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Wlodzimierz Bryc

Publications and source records attributed to Wlodzimierz Bryc.

At least 19 recordsLinked to original sources

Limit theorems for random Motzkin paths near boundary

We consider Motzkin paths of length $L$, not fixed at zero at both end points, with constant weights on the edges and general weights on the end points. We investigate, as the length $L$ tends to infinity, the limit behaviors of (a) boundary measures induced by the weights on both end points and (b) the segments of the sampled Motzkin path viewed as a process starting from each of the two end points, referred to as boundary processes. Our first result concerns the case when the induced boundary measures have finite first moments. Our second result concerns when the boundary measure on the right end point is a generalized geometric measure with parameter $ρ_1\ge 1$, so that this is an infinite measure and yet it induces a probability measure for random Motzkin path when $ρ_1$ is not too large. The two cases under investigation reveal a phase transition. In particular, we show that the limit left boundary processes in the two cases have the same transition probabilities as random walks conditioned to stay non-negative.

math.PR↗

Limits of Random Motzkin paths with KPZ related asymptotics

We study Motzkin paths of length $L$ with general weights on the edges and end points. We investigate the limit behavior of the initial and final segments of the random Motzkin path viewed as a pair of processes starting from each of the two end points as $L$ becomes large. We then study macroscopic limits of the resulting processes, where in two different regimes we obtain Markov processes that appeared in the description of the stationary measure for the KPZ equation on the half line and of conjectural stationary measure of the hypothetical KPZ fixed point on the half line. Our results rely on the behavior of the Al-Salam--Chihara polynomials in the neighbourhood of the upper end of their orthogonality interval and on the limiting properties of the $q$-Pochhammer and $q$-Gamma functions as $q\nearrow 1$.

math.PR↗

On matrix product ansatz for Asymmetric Simple Exclusion Process with open boundary in the singular case

We study a substitute for the matrix product ansatz for Asymmetric Simple Exclusion Process with open boundary in the ``singular case'' $αβ=q^Nγδ$, when the standard form of the matrix product ansatz of Derrida, Evans, Hakim and Pasquier does not apply. In our approach, the matrix product ansatz is replaced with a pair of linear functionals on an abstract algebra. One of the functionals, $φ_1$, is defined on the entire algebra, and determines stationary probabilities for large systems on $L\geq N+1$ sites. The other functional, $φ_0$, is defined only on a finite-dimensional linear subspace of the algebra, and determines stationary probabilities for small systems on $L< N+1$ sites. Functional $φ_0$ vanishes on non-constant Askey-Wilson polynomials and in non-singular case becomes an orthogonality functional for the Askey-Wilson polynomials.

math-ph↗

Pitman's discrete $2M-X$ theorem for arbitrary initial laws and continuous time limits

We discuss Pitman's representation of a Markov process, which serves as a discrete analog to the Bessel 3D process starting at time 0 from an arbitrary initial law. This representation involves maxima of lazy simple random walks and an auxiliary independent random variable. The law of the auxiliary random variable is explicitly related to the initial law of the Markov process. The proof is kept at an elementary level and relies on a reconstruction formula for the generalized Pitman transform. We then use continuous-time limits to shed additional light on the relation between two representations of the Bessel 3D process that appeared in the description of the stationary measure of the KPZ fixed point on the half-line, as proposed by Barraquand and Le Doussal (2022).

math.PR↗

Cauchy-Stieltjes families with polynomial variance functions and generalized orthogonality

This paper studies variance functions of Cauchy-Stieltjes Kernel families generated by compactly supported centered probability measures. We describe several operations that allow us to construct additional variance functions from known ones. We construct a class of examples which exhausts all cubic variance functions, and provide examples of polynomial variance functions of arbitrary degree. We also relate Cauchy-Stieltjes Kernel families with polynomial variance functions to generalized orthogonality. Our main results are stated solely in terms of classical probability; some proofs rely on analytic machinery of free probability.

math.PR↗

Infinitesimal generators for a class of polynomial processes

We study the infinitesimal generators of evolutions of linear mappings on the space of polynomials, which correspond to a special class of Markov processes with polynomial regressions called quadratic harnesses. We relate the infinitesimal generator to the unique solution of a certain commutation equation, and we use the commutation equation to find an explicit formula for the infinitesimal generator of free quadratic harnesses.

math.PR↗

Free Quadratic Harness

Free quadratic harness is a Markov process from the class of quadratic harnesses, i.e. processes with linear regressions and quadratic conditional variances. The process has recently been constructed for a restricted range of parameters in the paper "Askey-Wilson polynomials, quadratic harnesses and martingales" by W. Bryc and J. Wesołowski using Askey--Wilson polynomials. Here we provide a self-contained construction of the free quadratic harness for all values of parameters.

