# $R$-diagonal and $\eta$-diagonal Pairs of Random Variables

## TL;DR

This paper explores $R$-diagonal and $
eta$-diagonal pairs of random variables, generalizing circular elements in bi-free probability, and characterizes their distributions and independence properties in operator algebra contexts.

## Contribution

It introduces bi-circular pairs as $R$-diagonal examples, provides formulas for their product distributions, and characterizes $
eta$-diagonal pairs via $*$-distributions and invariance properties.

## Key findings

- Formulas for distributions of product pairs of $R$-diagonal pairs
- Characterization of $R$-diagonal pairs via $*$-moments and invariance
- Demonstration of non-Boolean independence in certain algebraic constructions

## Abstract

This paper is devoted to studying $R$-diagonal and $\eta$-diagonal pairs of random variables. We generalize circular elements to the bi-free setting, defining bi-circular element pairs of random variables, which provide examples of $R$-diagonal pairs of random variables. Formulae are given for calculating the distributions of the product pairs of two $*$-bi-free $R$-diagonal pairs. When focusing on pairs of left acting operators and right acting operators from finite von Neumann algebras in the standard form, we characterize $R$-diagonal pairs in terms of the $*$-moments of the random variables, and of distributional invariance of the random variables under multiplication by free unitaries. We define $\eta$-diagonal pairs of random variables, and give a characterization of $\eta$-diagonal pairs in terms of the $*$-distributions of the random variables. If every non-zero element in a $*$-probability space has a non-zero $*$-distribution, we prove that the unital algebra generated by a $2\times 2$ off-diagonal matrix with entries of a non-zero random variable $x$ and its adjoint $x^*$ in the algebra and the diagonal $2\times 2$ scalar matrices can never be Boolean independent fromm the $2\times 2$ scalar matrix algebra with amalgamation over the diagonal scalar matrix algebra.