Calculating Square Root of a Matrix in Quantum Information Theory

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The discussion focuses on calculating the square root of a matrix in the context of quantum information theory, emphasizing the need for a solid understanding of linear algebra. The absolute value of a matrix is defined as the square root of the product of the matrix and its conjugate transpose, raising questions about the definition and properties of the square root of a matrix. The participants explore whether this definition is basis independent and how it relates to linear transformations represented in different bases. They conclude that the square root of a positive semidefinite Hermitian matrix is unique and positive semidefinite, which is crucial for applications in quantum theory. Understanding these concepts is essential for progressing in quantum information theory.
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I'm doing an online course in quantum information theory, but it seems to require some knowledge of linear algebra that I don't have.
A definition that popped up today was the definition of the absolute value of a matrix as:

lAl = √(A*A) , where * denotes conjugate transpose.

Now for a given matrix I can calculate the product A*A, but how is the square root of this defined? I have no idea, though I think it should be basis independent, so maybe square root of the trace.
A*A is clearly positive semidefinite but I don't know if I can use that for anything.
 
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aaaa202 said:
I'm doing an online course in quantum information theory, but it seems to require some knowledge of linear algebra that I don't have.
A definition that popped up today was the definition of the absolute value of a matrix as:

lAl = √(A*A) , where * denotes conjugate transpose.

Now for a given matrix I can calculate the product A*A, but how is the square root of this defined? I have no idea, though I think it should be basis independent, so maybe square root of the trace.
A*A is clearly positive semidefinite but I don't know if I can use that for anything.
What's the definition of the square root of a number?
 
Well I guess that the square root of a matrix A is then a matrix B such that B^2 = A. Well wouldn't it be better with a matrix B such that B*B = A. And is this definition basis independent.
 
aaaa202 said:
Well I guess that the square root of a matrix A is then a matrix B such that B^2 = A. Well wouldn't it be better with a matrix B such that B*B = A. And is this definition basis independent.
That would be like requiring the square root of a complex number ##a## to satisfy ##b^*b = a##
 
Ok well is the definition basis independent?
 
aaaa202 said:
Ok well is the definition basis independent?

Let me rephrase that question. If a linear transformation T is represented by the matrix A in one basis and A' in another. Then is |A'| = |A|'?

What do you think?
 
I am not sure. I need to show that:

(√(A))' = √(A')
B' = √(A')

Now if A' = UAU maybe I can use that somehow...
 
aaaa202 said:
I am not sure. I need to show that:

(√(A))' = √(A')
B' = √(A')

Now if A' = UAU maybe I can use that somehow...

Or, think about diagonalizing A*A. It must be true if you want to accept that and get back to your quantum theory!
 
Maybe something like this:

A' = UAU
B' = UBU

Now B2 = A

We want to show that:
√A' = (√A)' = B'

So is B'2 = A'?

Well B'2 = UBUUBU = UB2U = UAU = A'

But all this requires that A and A' and B and B' are related by a basis change with a unitary as above. When is this true?
 
  • #10
That's essentially the proof. The only technicality is that B' must be the right square root. That probably depends on showing that a positive semi-definite matrix has a unique positive semi-definite square root.
 
  • #11
The square root of a positive semidefinite Hermitian matrix ##A## is the unique positive semidefinite matrix ##B## such that ##B^2=A##. You can look at Ch. VI s.3 of "Linear algebra done wrong" for an explanation of why such matrix exists and why it is unique.
 
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