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Christoph Thaele

Publications and source records attributed to Christoph Thaele.

At least 19 recordsLinked to original sources

Limit laws for longest edges in empty region graphs

Empty region graphs are graphs whose vertices are points in $\mathbb{R}^d$ and where two vertices are connected by an edge whenever some associated region does not contain any other vertices. We investigate the asymptotic behaviour of long edges in empty region graphs generated by a stationary Poisson process in $\mathbb{R}^d$. {Letting} the intensity of the underlying Poisson process tend to infinity, we consider the associated point process of edge midpoints, suitably transformed edge lengths, and directions of the edges. We prove that it converges in distribution to a Poisson process on $\mathbb{R}^d \times \mathbb{R}\times\mathbb{L}^d$, where $\mathbb{L}^d$ is the space of lines in $\mathbb{R}^d$ through the origin, and that the suitably transformed length of the longest edge with midpoint in an observation window converges in distribution to a Gumbel distributed random variable. Our approach yields explicit error bounds in Kantorovich--Rubinstein distance for the point process convergence {when restricting to an observation window} and in Kolmogorov distance for the maximal edge length. The results apply uniformly to a broad class of empty region graphs, including the Gabriel graph, the relative neighbourhood graph, the beta-skeleton graph, the Mastercard graph, and the Pacman graph.

math.PR

Seeing Through Hyperbolic Space: Visibility for $\lambda$-Geodesic Hyperplanes

We study visibility from a fixed point in the presence of a Poisson process of $\lambda$--geodesic hyperplanes in a $d$-dimensional hyperbolic space. The family of $\lambda$--geodesic hyperplanes interpolates between totally geodesic hyperplanes and horospheres. Our main result establishes a universality principle for this model: we prove that the fundamental visibility properties are invariant with respect to the parameter $\lambda\in[0,1]$. Namely, there is a critical intensity $\gamma_{\mathrm{crit}}>0$ such that the visible region is unbounded with positive probability for $\gamma < \gamma_{\mathrm{crit}}$ and almost surely bounded for $\gamma > \gamma_{\mathrm{crit}}$. For $d=2$ we establish almost sure boundedness also at criticality. The value for $\gamma_{\mathrm{crit}}$ is explicit and does not depend on $\lambda$. In the bounded phase, we show that the mean visible volume is identical with the known formula for $\lambda=0$. The key integral-geometric step is an explicit computation showing that the measure of $\lambda$-geodesic hyperplanes hitting a geodesic segment is a linear function of the length of the segment, independent of~$\lambda$.

math.PR

Visibility and intersection density for Boolean models in hyperbolic space

For Poisson particle processes in hyperbolic space we introduce and study concepts analogous to the intersection density and the mean visible volume, which were originally considered in the analysis of Boolean models in Euclidean space. In particular, we determine a necessary and sufficient condition for the finiteness of the mean visible volume of a Boolean model in terms of the intensity and the mean surface area of the typical grain.

math.PR

Limit Theorems for the Volume of Random Projections and Sections of $\ell_p^N$-balls

Let $\mathbb{B}_p^N$ be the $N$-dimensional unit ball corresponding to the $\ell_p$-norm. For each $N\in\mathbb N$ we sample a uniform random subspace $E_N$ of fixed dimension $m\in\mathbb{N}$ and consider the volume of $\mathbb{B}_p^N$ projected onto $E_N$ or intersected with $E_N$. We also consider geometric quantities other than the volume such as the intrinsic volumes or the dual volumes. In this setting we prove central limit theorems, moderate deviation principles, and large deviation principles as $N\to\infty$. Our results provide a complete asymptotic picture. In particular, they generalize and complement a result of Paouris, Pivovarov, and Zinn [A central limit theorem for projections of the cube, Probab. Theory Related Fields. 159 (2014), 701-719] and another result of Adamczak, Pivovarov, and Simanjuntak [Limit theorems for the volumes of small codimensional random sections of $\ell_p^n$-balls, Ann. Probab. 52 (2024), 93-126].

