The Inequalities of Quantum Information Theory

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Mathematics (HMC)

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Let ρ denote the density matrix of a quantum state having n parts 1, ..., n. For I⊆N={1, ..., n}, let ρI=TrNI/(ρ) denote the density matrix of the state comprising those parts i such that i∈I, and let S(ρI) denote the von Neumann (1927) entropy of the state ρI. The collection of ν=2n numbers {S(ρI)}I⊆N may be regarded as a point, called the allocation of entropy for ρ, in the vector space Rν. Let An denote the set of points in Rν that are allocations of entropy for n-part quantum states. We show that A~n~ (the topological closure of An) is a closed convex cone in Rν. This implies that the approximate achievability of a point as an allocation of entropy is determined by the linear inequalities that it satisfies. Lieb and Ruskai (1973) have established a number of inequalities for multipartite quantum states (strong subadditivity and weak monotonicity). We give a finite set of instances of these inequalities that is complete (in the sense that any valid linear inequality for allocations of entropy can be deduced from them by taking positive linear combinations) and independent (in the sense that none of them can be deduced from the others by taking positive linear combinations). Let Bn denote the polyhedral cone in Rν determined by these inequalities. We show that A~n~=Bn for n≤3. The status of this equality is open for n≥4. We also consider a symmetric version of this situation, in which S(ρI) depends on I only through the number i=≠I of indexes in I and can thus be denoted S(ρi). In this case, we give for each n a finite complete and independent set of inequalities governing the symmetric allocations of entropy {S(ρi)}0≤i≤n in Rn+1.

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© 2003 IEEE