Linear Algebra: Unitary matrix

In summary, the conversation discusses the concept of a unitary matrix and how it relates to the hermitian conjugate. It is shown that if U is unitary, then its hermitian conjugate is also unitary. This allows for the sum to be taken over either index. The conversation concludes with a demonstration of how this can be applied using the definition of V.
  • #1
Niles
1,866
0

Homework Statement


Hi

My teacher told us that if we have a unitary matrix U, then

[tex]
\sum\limits_p {\left| {U_{np} } \right|^2 } = 1
[/tex]

Is that really correct? I thought he should be summing over n, not p.
 
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  • #2
Use that if U is unitary, then the hermitian conjugate of U is unitary also to show you can sum over either index.
 
  • #3
Dick said:
Use that if U is unitary, then the hermitian conjugate of U is unitary also to show you can sum over either index.

Hmm, all I know is that U-1=UH. I cannot see how that helps me.
 
  • #4
Niles said:
Hmm, all I know is that U-1=UH. I cannot see how that helps me.

Define V=U^H. Then V also satisfies V^(-1)=V^H. So V is also unitary. The sum over the second index for U is the same as the sum over the first index for V.
 
  • #5
I see, very smart. Thanks.

Have a nice day.
 

1. What is a unitary matrix?

A unitary matrix is a square matrix that has complex entries and satisfies the condition that its conjugate transpose is equal to its inverse. In other words, a unitary matrix is a matrix that preserves the length of vectors and the angle between them when multiplied by it.

2. How is a unitary matrix different from an orthogonal matrix?

While both unitary and orthogonal matrices preserve the length of vectors, a unitary matrix also preserves the angle between vectors, whereas an orthogonal matrix only preserves the perpendicularity between vectors.

3. What is the significance of unitary matrices in linear algebra?

Unitary matrices are important in linear algebra because they represent transformations that preserve the inner product, which allows for a geometric interpretation of complex numbers. They also have applications in quantum mechanics and signal processing.

4. Can all square matrices be unitary?

No, not all square matrices can be unitary. In order to be unitary, a matrix must satisfy the condition that its conjugate transpose is equal to its inverse. This means that the matrix must have complex entries and be invertible.

5. How are unitary matrices used in quantum computing?

Unitary matrices are used in quantum computing to represent quantum gates, which are operations that can be performed on qubits (quantum bits). These operations must be unitary in order to preserve the probability amplitudes of the qubits, which are complex numbers.

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