q-deformed Perelomov–Popov Measures and Quantized Free Probability

Abstract The asymptotic study of tuples of random non-increasing integers is crucial for probabilistic models coming from asymptotic representation theory and statistical physics. We study the global behavior of such tuples, introducing a new family of discrete probability measures, depending on a parameter $$q \in [- 1, 1]$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>q</mml:mi> <mml:mo>∈</mml:mo> <mml:mo>[</mml:mo> <mml:mo>-</mml:mo> <mml:mn>1</mml:mn> <mml:mo>,</mml:mo> <mml:mn>1</mml:mn> <mml:mo>]</mml:mo> </mml:mrow> </mml:math> . We prove the Law of Large Numbers for these measures based on the asymptotics of the Schur generating functions and we provide explicit formulas for the moments and the free cumulants of the limiting measures. Our results provide an interpolation between the results of Bufetov and Gorin for $$q = 0, 1$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>q</mml:mi> <mml:mo>=</mml:mo> <mml:mn>0</mml:mn> <mml:mo>,</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:math> , who distinguished these two cases from the side of free probability theory. We show the connection with free probability theory and we introduce a deformation of free convolution, motivated by our formulas for the free cumulants. We also study the first-order correction to the Law of Large Numbers and we make the connection with infinitesimal free probability, computing explicitly the infinitesimal moments and the infinitesimal free cumulants. Finally, we prove non-asymptotic relations between the limiting measures for different q , which are related to the celebrated Markov-Krein correspondence.

Authors

Institutions

Publication Details

Journal
Annales Henri Poincaré
Published
2025-10-30
DOI
https://doi.org/10.1007/s00023-025-01636-1
Primary Topic
Random Matrices and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

q-deformed Perelomov–Popov Measures and Quantized Free Probability

Panagiotis Zografos
Annales Henri Poincaré
Random Matrices and Applications
article

q-deformed Perelomov–Popov Measures and Quantized Free Probability

Panagiotis Zografos
article en

Abstract

Abstract The asymptotic study of tuples of random non-increasing integers is crucial for probabilistic models coming from asymptotic representation theory and statistical physics. We study the global behavior of such tuples, introducing a new family of discrete probability measures, depending on a parameter $$q \in [- 1, 1]$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>q</mml:mi> <mml:mo>∈</mml:mo> <mml:mo>[</mml:mo> <mml:mo>-</mml:mo> <mml:mn>1</mml:mn> <mml:mo>,</mml:mo> <mml:mn>1</mml:mn> <mml:mo>]</mml:mo> </mml:mrow> </mml:math> . We prove the Law of Large Numbers for these measures based on the asymptotics of the Schur generating functions and we provide explicit formulas for the moments and the free cumulants of the limiting measures. Our results provide an interpolation between the results of Bufetov and Gorin for $$q = 0, 1$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>q</mml:mi> <mml:mo>=</mml:mo> <mml:mn>0</mml:mn> <mml:mo>,</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:math> , who distinguished these two cases from the side of free probability theory. We show the connection with free probability theory and we introduce a deformation of free convolution, motivated by our formulas for the free cumulants. We also study the first-order correction to the Law of Large Numbers and we make the connection with infinitesimal free probability, computing explicitly the infinitesimal moments and the infinitesimal free cumulants. Finally, we prove non-asymptotic relations between the limiting measures for different q , which are related to the celebrated Markov-Krein correspondence.

Annales Henri Poincaré
Leipzig University (DE)
Openalex Percentile: Top 71%
Random Matrices and Applications
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.