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The free Meixner laws arise as the distributions of orthogonal polynomials with constant-coefficient recursions. We show that these are the laws of the free pairs of random variables which have linear regressions and quadratic conditional…

Operator Algebras · Mathematics 2007-05-23 Marek Bozejko , Wlodzimierz Bryc

We introduce a class of independence relations, which include free, Boolean and monotone independence, in operator valued probability. We show that this class of independence relations have a matricial extension property so that we can…

Operator Algebras · Mathematics 2018-09-21 Weihua Liu

We consider the random matrix obtained by picking vectors randomly from a large collection of mutually unbiased bases of $\mathbb{C}^n$, and prove that the spectral distribution converges to the Marchenko-Pastur law. This shows that vectors…

Probability · Mathematics 2020-03-27 Chin Hei Chan , Maosheng Xiong

For a class of symmetric random matrices whose entries are martingale differences adapted to an increasing filtration, we prove that under a Lindeberg-like condition, the empirical spectral distribution behaves asymptotically similarly to a…

Probability · Mathematics 2014-02-27 Florence Merlevède , Costel Peligrad , Magda Peligrad

In this work we consider the {\em analog bipartite spin-glass} (or {\em real-valued restricted Boltzmann machine} in a neural network jargon), whose variables (those quenched as well as those dynamical) share standard Gaussian…

Disordered Systems and Neural Networks · Physics 2018-11-22 Elena Agliari , Francesco Alemanno , Adriano Barra , Alberto Fachechi

Bandeira et al. (2017) show that the eigenvalues of the Kendall correlation matrix of $n$ i.i.d. random vectors in $\mathbb{R}^p$ are asymptotically distributed like $1/3 + (2/3)Y_q$, where $Y_q$ has a Mar\v{c}enko-Pastur law with parameter…

Probability · Mathematics 2026-03-20 Pierre Bousseyroux , Tomas Espana , Matteo Smerlak

In this paper we establish a connection between the fluctuations of Wishart random matrices, shifted Chebyshev polynomials, and planar diagrams whose linear span form a basis for the irreducible representations of the annular Temperly-Lieb…

Operator Algebras · Mathematics 2009-07-12 Timothy Kusalik , James A. Mingo , Roland Speicher

This paper studies the limiting behavior of Tyler's M-estimator for the scatter matrix, in the regime that the number of samples $n$ and their dimension $p$ both go to infinity, and $p/n$ converges to a constant $y$ with $0<y<1$. We prove…

Statistics Theory · Mathematics 2016-04-04 Teng Zhang , Xiuyuan Cheng , Amit Singer

In this paper, we study the partial bi-free $S$-transform of a pair $(a,b)$ of random variables, and the $S$-transform of the $2\times 2$ matrix-valued random variable $\left(\begin{matrix}a&0\\0&b\end{matrix}\right)$ associated with…

Operator Algebras · Mathematics 2019-03-07 Mingchu Gao

We prove the Marchenko-Pastur law for the eigenvalues of $p \times p$ sample covariance matrices in two new situations where the data does not have independent coordinates. In the first scenario - the block-independent model - the $p$…

Probability · Mathematics 2021-02-03 Jennifer Bryson , Roman Vershynin , Hongkai Zhao

This paper is the first chapter of three of the author's undergraduate thesis. We study the random matrix ensemble of covariance matrices arising from random $(d_b, d_w)$-regular bipartite graphs on a set of $M$ black vertices and $N$ white…

Probability · Mathematics 2017-04-28 Kevin Yang

This paper studies the asymptotic spectral properties of the sample covariance matrix for high dimensional compositional data, including the limiting spectral distribution, the limit of extreme eigenvalues, and the central limit theorem for…

Statistics Theory · Mathematics 2023-12-25 Qianqian Jiang , Jiaxin Qiu , Zeng Li

We study the limiting spectral distribution of large-dimensional sample covariance matrices associated with symmetric random tensors formed by $\binom{n}{d}$ different products of $d$ variables chosen from $n$ independent standardized…

Probability · Mathematics 2021-11-09 Pavel Yaskov

In statistics, assuming samples are independent is reasonable. However, this property can fail to hold for the features, a distinction that has led to several lines of work aiming to remove the latter assumption of independence present in…

Probability · Mathematics 2026-02-03 Simona Diaconu

We introduce the notion of a conditionally free product and conditionally free convolution. We describe this convolution both from a combinatorial point of view, by showing its connection with the lattice of non-crossing partitions, and…

funct-an · Mathematics 2008-02-03 Marek Bozejko , Michael Leinert , Roland Speicher

We develop a numerical approach for computing the additive, multiplicative and compressive convolution operations from free probability theory. We utilize the regularity properties of free convolution to identify (pairs of) `admissible'…

Probability · Mathematics 2013-07-22 Sheehan Olver , Raj Rao Nadakuditi

Motivated by the asymptotic collective behavior of random and deterministic matrices, we propose an approximation (called "free deterministic equivalent") to quite general random matrix models, by replacing the matrices with operators…

Information Theory · Computer Science 2011-10-07 Roland Speicher , Carlos Vargas , Tobias Mai

We consider a problem in random matrix theory that is inspired by quantum information theory: determining the largest eigenvalue of a sum of p random product states in (C^d)^{otimes k}, where k and p/d^k are fixed while d grows. When k=1,…

Quantum Physics · Physics 2012-02-09 Andris Ambainis , Aram W. Harrow , Matthew B. Hastings

Finite-free additive and multiplicative convolutions are operations on the set of polynomials with real roots, introduced independently by Szeg\"{o} and Walsh in the 1920s. These operations have regained some interest, in the last decade,…

Probability · Mathematics 2025-07-30 Octavio Arizmendi , Daniel Perales , Josue Vazquez-Becerra

We consider the singular vectors of any $m \times n$ submatrix of a rectangular $M \times N$ Gaussian matrix and study their asymptotic overlaps with those of the full matrix, in the macroscopic regime where $N \,/\, M\,$, $m \,/\, M$ as…

Probability · Mathematics 2025-01-16 Elie Attal , Romain Allez