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We study a system of equal-sized circular discs each with an asymmetrically placed pivot at a fixed distance from the center. The pivots are fixed at the vertices of a regular triangular lattice. The discs can rotate freely about the…

Statistical Mechanics · Physics 2023-10-19 Sushant Saryal , Deepak Dhar

The convex shape contained in a disk having prescribed area and maximal perimeter is completely characterized in terms of the area fraction. The solution is always a polygon having all but one sides equal. The lengths of the sides are…

Metric Geometry · Mathematics 2024-02-09 Beniamin Bogosel

In this paper, we give an overview of some results concerning best and random approximation of convex bodies by polytopes. We explain how both are linked and see that random approximation is almost as good as best approximation.

Metric Geometry · Mathematics 2021-11-16 Joscha Prochno , Carsten Schütt , Elisabeth M. Werner

It is known that the surface of a cone over the unit disc with large height has smaller distortion than the standard embedding of the 2-sphere in $\mathbb R^3$. In this note we show that distortion minimisers exist among convex embedded…

Metric Geometry · Mathematics 2019-04-17 Sebastian Baader , Luca Studer , Roger Züst

We provide non-asymptotic bounds for first and higher order inclusion probabilities of the rejective sampling model with various size parameters. Further we derive bounds in the semi-definite ordering for matrices that collect (conditional)…

Probability · Mathematics 2022-12-20 Simon Ruetz , Karin Schnass

Let N(n, t) be the minimal number of points in a spherical t-design on the unit sphere S^n in R^{n+1}. For each n >= 3, we prove a new asymptotic upper bound N(n, t) <= C(n)t^{a_n}, where C(n) is a constant depending only on n, a_3 <= 4,…

Numerical Analysis · Mathematics 2008-11-04 Andriy V. Bondarenko , Maryna S. Viazovska

Optimal values and solutions of empirical approximations of stochastic optimization problems can be viewed as statistical estimators of their true values. From this perspective, it is important to understand the asymptotic behavior of these…

Optimization and Control · Mathematics 2025-07-01 Johannes Milz , Thomas M. Surowiec

We consider the Riemannian random wave model of Gaussian linear combinations of Laplace eigenfunctions on a general compact Riemannian manifold. With probability one with respect to the Gaussian coefficients, we establish that, both for…

Probability · Mathematics 2022-09-08 Louis Gass

We study extremal properties of spherical random polytopes, the convex hull of random points chosen from the unit Euclidean sphere in $\mathbb{R}^n$. The extremal properties of interest are the expected values of the maximum and minimum…

Probability · Mathematics 2025-01-16 Brett Leroux , Luis Rademacher , Carsten Schütt , Elisabeth M. Werner

We show that the random point measures induced by vertices in the convex hull of a Poisson sample on the unit ball, when properly scaled and centered, converge to those of a mean zero Gaussian field. We establish limiting variance and…

Probability · Mathematics 2008-01-09 T. Schreiber , J. E. Yukich

In this note we study the expected value of certain symplectic capacities of randomly rotated centrally symmetric convex bodies in the classical phase space.

Symplectic Geometry · Mathematics 2017-04-05 Efim D. Gluskin , Yaron Ostrover

The Coordinate Ascent Variational Inference scheme is a popular algorithm used to compute the mean-field approximation of a probability distribution of interest. We analyze its random scan version, under log-concavity assumptions on the…

Machine Learning · Statistics 2024-09-24 Hugo Lavenant , Giacomo Zanella

I first recall the various problems of real enumerative geometry out of which I could extract some integer valued invariants, providing some real counterpart to Gromov-Witten invariants. I then discuss sharpness of the lower bounds given by…

Algebraic Geometry · Mathematics 2010-03-16 Jean-Yves Welschinger

We propose new sequential simulation-optimization algorithms for general convex optimization via simulation problems with high-dimensional discrete decision space. The performance of each choice of discrete decision variables is evaluated…

Optimization and Control · Mathematics 2022-02-15 Haixiang Zhang , Zeyu Zheng , Javad Lavaei

We develop large sample theory including nonparametric confidence regions for $r$-dimensional ridges of probability density functions on $\mathbb{R}^d$, where $1\leq r<d$. We view ridges as the intersections of level sets of some special…

Statistics Theory · Mathematics 2020-04-24 Wanli Qiao

We study the asymptotic distribution, as the volume parameter goes to 1, of the peak (largest part) of finite- or slowly-growing-width cylindric plane partitions weighted by their trace, seam, and volume. There are two natural asymptotic…

Probability · Mathematics 2021-12-01 Dan Betea , Alessandra Occelli

The inscribed radius of a compact manifold with boundary is bounded above if its Ricci curvature and mean curvature are bounded from below. The rigidity result implies that the upper bound can be achieved only in space form. In this paper,…

Differential Geometry · Mathematics 2023-05-26 Xiaoshang Jin

We consider the following geometric optimization problem: find a convex polygon of maximum area contained in a given simple polygon $P$ with $n$ vertices. We give a randomized near-linear-time $(1-\varepsilon)$-approximation algorithm for…

Computational Geometry · Computer Science 2017-10-17 Sergio Cabello , Josef Cibulka , Jan Kynčl , Maria Saumell , Pavel Valtr

In this article a new upper bounds for the multiple trigonometrical integrals are found. The method of the work based on a new method of estimation for the areas of algebraic surfaces.

Number Theory · Mathematics 2013-03-15 Ilgar Sh. Jabbarov

We show that the spectral radius of an $N\times N$ random symmetric matrix with i.i.d. bounded centered but non-symmetrically distributed entries is bounded from above by $ 2 \*\sigma + o(N^{-6/11+\epsilon}), $ where $\sigma^2 $ is the…

Probability · Mathematics 2007-05-23 Sandrine Peche , Alexander Soshnikov