Von Neumann entropy for "similar" pvm observables

In summary, the von Neumann entropy for an observable can be written as ##s=-\sum\lambda\log\lambda##, with the ##\lambda##'s representing its eigenvalues. If two different pvm observables, such as ##A## and ##B##, both represent the same resolution of the identity but have different eigenvalues, with ##\lambda_{A_i}>\lambda_{B_i}## always, then ##s_A>s_B##. However, this raises the question of why the entropy of these two measurements would be any different, as they both represent the same experimental apparatus. The von Neumann entropy is actually an entropy of a state, represented by a positive density matrix ##\rho##
  • #1
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Why is the entropy different if the pvm's use the same resolution of the identity?
The von Neumann entropy for an observable can be written ##s=-\sum\lambda\log\lambda##, where the ##\lambda##'s are its eigenvalues. So suppose you have two different pvm observables, say ##A## and ##B##, that both represent the same resolution of the identity, but simply have different eigenvalues, with ##\lambda_{A_i}>\lambda_{B_i}## always. Then ##s_A>s_B##, but why should that be?

If they both represent the same resolution of the identity, then exactly the same experimental apparatus measures them both. Just change the labels on the pointer dial from the ##A##-values to the ##B##-values. For example, the ##A##-measurement could be mass in grams, whereas ##B## is simply in kilograms. Why should the entropy of those two measurements be any different?
 
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There is no such thing as von Neumann entropy of an observable. The von Neumann entropy is an entropy of a state, represented by a positive density matrix ##\rho## which satisfies ##{\rm Tr}{\rho}=1##. Due to the latter condition, it's impossible that all eigenvalues of one ##\rho## are larger than all eigenvalues of another ##\rho## in the same Hilbert space.
 
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  • #3
The von Neumann entropy is simply
$$S=-k_{\text{B}} \langle \ln \hat{\rho}=-k_{\text{B}} \mathrm{Tr}[\hat{\rho} \ln \hat{\rho}],$$
and this is independent of any choice of basis or which observable is being measured. It gives you the missing information, given the state ##\hat{\rho}##. You have "full information" in the information-theoretical sense when using the von Neumann entropy (which is the Shannon-Jaynes entropy for quantum theory) iff ##\hat{\rho}=|\psi \rangle \langle \psi|##, i.e., if the state is pure.
 

1. What is Von Neumann entropy for "similar" pvm observables?

Von Neumann entropy for "similar" pvm observables is a measure of the uncertainty or randomness associated with a quantum system. It is based on the concept of entropy in classical thermodynamics and is used to quantify the amount of information that is missing about a quantum system.

2. How is Von Neumann entropy calculated?

Von Neumann entropy is calculated by taking the negative of the trace of the density matrix multiplied by the logarithm of the density matrix. The density matrix is a mathematical representation of a quantum system that describes the probabilities of the system being in different states.

3. What is the significance of "similar" pvm observables in Von Neumann entropy?

"Similar" pvm observables refer to observables that have the same eigenvalues but different eigenvectors. In Von Neumann entropy, these observables are important because they represent different ways of measuring the same physical quantity, and the entropy can help determine the most efficient way to measure the system.

4. How does Von Neumann entropy relate to quantum information theory?

Von Neumann entropy is a fundamental concept in quantum information theory. It is used to quantify the amount of information that is missing about a quantum system, and it plays a crucial role in understanding quantum entanglement and quantum communication.

5. Can Von Neumann entropy be negative?

Yes, Von Neumann entropy can be negative in certain cases. This occurs when the density matrix has negative eigenvalues, which can happen in systems with quantum coherence or entanglement. Negative entropy values indicate that the system contains more information than can be measured by the observable being used.

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