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This paper constructs a class of martingale transforms based on L\'evy processes on Lie groups. From these, a natural class of bounded linear operators on the $L^p$-spaces of the group (with respect to Haar measure) for $1<p<\infty$, are…

Probability · Mathematics 2012-06-08 David Applebaum , Rodrigo Bañuelos

The extension $k \mapsto \mu^{\boxplus k}$ of the concept of a free convolution power to the case of non-integer $k \geq 1$ was introduced by Bercovici-Voiculescu and Nica-Speicher, and related to the minor process in random matrix theory.…

Probability · Mathematics 2021-02-10 Dimitri Shlyakhtenko , Terence Tao. With an appendix by David Jekel

We study matricial approximations of master fields we constructed in a previous work. These approximations (in non-commutative distribution) are obtained by extracting blocks of a Brownian unitary diffusion (with entries in $\mathbb{R},…

Probability · Mathematics 2020-05-26 Nicolas Gilliers

We determine the distributional behavior for products of free random variables in a general infinitesimal triangular array. In the case of positive variables, the main theorem extends a result proved earlier for arrays with identically…

Operator Algebras · Mathematics 2007-05-23 Hari Bercovici , Jiun-Chau Wang

In this paper, we introduce and study a unitary matrix-valued process which is closely related to the Hermitian matrix-Jacobi process. It is precisely defined as the product of a deterministic self-adjoint symmetry and a randomly-rotated…

Probability · Mathematics 2020-03-13 Nizar Demni , Tarek Hamdi

The goal of this paper is to investigate how the marginal and dependence structures of a variety of multivariate L\'evy models affect calibration and pricing. To this aim, we study the approaches of Luciano and Semeraro (2010) and Ballotta…

Pricing of Securities · Quantitative Finance 2025-01-22 Giovanni Amici , Paolo Brandimarte , Francesco Messeri , Patrizia Semeraro

We review the recent developments in the theory of normal, normal self-dual and general complex random matrices. The distribution and correlations of the eigenvalues at large scales are investigated in the large $N$ limit. The 1/N expansion…

High Energy Physics - Theory · Physics 2007-05-23 A. Zabrodin

Motivated by limits of critical inhomogeneous random graphs, we construct a family of sequences of measured metric spaces that we call continuous multiplicative graphs, that are expected to be the universal limit of graphs related to the…

Probability · Mathematics 2020-02-07 Nicolas Broutin , Thomas Duquesne , Minmin Wang

The complex analytic methods have found a wide range of applications in the study of multiplicity-free representations. This article discusses, in particular, its applications to the question of restricting highest weight modules with…

Representation Theory · Mathematics 2011-06-23 Toshiyuki Kobayashi

We study line patterns in a free group by considering the topology of the decomposition space, a quotient of the boundary at infinity of the free group related to the line pattern. We show that the group of quasi-isometries preserving a…

Group Theory · Mathematics 2014-11-11 Christopher H. Cashen , Natasa Macura

We present a diagrammatic technique for calculating the free energy of the Hermitian one-matrix model to all orders of 1/N expansion in the case where the limiting eigenvalue distribution spans arbitrary (but fixed) number of disjoint…

High Energy Physics - Theory · Physics 2010-02-03 L. Chekhov , B. Eynard

The eigenvalue spectrum of the sum of large random matrices that are mutually "free", i.e., randomly rotated, can be obtained using the formalism of R-transforms, with many applications in different fields. We provide a direct…

Disordered Systems and Neural Networks · Physics 2025-04-18 Pierre Bousseyroux , Jean-Philippe Bouchaud

This thesis deals with the geometric and integrable aspects associated with random matrix models. Its purpose is to provide various applications of random matrix theory, from algebraic geometry to partial differential equations of…

Mathematical Physics · Physics 2010-12-22 Olivier Marchal

We study the asymptotic behavior of the free cumulants (in the sense of free probability theory of Voiculescu) of Jucys--Murphy elements--or equivalently--of the transition measure associated with a Young diagram. We express these cumulants…

Combinatorics · Mathematics 2007-05-23 Piotr Sniady

We study a stochastic branching model for a population structured by a quantitative phenotypic trait and subject to births, deaths, and mutations. In a regime of large population and small mutations, and in logarithmic scales of size and…

Probability · Mathematics 2026-04-21 Nicolas Champagnat , Sylvie Méléard , Sepideh Mirrahimi , Viet Chi Tran

We prove new vanishing results on the growth of higher torsion homologies for suitable arithmetic lattices, Artin groups and mapping class groups. The growth is understood along Farber sequences, in particular, along residual chains. For…

Geometric Topology · Mathematics 2022-12-16 Miklos Abert , Nicolas Bergeron , Mikolaj Fraczyk , Damien Gaboriau

We introduce the concept of matrix liberation process, a random matrix counterpart of the liberation process in free probability, and prove a large deviation upper bound for its empirical distribution with several properties on its rate…

Probability · Mathematics 2019-05-21 Yoshimichi Ueda

Macroscopic loop correlators are investigated in the hermitian one matrix model with the potential perturbed by the higher order curvature term. In the phase of smooth surfaces the model is equivalent to the minimal conformal matter coupled…

High Energy Physics - Theory · Physics 2009-10-22 G. P. Korchemsky

In this paper, an analogue of matrix models from free probability is developed in the bi-free setting. A bi-matrix model is not simply a pair of matrix models, but a pair of matrix models where one element in the pair acts by…

Operator Algebras · Mathematics 2019-02-08 Paul Skoufranis

Modeling correlation (and covariance) matrices can be challenging due to the positive-definiteness constraint and potential high-dimensionality. Our approach is to decompose the covariance matrix into the correlation and variance matrices…

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