On the definition of Von Neumann entropy

In summary, the Von Neumann entropy, defined as S (\rho) = - tr(\rho \log \rho), is a measure of the uncertainty or randomness in a quantum system described by the density matrix, \rho. The logarithm of a matrix is defined as a series expansion using the derivative of the natural logarithm function and integration. This allows for the calculation of the Von Neumann entropy by transforming the density matrix into a diagonal matrix and using a similar series expansion method. This is a common approach for computing the Von Neumann entropy.
  • #1
univector
15
0
I am confused by the definition of the Von Neumann entropy. In Nielson and Chung's book page 510, the Von Neumann entropy is defined as
[tex] S (\rho) = - tr(\rho \log \rho) [/tex]
where [tex] \rho [/tex] is the density matrix. What is the definition of the logrithm of a matrix? Is it some series expansion of a matrix, or an element-by-element logrithm?

Thanks.
 
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  • #2
Note that

[tex]\frac{d}{dx}\log(1+x)=\frac{1}{1+x}=1-x+x^2-x^3+\cdots[/tex]

Integrate.

[tex]\log(1+x)=x-\frac{x^2}{2}+\frac{x^3}{3}-\frac{x^4}{4}+\cdots[/tex]

Now set y=1+x.

[tex]\log y=(y-1)-\frac{(y-1)^2}{2}+\cdots=\sum_{k=1}^\infty(-1)^{k+1}\frac{(y-1)^k}{k}[/tex]

This suggests that if A is a matrix, we can define log A by

[tex]\log A=\sum_{k=1}^\infty(-1)^{k+1}\frac{(A-I)^k}{k}[/tex]

for all matrices A such that the series converges. More information here.
 
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  • #3
Hi Fredrik,

Thanks for the explanation. If the matrix [itex] \rho [/itex] is not diagonal, it is not trivial to calculate the matrix polynomial series. Instead, if we do a similary transform to diagonize [itex] \rho [/itex] first, things may become easier. Let the diagonal matrix be [itex] D [/itex]. Then by using the series expansion forward (for a matrix) and backward (for a number), we can come up with
[tex] S(\rho) = tr (D M) [/tex],
where
[tex] M = \left( \begin{array}{cccc} \log \lambda_1 & 0 & 0 & ... \\
0 & \log \lambda_2 & 0 & ... \\
... & ... & ... & ... \\
0 & ... & 0 & \log \lambda_n
\end{array} \right)[/tex]
where [itex] \lambda_i [/itex] is the ith engenvalue of matrix [itex] \rho [/itex] (or [itex] D [/itex]), and [itex] n [/itex] is the number of rows (also columns) of [itex] \rho [/itex] .

Is this the way people calculate [itex] S(\rho) [/itex]?
 
  • #4
Yes.
 

FAQ: On the definition of Von Neumann entropy

1. What is Von Neumann entropy?

Von Neumann entropy is a measure of the randomness or uncertainty in a quantum system. It is named after physicist John von Neumann and is a fundamental concept in quantum information theory.

2. How is Von Neumann entropy defined?

Von Neumann entropy is defined as the negative trace of the density matrix, which represents the state of a quantum system. It is a measure of the average amount of information needed to describe the state of the system.

3. What is the significance of Von Neumann entropy in quantum mechanics?

Von Neumann entropy is a key concept in quantum mechanics as it quantifies the amount of uncertainty in a quantum system. It is also used in various quantum information processing tasks such as quantum cryptography and quantum computing.

4. How does Von Neumann entropy differ from classical entropy?

Classical entropy measures the randomness or disorder in a classical system, while Von Neumann entropy measures the randomness in a quantum system. Classical entropy is based on probabilities, while Von Neumann entropy is based on the density matrix.

5. Can Von Neumann entropy be negative?

Yes, Von Neumann entropy can be negative in certain cases, such as when dealing with entangled quantum states. This negative value indicates that the system has a lower level of randomness than a completely random state.

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