Repeated Quantum Interactions and Unitary Random Walks

Among the discrete evolution equations describing a quantum system ℋ _S undergoing repeated quantum interactions with a chain of exterior systems, we study and characterize those which are directed by classical random variables in ℝ ^N . The characterization we obtain is entirely algebraical in terms of the unitary operator driving the elementary interaction. We show that the solutions of these equations are then random walks on the group U(ℋ₀) of unitary operators on ℋ₀.     

Growth and Integrability of Fourier Transforms on Euclidean Space

A fundamental theme in classical Fourier analysis relates smoothness properties of functions to the growth and/or integrability of their Fourier transform. By using a suitable class of \(L^{p}\) -multipliers, a rather general inequality controlling the size of Fourier transforms for large and small argument is obtained. As consequences, quantitative Riemann–Lebesgue estimates are obtained and an integrability result for the Fourier transform is developed extending ideas used by Titchmarsh in the one dimensional setting.     

Stochastic Relations of Random Variables and Processes

This paper generalizes the notion of stochastic order to a relation between probability measures over arbitrary measurable spaces. This generalization is motivated by the observation that for the stochastic ordering of two stationary Markov processes, it suffices that the generators of the processes preserve some, not necessarily reflexive or transitive, subrelation of the order relation. The main contributions of the paper are: a functional characterization of stochastic relations, necessary and sufficient conditions for the preservation of stochastic relations, and an algorithm for finding subrelations preserved by probability kernels. The theory is illustrated with applications to hidden Markov processes, population processes, and queueing systems.     

Stochastic Integrals and Evolution Equations with Gaussian Random Fields

The paper studies stochastic integration with respect to Gaussian processes and fields. It is more convenient to work with a field than a process: by definition, a field is a collection of stochastic integrals for a class of deterministic integrands. The problem is then to extend the definition to random integrands. An orthogonal decomposition of the chaos space of the random field, combined with the Wick product, leads to the Itô-Skorokhod integral, and provides an efficient tool to study the integral, both analytically and numerically. For a Gaussian process, a natural definition of the integral follows from a canonical correspondence between random processes and a special class of random fields. Also considered are the corresponding linear stochastic evolution equations.     

Estimations of Hölder Regularities and Direction of Singularity by Hart Smith and Curvelet Transforms

Using Hart Smith’s and curvelet transforms, new necessary and new sufficient conditions for an L ²(?²) function to possess Hölder regularity, uniform and pointwise, with exponent α>0 are given. Similar to the characterization of Hölder regularity by the continuous wavelet transform, the conditions here are in terms of bounds of the transforms across fine scales. However, due to the parabolic scaling, the sufficient and necessary conditions differ in both the uniform and pointwise cases. We also investigate square-integrable functions with sufficiently smooth background. Specifically, sufficient and necessary conditions, which include the special case with 1-dimensional singularity line, are derived for pointwise Hölder exponent. Inside their “cones” of influence, these conditions are practically the same, giving near-characterization of direction of singularity.     

RETRACTED ARTICLE: Convergence of Weighted Sums for Arrays of Negatively Dependent Random Variables and Its Applications

We discuss the complete convergence of weighted sums for arrays of rowwise negatively dependent random variables (ND r.v.’s) to linear processes. As an application, we obtain the complete convergence of linear processes based on ND r.v.’s which extends the result of Li et al. (Stat. Probab. Lett. 14:111–114, 1992), including the results of Baum and Katz (Trans. Am. Math. Soc. 120:108–123, 1965), from the i.i.d. case to a negatively dependent (ND) setting. We complement the results of Ahmed et al. (Stat. Probab. Lett. 58:185–194, 2002) and confirm their conjecture on linear processes in the ND case.     

Least-squares Polynomial Estimation from Observations Featuring Correlated Random Delays

The least-squares polynomial filtering and fixed-point smoothing problems of discrete-time signals from randomly delayed observations is addressed, when the Bernoulli random variables modelling the delay are correlated at consecutive sampling times. Recursive estimation algorithms are deduced without requiring full knowledge of the state-space model generating the signal process, but only information about the delay probabilities and the moments of the processes involved. Defining a suitable augmented observation vector, the polynomial estimation problem is reduced to the linear estimation problem of the signal based on the augmented observations, which is solved by using an innovation approach.     

Moments and Distribution of the Local Times of a Transient Random Walk on ℤ d

Consider an arbitrary transient random walk on ℤ ^d with d∈ℕ. Pick α∈[0,∞), and let L _n (α) be the spatial sum of the αth power of the n-step local times of the walk. Hence, L _n (0) is the range, L _n (1)=n+1, and for integers α, L _n (α) is the number of the α-fold self-intersections of the walk. We prove a strong law of large numbers for L _n (α) as n→∞. Furthermore, we identify the asymptotic law of the local time in a random site uniformly distributed over the range. These results complement and contrast analogous results for recurrent walks in two dimensions recently derived by Černy (Stoch. Proc. Appl. 117:262–270, 2007). Although these assertions are certainly known to experts, we could find no proof in the literature in this generality.      

