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  2. Positive linear functional - Wikipedia

    en.wikipedia.org/wiki/Positive_linear_functional

    The significance of positive linear functionals lies in results such as Riesz–Markov–Kakutani representation theorem. When V {\displaystyle V} is a complex vector space, it is assumed that for all v ≥ 0 , {\displaystyle v\geq 0,} f ( v ) {\displaystyle f(v)} is real.

  3. Gelfand–Naimark–Segal construction - Wikipedia

    en.wikipedia.org/wiki/Gelfand–Naimark–Segal...

    Any positive linear functionals on dominated by is of the form = (), for some positive operator in () ′ with in the operator order. This is a version of the Radon–Nikodym theorem . For such g {\displaystyle g} , one can write f {\displaystyle f} as a sum of positive linear functionals: f = g + g ′ {\displaystyle f=g+g'} .

  4. State (functional analysis) - Wikipedia

    en.wikipedia.org/wiki/State_(functional_analysis)

    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 . A {\displaystyle A} can be viewed as a closed linear subspace of C ( Ω ) {\displaystyle C(\Omega )} (this is Kadison 's function representation ).

  5. Von Neumann algebra - Wikipedia

    en.wikipedia.org/wiki/Von_Neumann_algebra

    A weight ω on a von Neumann algebra is a linear map from the set of positive elements (those of the form a*a) to [0,∞]. A positive linear functional is a weight with ω(1) finite (or rather the extension of ω to the whole algebra by linearity). A state is a weight with ω(1) = 1. A trace is a weight with ω(aa*) = ω(a*a) for all a.

  6. Density matrix - Wikipedia

    en.wikipedia.org/wiki/Density_matrix

    [27] [28] For this reason, observables are identified with elements of an abstract C*-algebra A (that is one without a distinguished representation as an algebra of operators) and states are positive linear functionals on A. However, by using the GNS construction, we can recover Hilbert spaces that realize A as a subalgebra of operators.

  7. Riesz–Markov–Kakutani representation theorem - Wikipedia

    en.wikipedia.org/wiki/Riesz–Markov–Kakutani...

    Finally, is positive if and only if the measure is positive. One can deduce this statement about linear functionals from the statement about positive linear functionals by first showing that a bounded linear functional can be written as a finite linear combination of positive ones.

  8. Continuous functions on a compact Hausdorff space - Wikipedia

    en.wikipedia.org/wiki/Continuous_functions_on_a...

    Positive linear functionals on () correspond to (positive) regular Borel measures on , by a different form of the Riesz representation theorem. ( Rudin 1966 , Chapter 2) If X {\displaystyle X} is infinite, then C ( X ) {\displaystyle {\mathcal {C}}(X)} is not reflexive , nor is it weakly complete .

  9. Order dual (functional analysis) - Wikipedia

    en.wikipedia.org/wiki/Order_dual_(functional...

    In mathematics, specifically in order theory and functional analysis, the order dual of an ordered vector space is the set ⁡ ⁡ where ⁡ denotes the set of all positive linear functionals on , where a linear function on is called positive if for all , implies () [1] The order dual of is denoted by +.