Topological Mean Value Relations for Random Cell Complexes

There are investigated stationary random q-dimensional topological cell complexes in ?^d, in particular, random tessellations. General relationships between the mean values of topological characteristics are derived. Then they are specified for the cases d = 2, 3, 4.     

Geometric Measures for Random Curved Mosaics of Rd

This paper deals with stationary random mosaics of R^d with general cell shapes. As geometric measures concentrated on the i-skeleton (i = 0, 1,…,d) the i-dimensional surface area (volume) measure and (i — 1) different curvature measures are chosen. The corresponding densities are calculated as well as for the mosaics and their superpositions in terms of mean cell parameters and mean cell numbers. This leads to various relations between the characteristic which are applied, in particular, to two- and three-dimensional tessellations. A comparison with known formulas for mosaics with convex cells in R² and R³ is given.     

Intrinsic volumes of the maximal polytope process in higher dimensional STIT tessellations

Stationary and isotropic iteration stable random tessellations are considered, which are constructed by a random process of iterative cell division. The collection of maximal polytopes at a fixed time t within a convex window W⊂R^d is regarded and formulas for mean values, variances and a characterization of certain covariance measures are proved. The focus is on the case d≥3, which is different from the planar one, treated separately in Schreiber and Thäle (2010) [12]. Moreover, a limit theorem for suitably rescaled intrinsic volumes is established, leading — in sharp contrast to the situation in the plane — to a non-Gaussian limit.     

Shape-driven nested Markov tessellations

A new and rather broad class of stationary random tessellations of the d-dimensional Euclidean space is introduced, which we call shape-driven nested Markov tessellations. Locally, these tessellations are constructed by means of a spatio-temporal random recursive split dynamics governed by a family of Markovian split kernel, generalizing thereby the – by now classical – construction of iteration stable random tessellations. By providing an explicit global construction of the tessellations, it is shown that under suitable assumptions on the split kernels (shape-driven), there exists a unique time-consistent whole-space tessellation-valued Markov process of stationary random tessellations compatible with the given split kernels. Beside the existence and uniqueness result, the typical cell and some aspects of the first-order geometry of these tessellations are in the focus of our discussion.     

Poisson polyhedra in high dimensions

The zero cell of a parametric class of random hyperplane tessellations depending on a distance exponent and an intensity parameter is investigated, as the space dimension tends to infinity. The model includes the zero cell of stationary and isotropic Poisson hyperplane tessellations as well as the typical cell of a stationary Poisson Voronoi tessellation as special cases. It is shown that asymptotically in the space dimension, with overwhelming probability these cells satisfy the hyperplane conjecture, if the distance exponent and the intensity parameter are suitably chosen dimension-dependent functions. Also the high dimensional limits of the mean number of faces are explored and the asymptotic behaviour of an isoperimetric ratio is analysed. In the background are new identities linking the f-vector of the zero cell to certain dual intrinsic volumes.     

Some Markov processes with Brownian exit distributions

Summary LetD be a bounded domain inR ^d with regular boundary. LetX=(X_t, P^x) be a standard Markov process inD with continuous paths up to its lifetime. IfX satisfies some weak conditions, then it is possible to add a non-local part to its generator, and construct the corresponding standard Markov process inD with Brownian exit distributions fromD.This work was done while the author was an Alexander von Humboldt fellow at the Universität des Saarlandes in Saarbrücken, Germany     

Conditional limiting distribution of Type III elliptical random vectors

In this paper we consider elliptical random vectors in R^d,d≥2 with stochastic representation RAU where R is a positive random radius independent of the random vector U which is uniformly distributed on the unit sphere of R^d and A∈R^d×d is a non-singular matrix. When R has distribution function in the Weibull max-domain of attraction we say that the corresponding elliptical random vector is of Type III. For the bivariate set-up, Berman [Sojurns and Extremes of Stochastic Processes, Wadsworth & Brooks/ Cole, 1992] obtained for Type III elliptical random vectors an interesting asymptotic approximation by conditioning on one component. In this paper we extend Berman's result to Type III elliptical random vectors in R^d. Further, we derive an asymptotic approximation for the conditional distribution of such random vectors.     

