Unitary Matrix preserves the norm Proof

In summary, using the properties of a complex inner product, we can show that <v|v> = <w|w> by taking out the unitary matrix A on the right hand side. This is because A^HA is equal to the identity matrix, which leads to equality. However, if the definition of complex inner product is <Ax, Ay> = <x, A*Ay>, then more work is needed to show that A*A also equals the identity matrix.
  • #1
RJLiberator
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Homework Statement


Let |v> ∈ ℂ^2 and |w> = A|v> where A is an nxn unitary matrix. Show that <v|v> = <w|w>.

Homework Equations


* = complex conjugate
† = hermitian conjugate

The Attempt at a Solution



Start: <v|v> = <w|w>
Use definition of w
<v|v>=<A|v>A|v>>

Here's the interesting part
Using properties of a complex inner product, we can take out the unitary matrix A on the right hand side. When we do so, what do we get?

Is it A*A or is it A†A ?

If it is A†A this proof is complete, as sine A is unitary, this means A†A = the identity matrix and we get equality.

If the definition is A*A then we have to do more work.

I am getting mixed up, as I'm seeing both definitions floating around and with the abusive notation everywhere it is making me second guess which definition is right.

Is there any clarity on this issue here?
 
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  • #3
Thanks for the links. I was aware of the Unitary link, but the other non-English wiki link is of interest.

Although, the language barrier makes it difficult to follow.

They show that
<Ax, Ay> = <x,A^HAy> = <x,A^-1Ay> = <x, Iy> = <x,y>

Kind of similar to what I am doing, I guess, but I'm not sure what "H" is, I am guessing Hermitian conjugate.
So they take the Hermitian conjugate, but then get an inverse somehow, and A^-1*A is clearly the identity.

Still kind of unclear :/
 
  • #4
RJLiberator said:
Thanks for the links. I was aware of the Unitary link, but the other non-English wiki link is of interest.

Although, the language barrier makes it difficult to follow.

They show that
<Ax, Ay> = <x,A^HAy> = <x,A^-1Ay> = <x, Iy> = <x,y>

Kind of similar to what I am doing, I guess, but I'm not sure what "H" is, I am guessing Hermitian conjugate.
So they take the Hermitian conjugate, but then get an inverse somehow, and A^-1*A is clearly the identity.

Still kind of unclear :/
In the German Wikipedia, ##A^H## is indeed the Hermitian conjugate of ##A##, and then they use the fact that A is a Unitary matrix.
 
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  • #5
So this is a definition of complex inner product =

<Ax,Ay> = <x,A^HAy>

If so, then this is rather easy as A^HA = Identity matrix by definition of Unitary.
 

1. What is a unitary matrix?

A unitary matrix is a square matrix with complex entries that, when multiplied by its conjugate transpose, results in the identity matrix. In simpler terms, it is a matrix whose inverse is equal to its conjugate transpose.

2. How does a unitary matrix preserve the norm?

A unitary matrix preserves the norm because the product of a vector with its conjugate transpose is equal to the squared norm of the vector. As a unitary matrix has an inverse that is equal to its conjugate transpose, when it is multiplied with the original vector, the norm remains the same.

3. What is the norm of a vector?

The norm of a vector is a measure of its length, which is calculated by taking the square root of the sum of the squares of its components. It is also known as the magnitude or Euclidean norm.

4. How can the preservation of norm be proven for a unitary matrix?

The preservation of norm for a unitary matrix can be proven using mathematical properties and equations. This proof involves showing that the product of a vector with its conjugate transpose is equal to the squared norm of the vector, and then demonstrating how this holds true for a unitary matrix.

5. What are the applications of a unitary matrix preserving the norm?

The preservation of norm by a unitary matrix has various applications in fields such as quantum mechanics, signal processing, and linear algebra. It allows for the conservation of energy and information in quantum systems and is also used in algorithms for data compression and error correction.

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