Unitary equivalence vs. similarity

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In summary, two matrices A and B are unitarily equivalent if there exists a unitary matrix P such that A = P*BP. In order to determine if two matrices are unitarily equivalent, one must check if they are both normal and have the same eigenvalues. If both conditions are met, then the matrices are unitarily equivalent. However, having the same characteristic polynomial is not enough to guarantee unitary equivalence. Additionally, if the matrices are diagonalizable, having identical eigenvalues is sufficient to show similarity, but not unitary equivalence.
  • #1
quasar_4
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Two matrices A and B are defined to be unitarily equivalent if there exists a unitary matrix P such that A = P*BP.

If one is given two matrices A and B with no P, how do we know if the matrices are unitarily equivalent? I guess what I'm asking is, is it sufficient to check whether the matrices have the same characteristic polynomial and that one of them is diagonal? What exactely does normality have to do with unitary equivalence? How is it related to similarity and congruence of matrices? Someone suggested to me that I check to see if they are both normal, but I guess I don't see how that fits into the definition. I know that matrices that are unitarily equivalent are also similar (P seems a lot like regular change of basis matrix Q except that it comes from an orthonormal basis instead of regular bases).

Anyone know anything I'm missing?
 
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  • #2
I do not think that if one of the given matrices is diagonal then just comparing the two matrices to have the same char. function is enough to gaurantee that the matrices are unitarily equivalent. This may happen if A is not normal.

In general if none of the matrices are diagonal then simply comparing the char function will only give us similarilty and not unitary equivalence. If in addition the matrices are normal (unitarily diagonalizable) then we can say they are unitarily equivalent.

If A and B are normal and have same e.v. : A=P* D P and B=Q* D Q (P, Q unitary)
then P A P* = D and then B = Q* P A P* Q. Now P*Q is unitary. So A and B are unitarily equivalent.

But this seems to be a sufficient condition only. May be one can show that this is necessary as well.
 
  • #3
aha. this is making much more sense now. It seems that both A and B must be normal; to further check, one needs only check whether they have the same eigenvalues, since if they are unitarily equivalent then they are certainly similar. :rofl:
 
  • #4
Just wanted to straighten things out for record. I said earlier that if char. polynomial is same then the two matrices are similar. But that is not true. The implication is only that if two matrices are similar then they have the same char. polynomial. Again if in addition we are given the matrices are diagonalizable (not necessarily normal) then we have similarity.So for now we have:

If Diagonalizable: identical eigenvalues <=> Similarity
If Normal: identical eigenvalues <=> Unitary equivalence
 

What is the difference between unitary equivalence and similarity?

Unitary equivalence and similarity are both concepts used in linear algebra to compare and classify matrices. The main difference between these two concepts is that unitary equivalence is a stronger condition than similarity. Unitary equivalence requires both matrices to have the same eigenvalues and the same eigenvectors, while similarity only requires the matrices to have the same eigenvalues. In other words, two matrices that are unitarily equivalent are also similar, but the reverse is not always true.

How do you determine if two matrices are unitarily equivalent?

To determine if two matrices are unitarily equivalent, you can follow these steps:

  1. Compute the eigenvalues of both matrices.
  2. If the matrices have different eigenvalues, they are not unitarily equivalent.
  3. For each eigenvalue, find the corresponding eigenspace.
  4. If the eigenspaces for each eigenvalue are different, the matrices are not unitarily equivalent.
  5. If the eigenspaces are the same, check if the corresponding eigenvectors are the same. If they are not, the matrices are not unitarily equivalent.
  6. If the eigenspaces and eigenvectors are the same, the matrices are unitarily equivalent.

Can two matrices with different dimensions be unitarily equivalent?

No, two matrices with different dimensions cannot be unitarily equivalent. Unitary equivalence is a property that can only be applied to square matrices, meaning matrices with an equal number of rows and columns. Therefore, if two matrices have different dimensions, they cannot be unitarily equivalent.

What is the significance of unitarily equivalent matrices?

Unitarily equivalent matrices have the same eigenvalues and eigenvectors, which means they share the same characteristic properties. This is useful in many applications, such as solving systems of linear equations, diagonalizing matrices, and finding eigenvectors and eigenvalues. In addition, unitarily equivalent matrices have the same determinant, trace, and rank, which are important properties in linear algebra.

How is unitary equivalence related to unitary matrices?

A unitary matrix is a special type of square matrix that satisfies the property of being unitarily equivalent to its conjugate transpose. This means that a unitary matrix is always unitarily equivalent to itself, and it is also unitarily equivalent to any other matrix that is similar to it. Therefore, unitary matrices play a crucial role in understanding unitary equivalence and its applications in linear algebra.

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