State (functional analysis)

In functional analysis, a state of an operator system is a positive linear functional of norm 1. States in functional analysis generalize the notion of density matrices in quantum mechanics, which represent quantum states, both mixed states and pure states. Density matrices in turn generalize state vectors, which only represent pure states. For M an operator system in a C*-algebra A with identity, the set of all states of M, sometimes denoted by S(M), is convex, weak-* closed in the Banach dual space M*. Thus the set of all states of M with the weak-* topology forms a compact Hausdorff space, known as the state space of M .

In the C*-algebraic formulation of quantum mechanics, states in this previous sense correspond to physical states, i.e. mappings from physical observables (self-adjoint elements of the C*-algebra) to their expected measurement outcome (real number).

Jordan decomposition

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States can be viewed as noncommutative generalizations of probability measures. By Gelfand representation, every commutative C*-algebra A is of the form C0(X) for some locally compact Hausdorff X. In this case, S(A) consists of positive Radon measures on X, and the pure states are the evaluation functionals on X.

More generally, the GNS construction shows that every state is, after choosing a suitable representation, a vector state.

A bounded linear functional on a C*-algebra A is said to be self-adjoint if it is real-valued on the self-adjoint elements of A. Self-adjoint functionals are noncommutative analogues of signed measures.

The Jordan decomposition in measure theory says that every signed measure can be expressed as the difference of two positive measures supported on disjoint sets. This can be extended to the noncommutative setting.

Theorem — Every self-adjoint   in   can be written as   where   and   are positive functionals and  .

Proof

A proof can be sketched as follows: Let   be the weak*-compact set of positive linear functionals on   with norm ≤ 1, and   be the continuous functions on  .

  can be viewed as a closed linear subspace of   (this is Kadison's function representation). By Hahn–Banach,   extends to a   in   with  .

Using results from measure theory quoted above, one has:

 

where, by the self-adjointness of  ,   can be taken to be a signed measure. Write:

 

a difference of positive measures. The restrictions of the functionals   and   to   has the required properties of   and  . This proves the theorem.

It follows from the above decomposition that A* is the linear span of states.

Some important classes of states

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Pure states

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By the Krein-Milman theorem, the state space of M has extreme points. The extreme points of the state space are termed pure states and other states are known as mixed states.

Vector states

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For a Hilbert space H and a vector x in H, the equation ωx(T) := ⟨Tx,x⟩ (for T in B(H) ), defines a positive linear functional on B(H). Since ωx(1)=||x||2, ωx is a state if ||x||=1. If A is a C*-subalgebra of B(H) and M an operator system in A, then the restriction of ωx to M defines a positive linear functional on M. The states of M that arise in this manner, from unit vectors in H, are termed vector states of M.

Faithful states

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A state   is faithful, if it is injective on the positive elements, that is,   implies  .

Normal states

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A state   is called normal, iff for every monotone, increasing net   of operators with least upper bound  ,   converges to  .

Tracial states

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A tracial state is a state   such that

 

For any separable C*-algebra, the set of tracial states is a Choquet simplex.

Factorial states

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A factorial state of a C*-algebra A is a state such that the commutant of the corresponding GNS representation of A is a factor.

See also

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References

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  • Lin, H. (2001), An Introduction to the Classification of Amenable C*-algebras, World Scientific