math.PR

A Blaschke-Petkantschin formula for linear and affine subspaces with application to intersection probabilities

Consider a uniformly distributed random linear subspace $L$ and a stochastically independent random affine subspace $E$ in $\mathbb{R}^n$, both of fixed dimension. For a natural class of distributions for $E$ we show that the intersection $L\cap E$ admits a density with respect to the invariant measure. This density depends only on the distance $d(o,E \cap L)$ of $L\cap E$ to the origin and is derived explicitly. It can be written as the product of a power of $d(o,E \cap L)$ and a part involving an incomplete beta integral. Choosing $E$ uniformly among all affine subspaces of fixed dimension hitting the unit ball, we derive an explicit density for the random variable $d(o,E \cap L)$ and study the behavior of the probability that $E \cap L$ hits the unit ball in high dimensions. Lastly, we show that our result can be extended to the setting where $E$ is tangent to the unit sphere, in which case we again derive the density for $d(o,E \cap L)$. Our probabilistic results are derived by means of a new integral-geometric transformation formula of Blaschke--Petkantschin type.

math.MG

Weighted floating functions and weighted functional affine surface areas

The purpose of this paper is to introduce the new concept of weighted floating functions associated with log concave or $s$-concave functions. This leads to new notions of weighted functional affine surface areas. Their relation to more traditional versions of functional affine surface areas as well as to the classical affine surface areas for convex bodies is discussed in detail.

math.MG

Moderate deviations on Poisson chaos

This paper deals with U-statistics of Poisson processes and multiple Wiener-Itô integrals on the Poisson space. Via sharp bounds on the cumulants for both classes of random variables, moderate deviation principles, concentration inequalities and normal approximation bounds with Cramér correction are derived. It is argued that the results obtained in this way are in a sense best possible and cannot be improved systematically. Applications in stochastic geometry and to functionals of Ornstein-Uhlenbeck-Lévy processes are investigated.

math.PR

Large nearest neighbour balls in hyperbolic stochastic geometry

Consider a stationary Poisson process in a $d$-dimensional hyperbolic space. For $R>0$ define the point process $ξ_R^{(k)}$ of exceedance heights over a suitable threshold of the hyperbolic volumes of $k$th nearest neighbour balls centred around the points of the Poisson process within a hyperbolic ball of radius $R$ centred at a fixed point. The point process $ξ_R^{(k)}$ is compared to an inhomogeneous Poisson process on the real line with intensity function $e^{-u}$ and point process convergence in the Kantorovich-Rubinstein distance is shown. From this, a quantitative limit theorem for the hyperbolic maximum $k$th nearest neighbour ball with a limiting Gumbel distribution is derived.

math.PR

Sectional Voronoi tessellations: Characterization and high-dimensional limits

The intersections of beta-Voronoi, beta-prime-Voronoi and Gaussian-Voronoi tessellations in $\mathbb{R}^d$ with $\ell$-dimensional affine subspaces, $1\leq \ell\leq d-1$, are shown to be random tessellations of the same type but with different model parameters. In particular, the intersection of a classical Poisson-Voronoi tessellation with an affine subspace is shown to have the same distribution as a certain beta-Voronoi tessellation. The geometric properties of the typical cell and, more generally, typical $k$-faces, of the sectional Poisson-Voronoi tessellation are studied in detail. It is proved that in high dimensions, that is as $d\to\infty$, the intersection of the $d$-dimensional Poison-Voronoi tessellation with an affine subspace of fixed dimension $\ell$ converges to the $\ell$-dimensional Gaussian-Voronoi tessellation.

