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We introduce the cone of completely-positive functions, a subset of the cone of positive-type functions, and use it to fully characterize maximum-density distance-avoiding sets as the optimal solutions of a convex optimization problem. As a…

Metric Geometry · Mathematics 2023-09-14 Evan DeCorte , Fernando Mário de Oliveira Filho , Frank Vallentin

We study some methods of subgradient projections for solving a convex feasibility problem with general (not necessarily hyperplanes or half-spaces) convex sets in the inconsistent case and propose a strategy that controls the relaxation…

Optimization and Control · Mathematics 2010-09-21 Dan Butnariu , Yair Censor , Pini Gurfil , Ethan Hadar

We define a new structure on a space endowed with convexities, and call it a fractoconvex structure (or, a space with fractoconvexity). We introduce two operations on a set of fractoconvexities and in a special case we show that they…

General Mathematics · Mathematics 2024-08-20 Aidar Dulliev

Similarly to the classic notion in $E^d$, a subset of a positive diameter below $\frac{\pi}{2}$ of a hemisphere of the sphere $S^d$ is called complete, provided adding any extra point increases its diameter. Complete sets are convex bodies…

Metric Geometry · Mathematics 2020-10-08 Marek Lassak

We prove that universal differentiability sets in Euclidean spaces possess distinctive structural properties. Namely, we show that any universal differentiability set contains a `kernel' in which the points of differentiability of each…

Functional Analysis · Mathematics 2016-07-21 Michael Dymond

An orthoset (also called an orthogonality space) is a set $X$ equipped with a symmetric and irreflexive binary relation $\perp$, called the orthogonality relation. In quantum physics, orthosets play a central role. In fact, a Hilbert space…

Rings and Algebras · Mathematics 2021-11-03 Thomas Vetterlein

The equidistant set of two nonempty subsets $K$ and $L$ in the Euclidean plane is a set all of whose points have the same distance from $K$ and $L$. Since the classical conics can be also given in this way, equidistant sets can be…

Metric Geometry · Mathematics 2018-02-13 Csaba Vincze

Some models of set theory are given which contain sets that have some of the important characteristics of being geometric, or spatial, yet do not have any points, in various ways. What's geometrical is that there are functions to these…

Logic · Mathematics 2015-10-06 Robert Lubarsky

We examine properties of equidistant sets determined by nonempty disjoint compact subsets of a compact 2-dimensional Alexandrov space (of curvature bounded below). The work here generalizes many of the known results for equidistant sets…

Metric Geometry · Mathematics 2022-05-20 Logan S. Fox , J. J. P. Veerman

The set of distances of a monoid or of a domain is the set of all $d \in \mathbb N$ with the following property: there are irreducible elements $u_1, \ldots, u_k, v_1, \ldots, v_{k+d}$ such that $u_1 \cdot \ldots \cdot u_k = v_1 \cdot…

Commutative Algebra · Mathematics 2016-04-28 Alfred Geroldinger , Qinghai Zhong

The escaping set of an entire function consists of the points in the complex plane that tend to infinity under iteration. This set plays a central role in the dynamics of transcendental entire functions. The goal of this survey is to…

Dynamical Systems · Mathematics 2025-12-16 Walter Bergweiler , Lasse Rempe

The present work considers the properties of classes of generally convex sets in the plane known as $1$-semiconvex and weakly $1$-semiconvex. More specifically, the examples of open and closed weakly $1$-semiconvex but non $1$-semiconvex…

Metric Geometry · Mathematics 2020-02-11 T. M. Osipchuk

Tree convex sets refer to a collection of sets such that each set in the collection is a subtree of a tree whose nodes are the elements of these sets. They extend the concept of row convex sets each of which is an interval over a total…

Data Structures and Algorithms · Computer Science 2009-06-03 Yuanlin Zhang , Forrest Sheng Bao

A system of three particles undergoing inelastic collisions in arbitrary spatial dimensions is studied with the aim of establishing the domain of ``inelastic collapse''---an infinite number of collisions which take place in a finite time.…

mtrl-th · Physics 2009-10-30 Tong Zhou , Leo Kadanoff

The shapes of flat pebbles may be characterized in terms of the statistical distribution of curvatures measured along their contours. We illustrate this new method for clay pebbles eroded in a controlled laboratory apparatus, and also for…

Soft Condensed Matter · Physics 2007-05-23 D. J. Durian , H. Bideaud , P. Duringer , A. Schroder , C. M. Marques

The structure of the coincidence symmetry group of an arbitrary $n$-dimensional lattice in the $n$-dimensional Euclidean space is considered by describing a set of generators. Particular attention is given to the coincidence isometry…

Group Theory · Mathematics 2007-05-23 Yi Ming Zou

We consider a randomly forced particle moving in a finite region, which rebounds inelastically with coefficient of restitution r on collision with the boundaries. We show that there is a transition at a critical value of r, r_c\equiv…

Statistical Mechanics · Physics 2009-10-31 Stephen J. Cornell , Michael R. Swift , Alan J. Bray

Consider an orientable compact surface in three dimensional Euclidean space with minimum total absolute curvature. If the Gaussian curvature changes sign to finite order and satisfies a nondegeneracy condition along closed asymptotic…

Differential Geometry · Mathematics 2014-01-17 Qing Han , Marcus Khuri

We examine the convective stability of hydrodynamic discs with full stratification in the local approximation and in the presence of thermal diffusion (or relaxation). Various branches of the relevant axisymmetric dispersion relation…

Earth and Planetary Astrophysics · Physics 2016-04-27 Francesco Volponi

We introduce a criterion, resilience, which allows properties of a dataset (such as its mean or best low rank approximation) to be robustly computed, even in the presence of a large fraction of arbitrary additional data. Resilience is a…

Machine Learning · Computer Science 2017-11-28 Jacob Steinhardt , Moses Charikar , Gregory Valiant
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