Eigenvector in Non-Commutative Algebra
arXiv:2204.06320
Abstract
Let $\Basis e$ be a basis of vector space over non-commutative -algebra . Endomorhism $\Vector{\Basis eb}$ of vector space whose matrix with respect to given basis $\Basis e$ has form where is identity matrix is called similarity transformation with respect to the basis $\Basis e$. Let be a left -vector space and $\Basis e$ be basis of left -vector space . The vector is called eigenvector of the endomorphism \[\Vector f:V\rightarrow V\] with respect to the basis $\Basis e$, if there exists such that \[ \Vector f\circ{v}= \Vector{\Basis eb} \circ{v} \] -number is called eigenvalue of the endomorphism $\Vector f$ with respect to the basis $\Basis e$. There are two products of matrices: (row column: ) and (column row: ). -number is called $\RC$ eigenvalue of the matrix if the matrix is $\RC$ singular matrix. The -number is called right $\RC$ eigenvalue if there exists the column vector which satisfies to the equality \[a{}_*{}^* u=ub\] The column vector is called eigencolumn for right $\RC$ eigenvalue . The -number is called left $\RC$ eigenvalue if there exists the row vector which satisfies to the equality \[u{}_*{}^* a=bu\] The row vector is called eigenrow for right $\RC$ eigenvalue . The set $\RC$ of all left and right $\RC$ eigenvalues is called $\RC$ spectrum of the matrix a.
English text - 50 pages; Russian text - 55 pages. Based on talk given on The 2022 Virtual Joint Mathematics Meetings - April 6-9. arXiv admin note: substantial text overlap with arXiv:1801.01628