Computing the Noncommutative Inner Rank by Means of Operator-Valued Free Probability Theory

Abstract 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 distribution of a basic object in free probability theory, namely operator-valued semicircular elements. We have to solve a matrix-valued quadratic equation, for which we provide precise analytical and numerical control on the fixed point algorithm for solving the equation. Numerical examples show the efficiency of the algorithm.

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Publication Details

Journal
Foundations of Computational Mathematics
Published
2024-11-11
DOI
https://doi.org/10.1007/s10208-024-09684-5
Primary Topic
Random Matrices and Applications
Type
article
Field-Weighted Citation Impact
0.00

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Computing the Noncommutative Inner Rank by Means of Operator-Valued Free Probability Theory

Johannes Hoffmann, Roland Speicher, Tobias Mai
Foundations of Computational Mathematics
Random Matrices and Applications
article

Computing the Noncommutative Inner Rank by Means of Operator-Valued Free Probability Theory

Johannes Hoffmann, Roland Speicher, Tobias Mai
article en

Abstract

Abstract 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 distribution of a basic object in free probability theory, namely operator-valued semicircular elements. We have to solve a matrix-valued quadratic equation, for which we provide precise analytical and numerical control on the fixed point algorithm for solving the equation. Numerical examples show the efficiency of the algorithm.

Foundations of Computational MathematicsVol. 26(1)
Saarland University (DE)
Universität des Saarlandes
Openalex Percentile: Top 79%
Random Matrices and Applications
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