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Related papers: Operator-valued free multiplicative convolution: a…

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We develop an analytic theory of operator-valued additive free convolution in terms of subordination functions. In contrast to earlier investigations our functions are not just given by power series expansions, but are defined as Frechet…

Operator Algebras · Mathematics 2013-09-03 Serban Belinschi , Tobias Mai , Roland Speicher

In this paper we study some analytic properties of bi-free additive convolution, both scalar and operator-valued. We show that using properties of Voiculescu's subordination functions associated to free additive convolution of…

Operator Algebras · Mathematics 2018-01-11 Serban Belinschi , Hari Bercovici , Yinzheng Gu , Paul Skoufranis

It has been shown by Voiculescu and Biane that the analytic subordination property holds for free additive and multiplicative convolutions. In this paper, we present an operatorial approach to subordination for free multiplicative…

Operator Algebras · Mathematics 2009-10-22 Romuald Lenczewski

In this paper, we give subordination functions for free additive and free multiplicative deconvolutions in some domain of the complex half-plane, under the condition that the distributions admit moments, respectively, of second order for…

Operator Algebras · Mathematics 2018-07-18 Octavio Arizmendi , Pierre Tarrago , Carlos Vargas

Let k be a positive integer and let D_k denote the space of joint distributions for k-tuples of selfadjoint elements in C*-probability space. The paper studies the concept of "subordination distribution of \mu \boxplus \nu with respect to…

Operator Algebras · Mathematics 2008-10-30 Alexandru Nica

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

Let $M$ be a $B$-probability space. Assume that $B$ itself is a $D$-probability space; then $M$ can be viewed as $D$-probability space as well. Let $X$ be in $M$. We look at the question of relating the properties of $X$ as $B$-valued…

Operator Algebras · Mathematics 2007-05-23 Alexandru Nica , Dimitri Shlyakhtenko , Roland Speicher

The existence of Voiculescu's subordination functions in the context of non-tracial operator-valued C*-probability spaces has been established using analytic function theory methods. We use a matrix construction to show that the…

Operator Algebras · Mathematics 2022-09-27 Hari Bercovici , Serban T. Belinschi

We develop analytic tools for studying the free multiplicative convolution of any measure on the real line and any measure on the nonnegative real line. More precisely, we construct the subordination functions and the $S$-transform of an…

Probability · Mathematics 2026-04-21 Octavio Arizmendi , Takahiro Hasebe , Yu Kitagawa

In his article "On the free convolution with a semicircular distribution," Biane found very useful characterizations of the boundary values of the imaginary part of the Cauchy-Stieltjes transform of the free additive convolution of a…

Operator Algebras · Mathematics 2016-03-04 Serban Teodor Belinschi

We study random matrices acting on tensor product spaces which have been transformed by a linear block operation. Using operator-valued free probability theory, under some mild assumptions on the linear map acting on the blocks, we compute…

Probability · Mathematics 2016-01-26 Octavio Arizmendi , Ion Nechita , Carlos Vargas

We use the theory of fully matricial, or non-commutative, functions to investigate infinite divisibility and limit theorems in operator-valued non-commutative probability. Our main result is an operator-valued analogue of the Bercovici-Pata…

Operator Algebras · Mathematics 2011-11-24 Serban T. Belinschi , Mihai Popa , Victor Vinnikov

One of the main applications of free probability is to show that for appropriately chosen independent copies of $d$ random matrix models, any noncommutative polynomial in these $d$ variables has a spectral distribution that converges…

Operator Algebras · Mathematics 2023-10-25 Benoît Collins , Tobias Mai , Akihiro Miyagawa , Félix Parraud , Sheng Yin

In this paper, operator-valued bi-free distributions are investigated. Given a subalgebra $D$ of a unital algebra $B$, it is established that a two-faced family $Z$ is bi-free from $(B, B^{\mathrm{op}})$ over $D$ if and only if certain…

Operator Algebras · Mathematics 2016-09-08 Paul Skoufranis

Using simple operator-valued analytic function considerations several general analytic subordination results for a freely Markovian triple of operator algebras are derived from the analytic subordination result for generalized resolvents in…

Operator Algebras · Mathematics 2007-05-23 Dan Voiculescu

Given a set of matrices, modeled as samples of a matrix-valued function, we suggest a method to approximate the underline function using a product approximation operator. This operator extends known approximation methods by exploiting the…

Numerical Analysis · Mathematics 2016-11-15 Nira Dyn , Uri Itai , Nir Sharon

We study matrices whose entries are free or exchangeable noncommutative elements in some tracial $W^*$-probability space. More precisely, we consider operator-valued Wigner and Wishart matrices and prove quantitative convergence to…

Probability · Mathematics 2022-02-16 Marwa Banna , Guillaume Cébron

This in an introduction to the theory of non-commutative distributions of non-commuting operators or random matrices. Starting from the basic problem to find a good approach to the meaning of "non-commutative distribution" we will, in…

Operator Algebras · Mathematics 2020-09-09 Roland Speicher

We address the noncommutative version of the Edmonds' problem, which asks to determine the inner rank of a matrix in noncommuting variables. We provide an algorithm for the calculation of this inner rank by relating the problem with the…

Operator Algebras · Mathematics 2024-12-10 Johannes Hoffmann , Tobias Mai , Roland Speicher

Supervised operator learning centers on the use of training data, in the form of input-output pairs, to estimate maps between infinite-dimensional spaces. It is emerging as a powerful tool to complement traditional scientific computing,…

Machine Learning · Computer Science 2024-08-14 Nicholas H. Nelsen , Andrew M. Stuart
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