Free probability of type B prime

Free probability of type B was invented by Biane–Goodman–Nica, and then it was generalized by Belinschi–Shlyakhtenko and Février–Nica to infinitesimal free probability. The latter found its applications to eigenvalues of perturbed random matrices in the work of Shlyakhtenko and Cébron–Dahlqvist–Gabriel. This paper offers a new framework, called “free probability of type <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="normal upper B prime"> <mml:semantics> <mml:msup> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi mathvariant="normal">B</mml:mi> </mml:mrow> <mml:mo>′</mml:mo> </mml:msup> <mml:annotation encoding="application/x-tex">\mathrm {B}’</mml:annotation> </mml:semantics> </mml:math> </inline-formula> ”, which appears in the large size limit of independent unitarily invariant random matrices with perturbations. Our framework is related to Boolean, free, (anti)monotone, cyclic-(anti)monotone and conditionally free independences. We then apply the new framework to the principal minor of unitarily invariant random matrices, which leads to the definition of a multivariate inverse Markov–Krein transform and asymptotic infinitesimal freeness of principal minors.

Authors

Publication Details

Journal
Transactions of the American Mathematical Society
Published
2025-05-08
DOI
https://doi.org/10.1090/tran/9464
Citations
1
Primary Topic
Random Matrices and Applications
Type
article
Field-Weighted Citation Impact
2.63
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Free probability of type B prime

Takahiro Hasebe, Katsunori Fujie
1 citations
Transactions of the American Mathematical Society
Random Matrices and Applications
2.63
article

Free probability of type B prime

Takahiro Hasebe, Katsunori Fujie
article en
1 citations

Abstract

Free probability of type B was invented by Biane–Goodman–Nica, and then it was generalized by Belinschi–Shlyakhtenko and Février–Nica to infinitesimal free probability. The latter found its applications to eigenvalues of perturbed random matrices in the work of Shlyakhtenko and Cébron–Dahlqvist–Gabriel. This paper offers a new framework, called “free probability of type <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="normal upper B prime"> <mml:semantics> <mml:msup> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi mathvariant="normal">B</mml:mi> </mml:mrow> <mml:mo>′</mml:mo> </mml:msup> <mml:annotation encoding="application/x-tex">\mathrm {B}’</mml:annotation> </mml:semantics> </mml:math> </inline-formula> ”, which appears in the large size limit of independent unitarily invariant random matrices with perturbations. Our framework is related to Boolean, free, (anti)monotone, cyclic-(anti)monotone and conditionally free independences. We then apply the new framework to the principal minor of unitarily invariant random matrices, which leads to the definition of a multivariate inverse Markov–Krein transform and asymptotic infinitesimal freeness of principal minors.

Transactions of the American Mathematical SocietyVol. 378(8)
Openalex Percentile: Top 7%
Random Matrices and Applications
2.63
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.