math.PR↗

One-sided Cauchy-Stieltjes Kernel Families

This paper continues the study of a kernel family which uses the Cauchy-Stieltjes kernel in place of the celebrated exponential kernel of the exponential families theory. We extend the theory to cover generating measures with support that is unbounded on one side. We illustrate the need for such an extension by showing that cubic pseudo-variance functions correspond to free-infinitely divisible laws without the first moment. We also determine the domain of means, advancing the understanding of Cauchy-Stieltjes kernel families also for compactly supported generating measures.

math.PR↗

Free Exponential Families as Kernel Families

Free exponential families have been previously introduced as a special case of the q-exponential family. We show that free exponential families arise also from a procedure analogous to the definition of exponential families by using the Cauchy-Stieltjes kernel instead of the exponential kernel. We use this approach to re-derive several known results and to study further similarities with exponential families and reproductive exponential models.

math.PR↗

Duality of real and quaternionic random matrices

We show that quaternionic Gaussian random variables satisfy a generalization of the Wick formula for computing the expected value of products in terms of a family of graphical enumeration problems. When applied to the quaternionic Wigner and Wishart families of random matrices the result gives the duality between moments of these families and the corresponding real Wigner and Wishart families.

math.PR↗

On slow-fading non-separable correlation MIMO systems

In a frequency selective slow-fading channel in a MIMO system, the channel matrix is of the form of a block matrix. We propose a method to calculate the limit of the eigenvalue distribution of block matrices if the size of the blocks tends to infinity. We will also calculate the asymptotic eigenvalue distribution of $HH^*$, where the entries of $H$ are jointly Gaussian, with a correlation of the form $E[h_{pj}\bar h_{qk}]= \sum_{s=1}^t Ψ^{(s)}_{jk}\hatΨ^{(s)}_{pq}$ (where $t$ is fixed and does not increase with the size of the matrix). We will use an operator-valued free probability approach to achieve this goal. Using this method, we derive a system of equations, which can be solved numerically to compute the desired eigenvalue distribution.

cs.IT↗

Spectra of large block matrices

In a frequency selective slow-fading channel in a MIMO system, the channel matrix is of the form of a block matrix. This paper proposes a method to calculate the limit of the eigenvalue distribution of block matrices if the size of the blocks tends to infinity. While it considers random matrices, it takes an operator-valued free probability approach to achieve this goal. Using this method, one derives a system of equations, which can be solved numerically to compute the desired eigenvalue distribution. The paper initially tackles the problem for square block matrices, then extends the solution to rectangular block matrices. Finally, it deals with Wishart type block matrices. For two special cases, the results of our approach are compared with results from simulations. The first scenario investigates the limit eigenvalue distribution of block Toeplitz matrices. The second scenario deals with the distribution of Wishart type block matrices for a frequency selective slow-fading channel in a MIMO system for two different cases of $n_R=n_T$ and $n_R=2n_T$. Using this method, one may calculate the capacity and the Signal-to-Interference-and-Noise Ratio in large MIMO systems.

cs.IT↗

Asymptotic results for empirical measures of weighted sums of independent random variables

We prove that if a rectangular matrix with uniformly small entries and approximately orthogonal rows is applied to the independent standardized random variables with uniformly bounded third moments, then the empirical CDF of the resulting partial sums converges to the normal CDF with probability one. This implies almost sure convergence of empirical periodograms, almost sure convergence of spectra of circulant and reverse circulant matrices, and almost sure convergence of the CDF's generated from independent random variables by independent random orthogonal matrices. For special trigonometric matrices, the speed of the almost sure convergence is described by the normal approximation and by the large deviation principle.

math.PR↗

On a class of free Levy laws related to a regression problem

The free Meixner laws arise as the distributions of orthogonal polynomials with constant-coefficient recursions. We show that these are the laws of the free pairs of random variables which have linear regressions and quadratic conditional variances when conditioned with respect to their sum. We apply this result to describe free Levy processes with quadratic conditional variances, and to prove a converse implication related to asymptotic freeness of random Wishart matrices.

math.OA↗

Approximation Operators, Exponential, q-Exponential, and Free Exponential Families

Using the technique developed in approximation theory, we construct examples of exponential families of infinitely divisible laws which can be viewed as deformations of the normal, gamma, and Poisson exponential families. Replacing the differential equation of approximation theory by a q-differential equation, we define the q-exponential families, and we identify all q-exponential families with quadratic variance functions when |q|<1. We elaborate on the case of q=0 which is related to free convolution of measures. We conclude by considering briefly the case q>1, and other related generalizations.

math.ST↗