- Quantum mutual information
In

quantum information theory ,**quantum mutual information**, or**von Neumann mutual information**, is a measure of correlation between subsystems of quantum state. It is the quantum mechanical analog of Shannonmutual information .**Motivation**For simplicity, it will be assumed that all objects in the article are finite dimensional.

The definition of quantum mutual entropy is motivated by the classical case. For a probability distribution of two variables "p"("x", "y"), the two marginal distributions are

:$p(x)\; =\; sum\_\{y\}\; p(x,y);\; ,\; ;\; p(y)\; =\; sum\_\{x\}\; p(x,y).$

The classical mutual information "I"("X", "Y") is defined by

:$;I(X,Y)\; =\; S(p(x))\; +\; S(p(y))\; -\; S(p(x,y))$

where "S"("q") denotes the

Shannon entropy of the probability distribution "q".One can calculate directly

:$;\; S(p(x))\; +\; S(p(y))$

:$;\; =\; sum\_x\; p\_x\; log\; p(x)\; +\; sum\_y\; p\_y\; log\; p(y)$ :$;\; =\; sum\_x\; ;\; (\; sum\_\{y\text{'}\}\; p(x,y\text{'})\; log\; sum\_\{y\text{'}\}\; p(x,y\text{'})\; )\; +\; sum\_y\; (\; sum\_\{x\text{'}\}\; p(x\text{'},y)\; log\; sum\_\{x\text{'}\}\; p(x\text{'},y))$

:$;\; =\; sum\_\{x,y\}\; p(x,y)\; (log\; sum\_\{y\text{'}\}\; p(x,y\text{'})\; +\; log\; sum\_\{x\text{'}\}\; p(x\text{'},y))$

:$;\; =\; sum\_\{x,y\}\; p(x,y)\; log\; p(x)\; p(y)\; .$

So the mutual information is

:$I(X,Y)\; =\; sum\_\{x,y\}\; p(x,y)\; log\; frac\{p(x)\; p(y)\}\{p(x,y)\}.$

But this is precisely the

relative entropy between "p"("x", "y") and "p"("x")"p"("y"). In other words, if we assume the two variables "x" and "y" to be uncorrelated, mutual information is the "discrepancy in uncertainty" resulting from this (possibly erroneous) assumption.It follows from the property of relative entropy that "I"("X","Y") ≥ 0 and equality holds if and only if "p"("x", "y") = "p"("x")"p"("y").

**Definition**The quantum mechanical counterpart of classical probability distributions are density matrices.

Consider a composite quantum system whose state space is the tensor product

:$H\; =\; H\_A\; otimes\; H\_B.$

Let "ρ"

^{"AB"}be a density matrix acting on "H". Thevon Neumann entropy of "ρ", which is the quantum mechanical analaog of the Shannon entropy, is given by:$S(\; ho^\{AB\})\; =\; -\; operatorname\{Tr\}\; ho^\{AB\}\; log\; ho^\{AB\}.$

For a probability distribution "p"("x","y"), the marginal distributions are obtained by integrating away the variables "x" or "y". The corresponding operation for density matrices is the

partial trace . So one can assign to "ρ" a state on the subsystem "A" by:$ho^A\; =\; operatorname\{Tr\}\_B\; ;\; ho^\{AB\}$

where Tr

_{"B"}is partial trace with respect to system "B". This is the**reduced state**of "ρ^{AB}" on system "A". The**reduced von Neumann entropy**' of "ρ^{AB}" with respect to system "A" is:$;S(\; ho^A).$

"S"("ρ

^{B}") is defined in the same way."Technical Note:" In mathematical language, passing from the classical to quantum setting can be described as follows. The "algebra of observables" of a physical system is a

C*-algebra and states are unital linear functionals on the algebra. Classical systems are described by commutative C*-algebras, therefore classical states areprobability measure s. Quantum mechanical systems have non-commutative observable algebras. In concrete considerations, quantum states are density operators. If the probability measure "μ" is a state on classical composite system consisting of two subsystem "A" and "B", we project "μ" onto the system "A" to obtain the reduced state. As stated above, the quantum analog of this is the partial trace operation, which can be viewed as projection onto a tensor component. "End of note"We can see now the appropriate definition of quantum mutual information should be

:$;\; I(\; ho^\{AB\})\; =\; S(\; ho^A)\; +\; S(\; ho^B)\; -\; S(\; ho^\{AB\}).$

Quantum mutual information can be interpretated the same way as in the classical case: it can be shown that

:$I(\; ho^\{AB\})\; =\; S(\; ho^\{AB\}\; |\; ho^A\; otimes\; ho^B)$

where $S(cdot\; |\; cdot)$ denotes

quantum relative entropy .

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