Question about diagonalizable matrices

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In summary, if ##A## is a diagonalizable ##n \times n## matrix, it is similar to a diagonal matrix ##B##. The only other diagonal matrix to which ##A## is similar is ##B## itself, up to a rearrangement of the eigenvectors in an ordered eigenbasis for ##ℝ^n##. This can be proven by considering the characteristic polynomial and similarity transformations that preserve diagonal matrices.
  • #1
Bipolarity
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Suppose that ##A## is a diagonalizable ## n \times n ## matrix. Then it is similar to a diagonal matrix ##B##. My question is, is ##B## the only diagonal matrix to which ##A## is similar?

I have thought about this, but am unsure if my answer is correct. My claim is that ##B## is the only diagonal matrix to which ##A## is similar, up to a rearrangement (or permutation) of the eigenvectors of ##A## in an ordered eigenbasis for ##ℝ^{n}##. Thus, if you rearrange the vectors in your eigenbasis, you will obtain a different diagonal matrix for ##[L_{A}]_{β}## but this will be merely a rearrangement of the diagonal entries of B.

Is this true? If so, how might I go about proving this conjecture of mine?

BiP
 
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  • #2
Yes, it's true.

A hint for the proof: the diagonal entries are the eigenvalues of ##A##.
 
  • #3
If ##A = X^{-1}BX = Y^{-1}B'Y## then ##B = (Y X^{-1})^{-1} B' (Y X^{-1})##.
So if A is similar to two diagonal matrices, then these matrices are similar to each other.
I guess a starting point would be to check which similarity transformations keep diagonal matrices diagonal, and see what you can say about X and Y that way.
 
  • #4
micromass said:
Yes, it's true.

A hint for the proof: the diagonal entries are the eigenvalues of ##A##.
Not quite. A matrix can be similar to two different diagonal matrices if they have the same numbers on the diagonal in different orders.
 
  • #5
HallsofIvy said:
Not quite. A matrix can be similar to two different diagonal matrices if they have the same numbers on the diagonal in different orders.

That's exactly what the OP said:

Thus, if you rearrange the vectors in your eigenbasis, you will obtain a different diagonal matrix for ##[L_A]_\beta## but this will be merely a rearrangement of the diagonal entries of B.
 
  • #6
you might look at the characteristic polynomial.
 

What is a diagonalizable matrix?

A diagonalizable matrix is a square matrix that can be transformed into a diagonal matrix by using a similarity transformation. This means that the matrix can be written as a product of three matrices: A = PDP^-1, where P is an invertible matrix and D is a diagonal matrix.

How do I know if a matrix is diagonalizable?

A matrix is diagonalizable if it has n linearly independent eigenvectors, where n is the size of the matrix. This means that the matrix can be diagonalized by finding the eigenvalues and eigenvectors, and then using them to construct the similarity transformation matrix P.

What is the significance of a diagonalizable matrix?

Diagonalizable matrices have many important applications in linear algebra and other areas of mathematics. They are useful for simplifying calculations and solving systems of equations, and they have connections to concepts like eigenvalues, eigenvectors, and diagonalization.

Is every matrix diagonalizable?

No, not every matrix is diagonalizable. A matrix may not be diagonalizable if it does not have n linearly independent eigenvectors, or if its eigenvalues are repeated. However, diagonalizable matrices are a special and important subset of all matrices.

Can I diagonalize a non-square matrix?

No, diagonalization is only possible for square matrices. Non-square matrices cannot have eigenvalues or eigenvectors, which are essential for diagonalization. However, some non-square matrices may have similar properties to diagonalizable matrices, such as triangular matrices.

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