$S$-transform in Finite Free Probability

TL;DR

This paper introduces a finite free probability $S$-transform that converges to Voiculescu's $S$-transform, providing new tools for approximating free convolutions and related laws through finite polynomial analysis.

Contribution

The paper defines a finite $S$-transform that converges to the classical one, enabling finite approximations of free probability concepts and proving related limit theorems.

Findings

Defined a finite $S$-transform converging to Voiculescu's $S$-transform.

Established finite analogues of free laws and convolutions.

Proved a finite approximation of the Tucci--Haagerup--M"oller limit theorem.

Abstract

We present a simplified explanation of why free fractional convolution corresponds to the differentiation of polynomials, by finding how the finite free cumulants of a polynomial behave under differentiation. This approach allows us to understand the limiting behaviour of the coefficients $\widetilde{\mathsf{e}}_k(p_d)$ of $p_d$ when the degree $d$ tends to infinity and the empirical root distribution of $p_d$ has a limiting distribution $\mu$ on $[0,\infty)$. Specifically, we relate the asymptotic behaviour of the ratio of consecutive coefficients to Voiculescu's $S$-transform of $\mu$. This prompts us to define a new notion of finite $S$-transform, which converges to Voiculescu's $S$-transform in the large $d$ limit. It also satisfies several analogous properties to those of the $S$-transform in free probability, including multiplicativity and monotonicity. This new insight has several applications that strengthen the connection between free and finite free probability. Most notably, we generalize the approximation of $\boxtimes_d$ to $\boxtimes$ and prove a finite approximation of the Tucci--Haagerup--M\"oller limit theorem in free probability, conjectured by two of the authors. We also provide finite analogues of the free multiplicative Poisson law, the free max-convolution powers and some free stable laws.