math.PR

Random cones in high dimensions I: Donoho-Tanner and Cover-Efron cones

Two models of random cones in high dimensions are considered, together with their duals. The Donoho-Tanner random cone $D_{n,d}$ can be defined as the positive hull of $n$ independent $d$-dimensional Gaussian random vectors. The Cover-Efron random cone $C_{n,d}$ is essentially defined as the same positive hull, conditioned on the event that it is not the whole space. We consider expectations of various combinatorial and geometric functionals of these random cones and prove that they satisfy limit theorems, as $d$ and $n$ tend to infinity in a suitably coordinated way. This includes, for example, large deviation principles and central as well as non-central limit theorems for the expected number of $k$-faces and the $k$-th conic intrinsic volumes, as $n$, $d$ and possibly also $k$ tend to infinity simultaneously. Furthermore, we determine the precise high-dimensional asymptotic behaviour of the expected statistical dimension for both models of random cones, uncovering thereby another high-dimensional phase transition. As an application, limit theorems for the number of $k$-faces of high-dimensional polytopes generated by random Gale diagrams are discussed as well.

math.PR

Weighted $p$-radial Distributions on Euclidean and Matrix $p$-balls with Applications to Large Deviations

A probabilistic representation for a class of weighted $p$-radial distributions, based on mixtures of a weighted cone probability measure and a weighted uniform distribution on the Euclidean $\ell_p^n$-ball, is derived. Large deviation principles for the empirical measure of the coordinates of random vectors on the $\ell_p^n$-ball with distribution from this weighted measure class are discussed. The class of $p$-radial distributions is extended to $p$-balls in classical matrix spaces, both for self-adjoint and non-self-adjoint matrices. The eigenvalue distribution of a self-adjoint random matrix, chosen in the matrix $p$-ball according to such a distribution, is determined. Similarly, the singular value distribution is identified in the non-self-adjoint case. Again, large deviation principles for the empirical spectral measures for the eigenvalues and the singular values are presented as an application.

math.PR

Concentration on Poisson spaces via modified $Φ$-Sobolev inequalities

Concentration properties of functionals of general Poisson processes are studied. Using a modified $Φ$-Sobolev inequality a recursion scheme for moments is established, which is of independent interest. This is applied to derive moment and concentration inequalities for functionals on abstract Poisson spaces. Applications of the general results in stochastic geometry, namely Poisson cylinder models and Poisson random polytopes, are presented as well.

math.PR

The typical cell of a Voronoi tessellation on the sphere

The typical cell of a Voronoi tessellation generated by $n+1$ uniformly distributed random points on the $d$-dimensional unit sphere $\mathbb S^d$ is studied. Its $f$-vector is identified in distribution with the $f$-vector of a beta' polytope generated by $n$ random points in $\mathbb R^d$. Explicit formulae for the expected $f$-vector are provided for any $d$ and the low-dimensional cases $d\in\{2,3,4\}$ are studied separately. This implies an explicit formula for the total number of $k$-dimensional faces in the spherical Voronoi tessellation as well.

math.PR

Limit theorems for random points in a simplex

In this work the $\ell_q$-norms of points chosen uniformly at random in a centered regular simplex in high dimensions are studied. Berry-Esseen bounds in the regime $1\leq q < \infty$ are derived and complemented by a non-central limit theorem together with moderate and large deviations in the case where $q=\infty$. A comparison with corresponding results for $\ell_p^n$-balls is carried out as well.

math.PR

Large deviations, moderate deviations, and the KLS conjecture

Having its origin in theoretical computer science, the Kannan-Lovász-Simonovits (KLS) conjecture is one of the major open problems in asymptotic convex geometry and high-dimensional probability theory today. In this work, we establish a new connection between this conjecture and the study of large and moderate deviations for isotropic log-concave random vectors, thereby providing a novel possibility to tackle the conjecture. We then study the moderate deviations for the Euclidean norm of random orthogonally projected random vectors in an $\ell_p^n$-ball. This leads to a number of interesting observations: (A) the $\ell_1^n$-ball is critical for the new approach; (B) for $p\geq 2$ the rate function in the moderate deviations principle undergoes a phase transition, depending on whether the scaling is below the square-root of the subspace dimensions or comparable; (C) for $1\leq p<2$ and comparable subspace dimensions, the rate function again displays a phase transition depending on its growth relative to $n^{p/2}$.

