User:IssaRice/Linear algebra/Classification of operators

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Let V be a finite-dimensional inner product space, and let T:VV 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 Geometric interpretation Notes Examples
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]ββ 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. But there are at most dimV distinct eigenvalues so the diagonal matrix should be unique up to order? If T is the identity map, then every non-zero vector vV is an eigenvector of T with eigenvalue 1 because Tv=1v. Thus every basis β=(v1,,vn) diagonalizes T. The matrix of T with respect to β is the identity matrix.
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 (positive semidefinite) There exists an orthonormal basis of V consisting of eigenvectors of T with nonnegative real eigenvalues T is diagonalizable using an orthonormal basis and the diagonal entries are all nonnegative real numbers