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The intrinsic volumes of a convex cone are geometric functionals that return basic structural information about the cone. Recent research has demonstrated that conic intrinsic volumes are valuable for understanding the behavior of random…

Metric Geometry · Mathematics 2015-07-14 Michael B. McCoy , Joel A. Tropp

The intrinsic volumes of a convex body are fundamental invariants that capture information about the average volume of the projection of the convex body onto a random subspace of fixed dimension. The intrinsic volumes also play a central…

Metric Geometry · Mathematics 2022-08-31 Martin Lotz , Joel A. Tropp

The theory of intrinsic volumes of convex cones has recently found striking applications in areas such as convex optimization and compressive sensing. This article provides a self-contained account of the combinatorial theory of intrinsic…

Combinatorics · Mathematics 2017-08-23 Dennis Amelunxen , Martin Lotz

The intrinsic volumes induced by a stationary Poisson k-flat process inside a compact and convex sampling window are considered. Using techniques from stochastic analysis, more precisely calculus with multiple stochastic integrals and a…

Probability · Mathematics 2011-04-13 Matthias Schulte , Christoph Thaele

We study the discrepancy between the distribution of a vector-valued functional of i.i.d. random elements and that of a Gaussian vector. Our main contribution is an explicit bound on the convex distance between the two distributions,…

Probability · Mathematics 2022-03-25 Mikołaj J. Kasprzak , Giovanni Peccati

The intrinsic volumes are measures of the content of a convex body. This paper uses probabilistic and information-theoretic methods to study the sequence of intrinsic volumes of a convex body. The main result states that the intrinsic…

Metric Geometry · Mathematics 2019-03-21 Martin Lotz , Michael B. McCoy , Ivan Nourdin , Giovanni Peccati , Joel A. Tropp

Short and transparent proofs of central limit theorems for intrinsic volumes of random polytopes in smooth convex bodies are presented. They combine different tools such as estimates for floating bodies with Stein's method from probability…

Metric Geometry · Mathematics 2017-11-06 Christoph Thaele , Nicola Turchi , Florian Wespi

Intrinsic volumes, which generalize both Euler characteristic and Lebesgue volume, are important properties of $d$-dimensional sets. A random cubical complex is a union of unit cubes, each with vertices on a regular cubic lattice,…

Probability · Mathematics 2021-08-24 Michael Werman , Matthew L. Wright

We establish central limit theorems for natural volumes of random inscribed polytopes in projective Riemannian or Finsler geometries. In addition, normal approximation of dual volumes and the mean width of random polyhedral sets are…

Metric Geometry · Mathematics 2020-05-22 Florian Besau , Daniel Rosen , Christoph Thäle

Let $K$ be a $d$ dimensional convex body with a twice continuously differentiable boundary and everywhere positive Gauss-Kronecker curvature. Denote by $K_n$ the convex hull of $n$ points chosen randomly and independently from $K$ according…

Metric Geometry · Mathematics 2015-02-25 Imre Bárány , Ferenc Fodor , Viktor Vígh

We study the approximability of general convex sets in $\mathbb{R}^n$ by intersections of halfspaces, where the approximation quality is measured with respect to the standard Gaussian distribution $N(0,I_n)$ and the complexity of an…

Computational Complexity · Computer Science 2023-11-16 Anindya De , Shivam Nadimpalli , Rocco A. Servedio

The investigation of the volume, surface area, and other geometric properties of sections of convex bodies, and in particular cubes, has a long history and a rich literature. However, much less is known when the cube has a volume…

Metric Geometry · Mathematics 2025-11-18 Ferenc Fodor , Bernardo González Merino

The conic support measures localize the conic intrinsic volumes of closed convex cones in the same way as the support measures of convex bodies localize the intrinsic volumes of convex bodies. In this note, we extend the `Master Steiner…

Metric Geometry · Mathematics 2018-07-11 Rolf Schneider

Let $X_1,\ldots,X_n$ be i.i.d.\ random points in the $d$-dimensional Euclidean space sampled according to one of the following probability densities: $$ f_{d,\beta} (x) = \text{const} \cdot (1-\|x\|^2)^{\beta}, \quad \|x\|\leq 1, \quad…

Metric Geometry · Mathematics 2017-12-22 Zakhar Kabluchko , Daniel Temesvari , Christoph Thaele

We study three families of polyhedral cones whose sections are regular simplices, cubes, and crosspolytopes. We compute solid angles and conic intrinsic volumes of these cones. We show that several quantities appearing in stochastic…

Probability · Mathematics 2021-01-01 Zakhar Kabluchko , Hauke Seidel

We establish a general formula for the enclosed volume of constant mean curvature (CMC) surfaces in Euclidean three space with translational periods forming a lattice. The formula relates the volume to the surface area, a…

Differential Geometry · Mathematics 2026-01-22 Lynn Heller , Sebastian Heller , Martin Traizet

Let $X_1,\ldots,X_n$ be a standard normal sample in $\mathbb R^d$. We compute exactly the expected volume of the Gaussian polytope $\mathrm{conv}[X_1,\ldots,X_n]$, the symmetric Gaussian polytope $\mathrm{conv}[\pm X_1,\ldots,\pm X_n]$, and…

Probability · Mathematics 2017-06-27 Zakhar Kabluchko , Dmitry Zaporozhets

Intrinsic volumes are fundamental geometric invariants generalizing volume, surface area, and mean width for convex bodies. We establish a unified Laplace-Grassmannian representation for intrinsic and dual volumes of convex polynomial…

Metric Geometry · Mathematics 2025-11-04 Trí Minh Lê , Khai-Hoan Nguyen-Dang

The central limit theorem for convex bodies says that with high probability the marginal of an isotropic log-concave distribution along a random direction is close to a Gaussian, with the quantitative difference determined asymptotically by…

Functional Analysis · Mathematics 2019-10-01 Haotian Jiang , Yin Tat Lee , Santosh S. Vempala

We investigate a convexity properties for normalized log moment generating function continuing a recent investigation of Chen of convex images of Gaussians. We show that any variable satisfying a ``Ehrhard-like'' property for its…

Probability · Mathematics 2025-10-09 Maite Fernández-Unzueta , James Melbourne , Gerardo Palafox-Castillo
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