Central limit measure for V-monotone independence
Adrian Dacko

TL;DR
This paper investigates the central limit distribution for V-monotone independence, proving its absolute continuity and providing an implicit form of its density, supported by computational visualization.
Contribution
It introduces the explicit analysis of the central limit distribution for V-monotone independence, including its density and properties, expanding non-commutative probability theory.
Findings
The distribution is absolutely continuous with respect to Lebesgue measure.
An implicit form of the density function is derived.
A computer-generated graph visualizes the density.
Abstract
We study the central limit distribution for V-monotone independence. Using its Cauchy--Stieltjes transform, we prove that is absolutely continuous with respect to the Lebesgue measure on and we give its density in an implicit form. We present a computer generated graph of .
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStochastic processes and statistical mechanics · advanced mathematical theories · Random Matrices and Applications