Intersection patterns of convex sets

LetK ₁,…K_n be convex sets inR ^d. For 0≦i denote byf _ithe number of subsetsS of {1,2,…,n} of cardinalityi+1 that satisfy ∩{K _i∶i∈S}≠Ø. We prove:Theorem.If f _d+r=0 for somer r>=0, then {fx161-1} This inequality was conjectured by Katchalski and Perles. Equality holds, e.g., ifK ₁=…=K_r=R^d andK _r+1,…,K_n aren?r hyperplanes in general position inR ^d. The proof uses multilinear techniques (exterior algebra). Applications to convexity and to extremal set theory are given.     

Point processes of cylinders,particles and flats

Point processesX of cylinders, compact sets (particles), or flats inR ^d are mathematical models for fields of sets as they occur, e.g., in practical problems of image analysis and stereology. For the estimation of geometric quantities of such fields, mean value formulas forX are important. By a systematic approach, integral geometric formulas for curvature measures are transformed into density formulas for geometric point processes. In particular, a number of results which are known for stationary and isotropic Poisson processes of convex sets are generalized to nonisotropic processes, to non-Poissonian processes, and to processes of nonconvex sets. The integral geometric background (including recent results from translative integral geometry), the fundamentals of geometric point processes, and the resulting density formulas are presented in detail. Generalizations of the theory and applications in image analysis and stereology are mentioned shortly.     

Confinement of Brownian motion among Poissonian obstacles in ℝ d , d≥ 3

Consider Brownian motion among random obstacles obtained by translating a fixed compact nonpolar subset of ℝ ^d , d≥ 1, at the points of a Poisson cloud of constant intensity v <: 0. Assume that Brownian motion is absorbed instantaneously upon entering the obstacle set. In SZN-conf Sznitman has shown that in d = 2, conditionally on the event that the process does not enter the obstacle set up to time t, the probability that Brownian motion remains within distance ∼t ^1/4 from its starting point is going to 1 as t goes to infinity. We show that the same result holds true for d≥ 3, with t ^1/4 replaced by t ^{1/( d +2)}. The proof is based on Sznitmans refined method of enlargement of obstacles [10] as well as on a quantitative isoperimetric inequality due to Hall [4]. Received: 6 July 1998     

Convergence to Lévy stable processes under some weak dependence conditions

For a strictly stationary sequence of random vectors in R^d${\mathbb{R}}^d$ we study convergence of partial sum processes to a Lévy stable process in the Skorohod space with _J1$J_1$-topology. We identify necessary and sufficient conditions for such convergence and provide sufficient conditions when the stationary sequence is strongly mixing.     

On Multivariate Adaptive Approximation

Recently, A. Cohen, R. A. DeVore, P. Petrushev, and H. Xu investigated nonlinear approximation in the space BV (R ² ). They modified the classical adaptive algorithm to solve related extremal problems. In this paper, we further study the modified adaptive approximation and obtain results on some extremal problems related to the spaces V _σ,p ^r (R ^d ) of functions of ``Bounded Variation" and Besov spaces B ^α (R ^d ). November 23, 1998. Date revised: June 25, 1999. Date accepted: September 13, 1999.     

On Some Inequalities for Poisson Networks

A stationary Poisson hyperplane process in R^d induces a random network of (d-2)-flats, each of which is the intersection of two hyperplanes of the process. It is known that the intensity of the induced (d-2)-flat process divided by the square of the intensity of the original hyperplane process is maximal in the isotropic case. An integral-geometric formula for elliptic spaces is presented, from which the mentioned extremum property and related inequalities for superpositions of stationary Poisson hyperplane processes are derived.     

