Operator-valued Jacobi parameters and examples of operator-valued distributions

TL;DR

This paper introduces generalized Jacobi parameters for operator-valued distributions, develops combinatorial tools for free probability calculations, and provides new examples and algorithms related to operator-valued free convolutions.

Contribution

It defines operator-valued Jacobi parameters, introduces a combinatorial method for joint distribution calculations, and presents new free convolution examples and a counting algorithm.

Findings

Includes a new family of $$-valued free binomial distributions.

Develops a combinatorial method using two-color non-crossing partitions.

Shows the class of distributions with Jacobi parameters is not closed under free convolution.

Abstract

In the setting of distributions taking values in a $C^\ast$-algebra $\mathcal{B}$, we define generalized Jacobi parameters and study distributions they generate. These include numerous known examples and one new family, of $\mathcal{B}$-valued free binomial distributions, for which we are able to compute free convolution powers. Moreover, we develop a convenient combinatorial method for calculating the joint distributions of $\mathcal{B}$-free random variables with Jacobi parameters, utilizing two-color non-crossing partitions. This leads to several new explicit examples of free convolution computations in the operator-valued setting. Additionally, we obtain a counting algorithm for the number of two-color non-crossing pairings of relative finite depth, using only free probabilistic techniques. Finally, we show that the class of distributions with Jacobi parameters is not closed under free convolution.