Some Exponential Inequalities for Positively Associated Random Variables and Rates of Convergence of the Strong Law of Large Numbers

We present some exponential inequalities for positively associated unbounded random variables. By these inequalities, we obtain the rate of convergence n ^−1/2 β _n log ^3/2 n in which β _n can be particularly taken as (log log n)^1/σ with any σ>2 for the case of geometrically decreasing covariances, which is faster than the corresponding one n ^−1/2(log log n)^1/2log ² n obtained by Xing, Yang, and Liu in J. Inequal. Appl., doi: (2008) for the case mentioned above, and derive the convergence rate n ^−1/2 β _n log ^1/2 n for the above β _n under the given covariance function, which improves the relevant one n ^−1/2(log log n)^1/2log n obtained by Yang and Chen in Sci. China, Ser. A 49(1), 78–85 (2006) for associated uniformly bounded random variables. In addition, some moment inequalities are given to prove the main results, which extend and improve some known results.     

Uniformly Accurate Quantile Bounds for Sums of Arbitrary Independent Random Variables

Fix any n≥1. Let X ₁,…,X _n be independent random variables such that S _n =X ₁+⋅⋅⋅+X _n , and let S^*_n=sup_{1 ￡ k ￡ n}S_kS^{*}_{n}=\sup_{1\le k\le n}S_{k} . We construct upper and lower bounds for s _y and s_y^*s_{y}^{*} , the upper \frac1y\frac{1}{y} th quantiles of S _n and S^*_nS^{*}_{n} , respectively. Our approximations rely on a computable quantity Q _y and an explicit universal constant γ _y , the latter depending only on y, for which we prove that

On Asymptotic Expansion in the Random Allocation of Particles by Sets

We consider a scheme of equiprobable allocation of particles into cells by sets. An Edgeworth-type asymptotic expansion in the local central limit theorem for the number of empty cells left after allocation of all sets of particles is derived.     

Refined Self-normalized Large Deviations for Independent Random Variables

Let X ₁,X ₂,…?, be independent random variables with EX _i =0 and write \(S_{n}=\sum_{i=1}^{n}X_{i}\) and \(V_{n}^{2}=\sum_{i=1}^{n}X_{i}^{2}\). This paper provides new refined results on the Cramér-type large deviation for the so-called self-normalized sum S _n /V _n . The major techniques used to derive these new findings are different from those used previously.     

Recurrence Relationships for the Mean Number of Faces and Vertices for Random Convex Hulls

This paper studies the convex hull of n random points in R^d\mathsf{R}^{d} . A recently proved topological identity of the author is used in combination with identities of Efron and Buchta to find the expected number of vertices of the convex hull—yielding a new recurrence formula for all dimensions d. A recurrence for the expected number of facets and (d−2)-faces is also found, this analysis building on a technique of Rényi and Sulanke. Other relationships for the expected count of i-faces (1≤i<d) are found when d≤5, by applying the Dehn–Sommerville identities. A general recurrence identity (see (3) below) for this expected count is conjectured.     

Hedetniemi’s Conjecture and Dense Boolean Lattices

The category D{\mathcal{D}} of finite directed graphs is Cartesian closed, hence it has a product and exponential objects. For a fixed K, let K^DK^{\mathcal{D}} be the class of all directed graphs of the form K ^G , preordered by the existence of homomorphisms, and factored by homomorphic equivalence. It has long been known that K^DK^{\mathcal{D}} is always a Boolean lattice. In this paper we prove that for any complete graph K _n with n ≥ 3, K_n^DK_n^{\mathcal{D}} is dense, hence up to isomorphism it is the unique countable dense Boolean lattice. In graph theory, the structure of K_n^DK_n^{\mathcal{D}} is connected to the conjecture of Hedetniemi on the chromatic number of a categorical product of graphs.     

Weighted Poisson Cells as Models for Random Convex Polytopes

We introduce a parametric family for random convex polytopes in ? ^d which allows for an easy generation of samples for further use, e.g., as random particles in materials modelling and simulation. The basic idea consists in weighting the Poisson cell, which is the typical cell of the stationary and isotropic Poisson hyperplane tessellation, by suitable geometric characteristics. Since this approach results in an exponential family, parameters can be efficiently estimated by maximum likelihood. This work has been motivated by the desire for a flexible model for random convex particles as can be found in many composite materials such as concrete or refractory castables.     

Random and algebraic permutations’ statistics

An algebraic permutation $\hat{A}\in S(N=n^{m})$ is the permutation of the N points of the finite torus ? _n ^m , realized by a linear operator A∈SL(m,? _n ). The statistical properties of algebraic permutations are quite different from those of random permutations of N points. For instance, the period length T(A) grows superexponentially with N for some (random) permutations A of N elements, whereas $T(\hat{A})$ is bounded by a power of N for algebraic permutations  $\hat{A}$ . The paper also contains a strange mean asymptotics formula for the number of points of the finite projective line P¹(? _n ) in terms of the zeta function.     

Exact Asymptotics in log log Laws for Random Fields

Let be i.i.d. random variables, and set S _n = _k n X _k . We exhibit a method able to provide exact loglog rates. The typical result is that

Identification of the Time Derivative Coefficient in a Fast Diffusion Degenerate Equation

In this paper, we deal with the identification of the space variable time derivative coefficient u in a degenerate fast diffusion differential inclusion. The function u is vanishing on a subset strictly included in the space domain Ω. This problem is approached as a control problem (P) with the control u. An approximating control problem (P _ε ) is introduced and the existence of an optimal pair is proved. Under certain assumptions on the initial data, the control is found in W ^2,m (Ω), with m>N, in an implicit variational form. Next, it is shown that a sequence of optimal pairs (u_e^*,y_e^*)(u_{\varepsilon }^{\ast },y_{\varepsilon }^{\ast }) of (P _ε ) converges as ε goes to 0 to a pair (u ^*,y ^*) which realizes the minimum in (P), and y ^* is the solution to the original state system.