Relationship between Trace and Determinant of Unitary Matrices

Since the determinant is 1, the values along the diagonal of the matrix must also be 1. This means that the trace of the matrix will be 2. Therefore, the absolute value of the trace is always less than or equal to 2. The explicit form of U when the trace is 2 is the 2 x 2 identity matrix.
  • #1
dpeagler
34
0

Homework Statement



If U is a 2 x 2 unitary matrix with detU=1. Show that |TrU|≤2. Write down the explicit form ofU when TrU=±2

Homework Equations



Not aware of any particular equations other than the definition of the determinant and trace.

The Attempt at a Solution



I have attempted this problem in several different ways to no avail. I'm pretty sure that the explicit form of U when the trace is 2 is simply the 2 x 2 identity matrix.

I do know that

Tr(AB) ≠ Tr(A)Tr(B)

and

U*U = I

but not sure where to go with this.


Any help is greatly appreciated.
 
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  • #2
remember that for diagonal matrices the determinant is given by the product of the eigenvalues
 
  • #3
dpeagler said:

Homework Statement



If U is a 2 x 2 unitary matrix with detU=1. Show that |TrU|≤2. Write down the explicit form ofU when TrU=±2

Homework Equations



Not aware of any particular equations other than the definition of the determinant and trace.

The Attempt at a Solution



I have attempted this problem in several different ways to no avail. I'm pretty sure that the explicit form of U when the trace is 2 is simply the 2 x 2 identity matrix.

I do know that

Tr(AB) ≠ Tr(A)Tr(B)

and

U*U = I

but not sure where to go with this.


Any help is greatly appreciated.

Perhaps you can use one of the equivalent definitions of a unitary matrix?
See: http://en.wikipedia.org/wiki/Unitary_matrix
I'm thinking that the columns of a unitary matrix form an orthonormal basis...
 
  • #4
Sgd37 I am aware that the product of the eigenvalues has to be 1, but there are an infinite number of combinations that I can create. I'm not sure if the eigenvalues have to be real or not since I don't think that the unitary matrix is necessarily Hermitian.

I'm probably missing something simple.

Thanks so much.
 
  • #5
In an orthonormal basis, the vectors have length 1.
So the highest value in such a vector is 1.
 

FAQ: Relationship between Trace and Determinant of Unitary Matrices

What is the relationship between the trace and determinant of unitary matrices?

The trace and determinant of unitary matrices are both mathematical concepts that describe properties of unitary matrices. The trace of a matrix is the sum of its diagonal elements, while the determinant is a scalar value that describes the scaling factor of the matrix.

How are the trace and determinant related in unitary matrices?

In unitary matrices, the trace and determinant are always related by the equation:
Trace(A) = det(A) + det(A*)
where A* is the conjugate transpose of A. This relationship holds true for all unitary matrices.

Can the trace and determinant of a unitary matrix be equal?

Yes, it is possible for the trace and determinant of a unitary matrix to be equal. This occurs when the matrix has only real eigenvalues, which means that the matrix is also Hermitian. In this case, the trace and determinant will both be equal to the sum of the squares of the matrix's eigenvalues.

How do the trace and determinant change when a unitary matrix is multiplied by a scalar?

When a unitary matrix is multiplied by a scalar, the trace and determinant will both be multiplied by the same scalar value. In other words, if A is a unitary matrix and c is a scalar, then Trace(cA) = c * Trace(A) and det(cA) = c * det(A).

Are there any other relationships between the trace and determinant of unitary matrices?

Yes, there are other relationships between the trace and determinant of unitary matrices. For example, the trace of the product of two unitary matrices is equal to the trace of their individual determinants. Also, the determinant of the product of two unitary matrices is equal to the product of their individual determinants. These relationships can be generalized to the product of n unitary matrices.

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