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Finite free convolutions of polynomials

We study three convolutions of polynomials in the context of free probability theory. We prove that these convolutions can be written as the expected characteristic polynomials of sums and products of unitarily invariant random matrices. The symmetric additive and multiplicative convolutions were in...

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Autores principales: Marcus, Adam W., Spielman, Daniel A., Srivastava, Nikhil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013345/
https://www.ncbi.nlm.nih.gov/pubmed/35509286
http://dx.doi.org/10.1007/s00440-021-01105-w
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author Marcus, Adam W.
Spielman, Daniel A.
Srivastava, Nikhil
author_facet Marcus, Adam W.
Spielman, Daniel A.
Srivastava, Nikhil
author_sort Marcus, Adam W.
collection PubMed
description We study three convolutions of polynomials in the context of free probability theory. We prove that these convolutions can be written as the expected characteristic polynomials of sums and products of unitarily invariant random matrices. The symmetric additive and multiplicative convolutions were introduced by Walsh and Szegö in different contexts, and have been studied for a century. The asymmetric additive convolution, and the connection of all of them with random matrices, is new. By developing the analogy with free probability, we prove that these convolutions produce real rooted polynomials and provide strong bounds on the locations of the roots of these polynomials.
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spelling pubmed-90133452022-05-02 Finite free convolutions of polynomials Marcus, Adam W. Spielman, Daniel A. Srivastava, Nikhil Probab Theory Relat Fields Article We study three convolutions of polynomials in the context of free probability theory. We prove that these convolutions can be written as the expected characteristic polynomials of sums and products of unitarily invariant random matrices. The symmetric additive and multiplicative convolutions were introduced by Walsh and Szegö in different contexts, and have been studied for a century. The asymmetric additive convolution, and the connection of all of them with random matrices, is new. By developing the analogy with free probability, we prove that these convolutions produce real rooted polynomials and provide strong bounds on the locations of the roots of these polynomials. Springer Berlin Heidelberg 2022-02-18 2022 /pmc/articles/PMC9013345/ /pubmed/35509286 http://dx.doi.org/10.1007/s00440-021-01105-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Marcus, Adam W.
Spielman, Daniel A.
Srivastava, Nikhil
Finite free convolutions of polynomials
title Finite free convolutions of polynomials
title_full Finite free convolutions of polynomials
title_fullStr Finite free convolutions of polynomials
title_full_unstemmed Finite free convolutions of polynomials
title_short Finite free convolutions of polynomials
title_sort finite free convolutions of polynomials
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013345/
https://www.ncbi.nlm.nih.gov/pubmed/35509286
http://dx.doi.org/10.1007/s00440-021-01105-w
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