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Iterative methods with certified convergence for the computation of Gauss--Jacobi quadratures are described. The methods do not require a priori estimations of the nodes to guarantee its fourth-order convergence. They are shown to be…

Numerical Analysis · Mathematics 2020-08-24 A. Gil , J. Segura , N. M. Temme

We prove that the combinatorial optimization problem of determining the hull number of a partial cube is NP-complete. This makes partial cubes the minimal graph class for which NP-completeness of this problem is known and improves some…

Combinatorics · Mathematics 2015-10-09 Marie Albenque , Kolja Knauer

Huffman coding finds a prefix code that minimizes mean codeword length for a given probability distribution over a finite number of items. Campbell generalized the Huffman problem to a family of problems in which the goal is to minimize not…

Information Theory · Computer Science 2007-07-16 Michael B. Baer

A generic method for combinatorial constructions of intrinsic geometrical spaces is presented. It is based on the well known inverse sequences of finite graphs that determine (in the limit) topological spaces. If a pattern of the…

Computational Geometry · Computer Science 2020-10-09 Stanislaw Ambroszkiewicz

This paper studies projections of uniform random elements of (co)adjoint orbits of compact Lie groups. Such projections generalize several widely studied ensembles in random matrix theory, including the randomized Horn's problem, the…

Mathematical Physics · Physics 2023-10-25 Benoît Collins , Colin McSwiggen

We define discrete constant mean curvature (cmc) surfaces in the three-dimensional Euclidean and Lorentz spaces in terms of sphere packings with orthogonally intersecting circles. These discrete cmc surfaces can be constructed from…

Differential Geometry · Mathematics 2024-10-14 Alexander I. Bobenko , Tim Hoffmann , Nina Smeenk

This paper focuses on the approximation of continuous functions on the unit sphere by spherical polynomials of degree $n$ via hyperinterpolation. Hyperinterpolation of degree $n$ is a discrete approximation of the $L^2$-orthogonal…

Numerical Analysis · Mathematics 2022-10-05 Congpei An , Hao-Ning Wu

In this paper we study the geometric discrepancy of explicit constructions of uniformly distributed points on the two-dimensional unit sphere. We show that the spherical cap discrepancy of random point sets, of spherical digital nets and of…

Numerical Analysis · Mathematics 2014-02-17 Christoph Aistleitner , Johann Brauchart , Josef Dick

Based on earlier work by Carlen-Maas and the second- and third-named author, we introduce the notion of intertwining curvature lower bounds for graphs and quantum Markov semigroups. This curvature notion is stronger than both Bakry-\'Emery…

Functional Analysis · Mathematics 2024-01-11 Florentin Münch , Melchior Wirth , Haonan Zhang

We present a general construction of embedded minimal and constant mean curvature surfaces in $\mathbb{S}^n$ and one-phase free boundaries joined by a smooth interpolation by capillary hypersurfaces. This framework recovers all known…

Differential Geometry · Mathematics 2026-04-07 Benjy Firester , Raphael Tsiamis

We introduce a minor variant of the approximate D-optimal design of experiments with a more general information matrix that takes into account the representation of the design space S. The main motivation (and result) is that if S in R^d is…

Optimization and Control · Mathematics 2025-05-15 Didier Henrion , Jean Bernard Lasserre

A set-system $S\subseteq \{0,1\}^n$ is cube-ideal if its convex hull can be described by capacity and generalized set covering inequalities. In this paper, we use combinatorics, convex geometry, and polyhedral theory to give exponential…

Combinatorics · Mathematics 2026-04-21 Ahmad Abdi , Gérard Cornuéjols , Daniel Dadush , Mahsa Dalirrooyfard

An approach to gauge theory in the context of locally conformally flat space-time is described. It is discussed how there are a number of natural principal bundles associated with any given locally conformally flat space-time $X$. The…

Mathematical Physics · Physics 2025-06-25 John Mashford

Product measures of dimension $n$ are known to be concentrated in Hamming distance: for any set $S$ in the product space of probability $\epsilon$, a random point in the space, with probability $1-\delta$, has a neighbor in $S$ that is…

Data Structures and Algorithms · Computer Science 2019-07-12 Omid Etesami , Saeed Mahloujifar , Mohammad Mahmoody

In this paper, we study a natural discretization of the smooth Gaussian curvature on surfaces. A discrete uniformization theorem is established for this discrete Gaussian curvature. We further investigate the prescribing combinatorial…

Differential Geometry · Mathematics 2024-01-11 Xu Xu , Chao Zheng

For a $d$-dimensional random vector $X$, let $p_{n, X}(\theta)$ be the probability that the convex hull of $n$ independent copies of $X$ contains a given point $\theta$. We provide several sharp inequalities regarding $p_{n, X}(\theta)$ and…

Probability · Mathematics 2023-01-11 Satoshi Hayakawa , Terry Lyons , Harald Oberhauser

Let $(X,d)$ be a compact metric space. We consider the behavior of probability measures $\mu$ with the property that $$ \int_{X} d(x, y) d\mu(y) \qquad \mbox{is independent of}~x \in X.$$ It appears that such measures, when they exist,…

Metric Geometry · Mathematics 2026-02-24 Stefan Steinerberger

We study Hilbert functions of certain non-reduced schemes A supported at finite sets of points in projective space, in particular, fat point schemes. We give combinatorially defined upper and lower bounds for the Hilbert function of A using…

Algebraic Geometry · Mathematics 2010-12-14 Susan Cooper , Brian Harbourne , Zach Teitler

We investigate the implementation of a new stochastic Kuramoto-Vicsek-type model for global optimization of nonconvex functions on the sphere. This model belongs to the class of Consensus-Based Optimization. In fact, particles move on the…

Machine Learning · Computer Science 2021-07-29 Massimo Fornasier , Hui Huang , Lorenzo Pareschi , Philippe Sünnen

The successful development and optimisation of optically-driven micromachines will be greatly enhanced by the ability to computationally model the optical forces and torques applied to such devices. In principle, this can be done by…