy, namely continuous discrepancy and combinatorial discrepancy. Depending on the ranges, several…

Computational Geometry · Computer Science 2011-03-24 Panos Giannopoulos , Christian Knauer , Magnus Wahlström , Daniel Werner

The Euclidean distance geometry problem arises in a wide variety of applications, from determining molecular conformations in computational chemistry to localization in sensor networks. When the distance information is incomplete, the…

Information Theory · Computer Science 2018-10-30 Abiy Tasissa , Rongjie Lai