Open AccessKronecker products of Perron similarities
Author(s) -
Janelle M. Dockter,
Pietro Paparella,
Robert L. Perry,
Jamie T. Ta
Publication year - 2022
Publication title -
the electronic journal of linear algebra
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 31
eISSN - 1537-9582
pISSN - 1081-3810
DOI - 10.13001/ela.2022.6697
Subject(s) - mathematics , invertible matrix , irreducibility , inverse , eigenvalues and eigenvectors , kronecker delta , matrix (chemical analysis) , similarity (geometry) , kronecker product , combinatorics , pure mathematics , physics , geometry , materials science , image (mathematics) , quantum mechanics , artificial intelligence , computer science , composite material
An invertible matrix is called a Perron similarity if one of its columns and the corresponding row of its inverse are both nonnegative or both nonpositive. Such matrices are of relevance and import in the study of the nonnegative inverse eigenvalue problem. In this work, Kronecker products of Perron similarities are examined and used to construct ideal Perron similarities all of whose rows are extremal.