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Let $\{f_j\}_{j=0}^n$ be a sequence of orthonormal polynomials where the orthogonality relation is satisfied on either the real line or on the unit circle. We study zero distribution of random linear combinations of the form…

Classical Analysis and ODEs · Mathematics 2018-02-12 Aaron Yeager

Random union sets $Z$ associated with stationary Poisson processes of $k$-cylinders in $\mathbb{R}^d$ are considered. Under general conditions on the typical cylinder base a concentration inequality for the volume of $Z$ restricted to a…

Probability · Mathematics 2019-08-07 Anastas Baci , Carina Betken , Anna Gusakova , Christoph Thaele

We construct a quasi-polynomial time deterministic approximation algorithm for computing the volume of an independent set polytope with restrictions. Randomized polynomial time approximation algorithms for computing the volume of a convex…

Data Structures and Algorithms · Computer Science 2023-12-08 David Gamarnik , Devin Smedira

We investigate the combinatorics and geometry of permutation polytopes associated to cyclic permutation groups, i.e., the convex hulls of cyclic groups of permutation matrices. We give formulas for their dimension and vertex degree. In the…

Combinatorics · Mathematics 2011-09-02 Barbara Baumeister , Christian Haase , Benjamin Nill , Andreas Paffenholz

The convex hull of the roots of a classical root lattice is called a root polytope. We determine explicit unimodular triangulations of the boundaries of the root polytopes associated to the root lattices A_n, C_n, and D_n, and compute their…

Combinatorics · Mathematics 2013-10-07 Federico Ardila , Matthias Beck , Serkan Hosten , Julian Pfeifle , Kim Seashore

The sample range of uniform random points $X_1, \dots , X_n$ chosen in a given convex set is the convex hull ${\rm conv}[X_1, \dots, X_n]$. It is shown that in dimension three the expected volume of the sample range is not monotone with…

Probability · Mathematics 2016-12-07 Stefan Kunis , Benjamin Reichenwallner , Matthias Reitzner

A generalized version of a well-known problem of D. G. Kendall states that the zero cell of a stationary Poisson hyperplane tessellation in ${\mathbb{R}}^d$, under the condition that it has large volume, approximates with high probability a…

Probability · Mathematics 2010-10-13 Daniel Hug , Rolf Schneider

We address the problem of constructing elliptic polytopes in R^d, which are convex hulls of finitely many two-dimensional ellipses with a common center. Such sets arise in the study of spectral properties of matrices, asymptotics of long…

Numerical Analysis · Mathematics 2021-07-07 Thomas Mejstrik , Vladimir Yu. Protasov

Poisson processes of so-called $\lambda$-geodesic hyperplanes in $d$-dimensional hyperbolic space are studied for $0\leq\lambda\leq 1$. The case $\lambda=0$ corresponds to genuine geodesic hyperplanes, the case $\lambda=1$ to horospheres…

Probability · Mathematics 2024-02-23 Zakhar Kabluchko , Daniel Rosen , Christoph Thäle

A random matrix representation is proposed for the two-dimensional (2D) Coulomb gas at inverse temperature $\beta$. For $2\times 2$ matrices with Gaussian distribution we analytically compute the nearest neighbour spacing distribution of…

Statistical Mechanics · Physics 2022-07-29 Gernot Akemann , Adam Mielke , Patricia Päßler

We present an explicit closed-form formula for the vertices of the classical cut polytope $\operatorname{CUT}(n)$, defined as the convex hull of cut vectors of the complete graph $K_n$. Our derivation proceeds via a related polytope,…

Combinatorics · Mathematics 2025-07-22 Nevena Marić

Spectrahedra are affine-linear sections of the cone $\mathcal{P}_n$ of positive semidefinite symmetric $n\times n$-matrices. We consider random spectrahedra that are obtained by intersecting~$\mathcal{P}_n$ with the affine-linear space…

Algebraic Geometry · Mathematics 2019-09-18 Paul Breiding , Khazhgali Kozhasov , Antonio Lerario

Let K be the symmetric convex hull of m independent random vectors uniformly distributed on the unit sphere of R^n. We prove that, for every $\delta>0$, the isotropy constant of K is bounded by a constant $c(\delta)$ with high probability,…

Metric Geometry · Mathematics 2007-07-12 David Alonso-Gutierrez

There are (at least) two reasons to study random polytopes. The first is to understand the combinatorics and geometry of random polytopes especially as compared to other classes of polytopes, and the second is to analyze average-case…

Probability · Mathematics 2019-05-02 Andrew Newman

Consider a convex body $C \subset \mathbb{R}^d$. Let $X$ be a random point with uniform distribution in $[0,1]^d$. Define $X_C$ as the number of lattice points in $\mathbb{Z}^d$ inside the translated body $C + X$. It is well known that…

Probability · Mathematics 2025-07-15 Aleksandr Tokmachev

Motivated by the analysis of the performance of the simplex method we study the behavior of families of pivot rules of linear programs. We introduce normalized-weight pivot rules which are fundamental for the following reasons: First, they…

Combinatorics · Mathematics 2022-01-14 Alexander E. Black , Jesús A. De Loera , Niklas Lütjeharms , Raman Sanyal

We study the combinatorial Reeb flow on the boundary of a four-dimensional convex polytope. We establish a correspondence between "combinatorial Reeb orbits" for a polytope, and ordinary Reeb orbits for a smoothing of the polytope,…

Symplectic Geometry · Mathematics 2021-07-28 Julian Chaidez , Michael Hutchings

We study random partitions $\lambda=(\lambda_1,\lambda_2,...,\lambda_d)$ of $n$ whose length is not bigger than a fixed number $d$. Suppose a random partition $\lambda$ is distributed according to the Jack measure, which is a deformation of…

Combinatorics · Mathematics 2009-02-12 Sho Matsumoto

We investigate several computational problems related to the stochastic convex hull (SCH). Given a stochastic dataset consisting of $n$ points in $\mathbb{R}^d$ each of which has an existence probability, a SCH refers to the convex hull of…

Computational Geometry · Computer Science 2017-05-02 Jie Xue , Yuan Li , Ravi Janardan

We analyze the form of the probability distribution function P_{n}^{(\beta)}(w) of the Schmidt-like random variable w = x_1^2/(\sum_{j=1}^n x^{2}_j/n), where x_j are the eigenvalues of a given n \times n \beta-Gaussian random matrix, \beta…

Disordered Systems and Neural Networks · Physics 2015-06-11 M. P. Pato , G. Oshanin
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