math.PR

Beta polytopes and Poisson polyhedra: $f$-vectors and angles

We study random polytopes of the form $[X_1,\ldots,X_n]$ defined as convex hulls of independent and identically distributed random points $X_1,\ldots,X_n$ in $\mathbb{R}^d$ with one of the following densities: $$ f_{d,β} (x) = c_{d,β} (1-\|x\|^2)^β, \qquad \|x\| < 1, \quad \text{(beta distribution, $β>-1$)} $$ or $$ \tilde f_{d,β} (x) = \tilde{c}_{d,β} (1+\|x\|^2)^{-β}, \qquad x\in\mathbb{R}^d, \quad \text{(beta' distribution, $β>d/2$)}. $$ This setting also includes the uniform distribution on the unit sphere and the standard normal distribution as limiting cases. We derive exact and asymptotic formulae for the expected number of $k$-faces of $[X_1,\ldots,X_n]$ for arbitrary $k\in\{0,1,\ldots,d-1\}$. We prove that for any such $k$ this expected number is strictly monotonically increasing with $n$. Also, we compute the expected internal and external angles of these polytopes at faces of every dimension and, more generally, the expected conic intrinsic volumes of their tangent cones. By passing to the large $n$ limit in the beta' case, we compute the expected $f$-vector of the convex hull of Poisson point processes with power-law intensity function. Using convex duality, we derive exact formulae for the expected number of $k$-faces of the zero cell for a class of isotropic Poisson hyperplane tessellations in $\mathbb R^d$. This family includes the zero cell of a classical stationary and isotropic Poisson hyperplane tessellation and the typical cell of a stationary Poisson--Voronoi tessellation as special cases. In addition, we prove precise limit theorems for this $f$-vector in the high-dimensional regime, as $d\to\infty$. Finally, we relate the $d$-dimensional beta and beta' distributions to the generalized Pareto distributions known in extreme-value theory.

math.PR

A new look at random projections of the cube and general product measures

A strong law of large numbers for $d$-dimensional random projections of the $n$-dimensional cube is derived. It shows that with respect to the Hausdorff distance a properly normalized random projection of $[-1,1]^n$ onto $\mathbb{R}^d$ almost surely converges to a centered $d$-dimensional Euclidean ball of radius $\sqrt{2/π}$, as $n\to\infty$. For every point inside this ball we determine the asymptotic number of vertices and the volume of the part of the cube projected `close' to this point. Moreover, large deviations for random projections of general product measures are studied. Let $ν^{\otimes n}$ be the $n$-fold product measure of a Borel probability measure $ν$ on $\mathbb{R}$, and let $I$ be uniformly distributed on the Stiefel manifold of orthogonal $d$-frames in $\mathbb{R}^n$. It is shown that the sequence of random measures $ν^{\otimes n}\circ(n^{-1/2}I^*)^{-1}$, $n\in\mathbb{N}$, satisfies a large deviations principle with probability $1$. The rate function is explicitly identified in terms of the moment generating function of $ν$. At the heart of the proofs lies a transition trick which allows to replace the uniform projection by the Gaussian one. A number of concrete examples are discussed as well, including the uniform distributions on the cube $[-1,1]^n$ and the discrete cube $\{-1,1\}^n$ as a special cases.

math.PR

The volume of simplices in high-dimensional Poisson-Delaunay tessellations

Typical weighted random simplices $Z_μ$, $μ\in(-2,\infty)$, in a Poisson-Delaunay tessellation in $\mathbb{R}^n$ are considered, where the weight is given by the $(μ+1)$st power of the volume. As special cases this includes the typical ($μ=-1$) and the usual volume-weighted ($μ=0$) Poisson-Delaunay simplex. By proving sharp bounds on cumulants it is shown that the logarithmic volume of $Z_μ$ satisfies a central limit theorem in high dimensions, that is, as $n\to\infty$. In addition, rates of convergence are provided. In parallel, concentration inequalities as well as moderate deviations are studied. The set-up allows the weight $μ=μ(n)$ to depend on the dimension $n$ as well. A number of special cases are discussed separately. For fixed $μ$ also mod-$ϕ$ convergence and the large deviations behaviour of the logarithmic volume of $Z_μ$ are investigated.

math.PR