Identifying Self-Adjoint Operators

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Homework Help Overview

The discussion revolves around identifying whether a matrix A is self-adjoint based on its eigenvalues and eigenvectors. The context involves linear algebra concepts, particularly focusing on properties of self-adjoint (or symmetric) matrices.

Discussion Character

  • Conceptual clarification, Assumption checking, Mathematical reasoning

Approaches and Questions Raised

  • The original poster attempts to determine the self-adjoint nature of matrix A by examining its eigenvalues and eigenvectors. Some participants question the sufficiency of orthogonality of eigenvectors as a condition for self-adjointness. Others suggest considering the relationship between the diagonal matrix of eigenvalues and the original matrix.

Discussion Status

Participants are exploring various properties of self-adjoint matrices, including the implications of real eigenvalues and orthogonal eigenvectors. Some guidance has been provided regarding the relationship between the original matrix and its diagonal form, but there is no explicit consensus on the sufficiency of the conditions discussed.

Contextual Notes

There is an ongoing exploration of the definitions and properties of self-adjoint matrices, including the relevance of diagonalization and the relationship between a matrix and its adjoint. The discussion reflects a learning environment where assumptions and definitions are being critically examined.

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Homework Statement



If A has eigenvalues 0 and 1, corresponding to the eigenvectors (1,2) and (2, -1), how can one tell in advance that A is self-adjoint and real.

Homework Equations



e=m^2

The Attempt at a Solution



I can show that A is real: it has real orthogonal eigenvectors and real eigenvalues which form a basis of R2, so any real vector is transformed by A to another vector in R2. It follows that all of the components of A are real.

Showing that the matrix is self-adjoint, however, is trickier for me. I know that eigenvectors corresponding to distinct eigenvalues of a self-adjoint matrix are orthogonal, and clearly these eigenvectors are orthogonal. However, I don't think is is a sufficient condition. If a matrix has two orthogonal eigenvectors, surely that doesn't mean it is self-adjoint, right?

So how can you know at a glance (that is, without reconstructing A by finding the unitary operators formed by taking its eigenvectors as columns), that A is self-adjoint?
 
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What can you say about the diagonal matrix of eigenvalues?
What can you say about any conjugate of a self-adjoint matrix?
 
Perhaps it'd be easier if you noted that a self-adjoint matrix which is real, is simply a symmetric matrix.
 
rochfor1 said:
What can you say about the diagonal matrix of eigenvalues?
What can you say about any conjugate of a self-adjoint matrix?

I'm not quite getting why these are relevant. The conjugate of a self-adjoint matrix A is just A transposed. Not sure what is so interesting about the diagonal matrix of eigenvalues...
 
Write down the diagonal matrix of eigenvalues in this situation. Write down its adjoint. Can you see a relationship?
 
Think about how the original matrix A and the diagonal matrix of eigenvalues are related.

Edit: Oh, I missed you had written this:
So how can you know at a glance (that is, without reconstructing A by finding the unitary operators formed by taking its eigenvectors as columns), that A is self-adjoint?
Construct the matrix with the eigenvectors as columns. Do you notice anything about it?
 
Bam!, I think I have it.

A is diagonalizable, so...

A = U^\ast \Lambda U

And so:

A^\ast = U^\ast \Lambda ^\ast U

But the eigenvalues are all real, so big lambda is self-adjoint, and we can say that:

A^\ast = U^\ast \Lambda U = A

I think that does it. Cool beans.
 

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