User:IssaRice/Linear algebra/Classification of operators: Difference between revisions

Revision as of 23:56, 2 January 2019

Let $V$ be a finite-dimensional inner product space, and let $T : V \to V$ be a linear transformation. Then in the table below, the statements within the same row are equivalent.

Operator kind	Description in terms of eigenvectors	Description in terms of diagonalizability	Notes
$T$ is diagonalizable	There exists a basis of $V$ consisting of eigenvectors of $T$	$T$ is diagonalizable (there exists a basis $β$ of $V$ with respect to which $[T]_{β}^{β}$ is a diagonal matrix)	This basis is not unique because we can reorder the vectors and also scale eigenvectors by a non-zero number to obtain an eigenvector.
$T$ is normal	There exists an orthonormal basis of $V$ consisting of eigenvectors of $T$	$T$ is diagonalizable using an orthonormal basis
$T$ self-adjoint ( $T$ is Hermitian)	There exists an orthonormal basis of $V$ consisting of eigenvectors of $T$ with real eigenvalues	$T$ is diagonalizable using an orthonormal basis and the diagonal entries are all real
$T$ is an isometry	There exists an orthonormal basis of $V$ consisting of eigenvectors of $T$ whose eigenvalues all have absolute value 1	$T$ is diagonalizable using an orthonormal basis and the diagonal entries all have absolute values 1	This only works when the field of scalars is the complex numbers
$T$ is positive	There exists an orthonormal basis of $V$ consisting of eigenvectors of $T$ with positive real eigenvalues	$T$ is diagonalizable using an orthonormal basis and the diagonal entries are all positive real numbers

@@ Line 5: / Line 5: @@
 ! Operator kind !! Description in terms of eigenvectors !! Description in terms of diagonalizability !! Notes
 |-
-| <math>T</math> is diagonalizable || There exists a basis of <math>V</math> consisting of eigenvectors of <math>T</math> || <math>T</math> is diagonalizable (there exists a basis <math>\beta</math> of <math>V</math> with respect to which <math>[T]_\beta^\beta</math> is a diagonal matrix)
+| <math>T</math> is diagonalizable || There exists a basis of <math>V</math> consisting of eigenvectors of <math>T</math> || <math>T</math> is diagonalizable (there exists a basis <math>\beta</math> of <math>V</math> with respect to which <math>[T]_\beta^\beta</math> is a diagonal matrix) || This basis is not unique because we can reorder the vectors and also scale eigenvectors by a non-zero number to obtain an eigenvector.
 |-
 | <math>T</math> is normal || There exists an orthonormal basis of <math>V</math> consisting of eigenvectors of <math>T</math> || <math>T</math> is diagonalizable using an orthonormal basis