Decomposing Real Square Matrices via Unitary Diagonalization
Spectral Theory
2016-06-07 v2 Combinatorics
Abstract
Diagonalization, or eigenvalue decomposition, is very useful in many areas of applied mathematics, including signal processing and quantum physics. Matrix decomposition is also a useful tool for approximating matrices as the product of a matrix and its transpose, which relates to unitary diagonalization. As stated by the spectral theorem, only normal matrices are unitarily diagonalizable. However we show that all real square matrices are the real part of some unitarily diagonalizable matrix.
Cite
@article{arxiv.1605.07103,
title = {Decomposing Real Square Matrices via Unitary Diagonalization},
author = {Théo Trouillon and Christopher R. Dance and Éric Gaussier and Guillaume Bouchard},
journal= {arXiv preprint arXiv:1605.07103},
year = {2016}
}