Lecture 24
Chapter V Eigenvalue and Eigenvectors
5E Commuting Operators
Definition 5.71
- For , and commute if .
- For , and commute if .
Example: For , and commute
- Partial Derivatives ,
- Diagonal matrices commute with each other
Proposition 5.74
Given , commute if and only if commute.
Proof:
Proposition 5.75
Suppose commute and , then the eigenspace is invariant under .
Proof: Suppose
is an eigenvector with eigenvalue (or )
Theorem 5.76
Let be diagonalizable operators. Then are diagonalizable with respect to the same basis (simultaneously diagonalizable) if and only if commute.
Proof:
diagonal matrices commute
Since is diagonalizable, , where are the (distinct) eigenvalues of . consider (Theorem 5.65) this operator is diagonalizable because is diagonalizable. We can chose a basis of such that gives a diagonal matrix. Take the basis of given by concatenating the bases of the elements of this basis eigenvectors of and so and are diagonalizable with respect to this basis.
Proposition 5.78
Every pair of commuting operators on a finite dimensional complex nonzero vector spaces has at least one common eigenvectors.
Proof: apply (5.75) and the fact that operator on complex vector spaces has at least one eigenvector.
Theorem 5.80
If are commuting operators, then there is a basis where both have upper triangular matrices.
Proof:
Induction on .
, clear
, use (5.78) to find and eigenvector for and . Decompose as then defined a map define as similarly now apply the inductive hypothesis to and . get a basis where they are both upper triangular and then exercise: are upper triangular with respect to the basis .
Theorem 5.81
For finite dimensional commuting operators then every eigenvalue of is a sum of an eigenvector of and an eigenvalue of ; every eigenvalue of is a product of an eigenvector of and an eigenvalue of .
Proof:
For upper triangular matrices