A class of quasilinear stochastic partial differential equations of McKean-Vlasov type with mass conservation

Summary A system ofN particles inR ^d with mean field interaction and diffusion is considered. Assuming adiabatic elimination of the momenta the positions satisfy a stochastic ordinary differential equation driven by Brownian sheets (microscopic equation), where all coefficients depend on the position of the particles and on the empirical mass distribution process. This empirical mass distribution process satisfies a quasilinear stochastic partial differential equation (SPDE). This SPDE (mezoscopic equation) is solved for general measure valued initial conditions by extending the empirical mass distribution process from point measure valued initial conditions with total mass conservation. Starting with measures with densities inL ₂(R ^d ,dr), wheredr is the Lebesgue measure, the solution will have densities inL ₂(R ^d ,dr) and strong uniqueness (in the Itô sense) is obtained. Finally, it is indicated how to obtain (macroscopic) partial differential equations as limits of the so constructed SPDE's.This research was supported by NSF grant DMS92-11438 and ONR grant N00014-91J-1386     

An invariance principle for stationary random fields under Hannan’s condition

We establish an invariance principle for a general class of stationary random fields indexed by Z^d${\mathbb{Z}}^d$, under Hannan’s condition generalized to Z^d${\mathbb{Z}}^d$. To do so we first establish a uniform integrability result for stationary orthomartingales, and second we establish a coboundary decomposition for certain stationary random fields. At last, we obtain an invariance principle by developing an orthomartingale approximation. Our invariance principle improves known results in the literature, and particularly we require only finite second moment.     

Characterization of Gaussian measures by the isoperimetric property of half-spaces

If the half-spaces of the form {x∈Rⁿ:x₁≤c} are extremal in the isoperimetric problem for a product-measure μⁿ, n≥2, then the marginal distribution of μ is Gaussian. Bibliography: 8 titles. Translated fromZapiski Nauchnykh Seminarov POMI, Vol. 228, 1996, pp. 31–38.     

Growth of the coefficient of quasiconformality and the boundary correspondence of automorphisms of a ball

A homeomorphismf:B ⁿ→B ⁿ of the unit ball inR ⁿ(n≥2) whose coefficient of quasiconformality in the ball of radiusr<1 has asymptotic rate of growthK(r)=sup _|x|≤r k(x, f)=O(log (1/1−r)) can be continued to a homeomorphism of the closed ball . Forn=2 this implies that the Caratheodory theory of prime ends for conformal mappings also holds for the class of homeomorphismsf:B ²→D withK(r)=O(log (1/1−r)). This work was partially supported by SIZ za nauku SRCG, Titograd.     

On the structure of stationary flat processes. III

Summary For arbitrary k and d with 1 k < d, sufficient conditions in terms of the second order moment measure are found for a stationary random measure in the space of k-flats in R ^d to be a.s. invariant. Some of these conditions are further shown to be almost sharp, in the sense of being nearly fulfilled for a certain class of stationary random measures which fail to be invariant. The latter results are based on estimates of the distributions under the homogeneous probability measure of certain rotational invariants for pairs of linear subspaces.     

Intersection properties of boxes part II: Extremal families

In a previous paper (this Journal, Vol. 62, pp. 283–301) we proved an Upper-Bound Theorem for finite families of boxes inR ^d with edges parallel to the coordinate axes. This theorem concerns the maximum possible numbers of intersecting subfamilies of a family having a given number of members and a given clique number. Here we give an intrinsic characterization ofextremal families of boxes, i.e., families for which all the respective maximum numbers are achieved. We also deal with the problem of enumerating the possible intersection types of extremal families.     

Randomizable point systems

This paper gives a survey of the theory of point-set randomizations with respect to a group. It is shown that only the so-calledk-lattices are randomizable with respect to the parallel translations and all motions of theR ⁿ space. It is shown how the randomizability problems are connected with questions of the theory of discrete Lie groups and regular point systems. The results are applied to the construction of stationary random line processes.