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arXiv:1207.0086

Semispectral Measures and Feller markov Kernels

Roberto Beneduci

Published Jun 30, 2012• 3 citations
arXivHTMLPDF

Abstract

We give a characterization of commutative semispectral measures by means of Feller and Strong Feller Markov kernels. In particular: {itemize} we show that a semispectral measure $F$ is commutative if and only if there exist a self-adjoint operator $A$ and a Markov kernel $μ_{(\cdot)}(\cdot):Γ\times\mathcal{B}(\mathbb{R})\to[0,1]$, $Γ\subsetσ(A)$, $E(Γ)=\mathbf{1}$, such that $$F(Δ)=\int_Γμ_Δ(λ)\,dE_λ,$$ \noindent and $μ_{(Δ)}$ is continuous for each $Δ\in R$ where, $R\subset\mathcal{B}(\mathbb{R})$ is a ring which generates the Borel $σ$-algebra of the reals $\mathcal{B}(\mathbb{R})$. Moreover, $μ_{(\cdot)}(\cdot)$ is a Feller Markov kernel and separates the points of $Γ$. we prove that $F$ admits a strong Feller Markov kernel $μ_{(\cdot)}(\cdot)$, if and only if $F$ is uniformly continuous. Finally, we prove that if $F$ is absolutely continuous with respect to a regular finite measure $ν$ then, it admits a strong Feller Markov kernel. {itemize} The mathematical and physical relevance of the results is discussed giving a particular emphasis to the connections between $μ$ and the imprecision of the measurement apparatus.

DOI
10.48550/arxiv.1207.0086

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We give a characterization of commutative semispectral measures by means of Feller and Strong Feller Markov kernels. In particular: {itemize} we show that a semispectral measure FFF is commutative if and only if there exist a self-adjoint operator AAA and a Markov kernel μ(⋅)(⋅):Γ×B(R)→[0,1]μ_{(\cdot)}(\cdot):Γ\times\mathcal{B}(\mathbb{R})\to[0,1]μ(⋅)​(⋅):Γ×B(R)→[0,1], Γ⊂σ(A)Γ\subsetσ(A)Γ⊂σ(A), E(Γ)=1E(Γ)=\mathbf{1}E(Γ)=1, such that F(Δ)=∫ΓμΔ(λ) dEλ,F(Δ)=\int_Γμ_Δ(λ)\,dE_λ,F(Δ)=∫Γ​μΔ​(λ)dEλ​, \noindent and μ(Δ)μ_{(Δ)}μ(Δ)​ is continuous for each Δ∈RΔ\in RΔ∈R where, R⊂B(R)R\subset\mathcal{B}(\mathbb{R})R⊂B(R) is a ring which generates the Borel σσσ-algebra of the reals B(R)\mathcal{B}(\mathbb{R})B(R). Moreover, μ(⋅)(⋅)μ_{(\cdot)}(\cdot)μ(⋅)​(⋅) is a Feller Markov kernel and separates the points of ΓΓΓ. we prove that FFF admits a strong Feller Markov kernel μ(⋅)(⋅)μ_{(\cdot)}(\cdot)μ(⋅)​(⋅), if and only if FFF is uniformly continuous. Finally, we prove that if FFF is absolutely continuous with respect to a regular finite measure ννν then, it admits a strong Feller Markov kernel. {itemize} The mathematical and physical relevance of the results is discussed giving a particular emphasis to the connections between μμμ and the imprecision of the measurement apparatus.
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Abstract In Kiukas, Lahti, and Ylinen (2006, Journal of Mathematical Physics 47, 072104), the authors asked the following general question. When is a positive operator measure projection valued? A version of this question formulated in terms of operator moments was posed in Pietrzycki and Stochel (2021, Journal of Functional Analysis 280, 109001). Let T be a self-adjoint operator, and let F be a Borel semispectral measure on the real line with compact support. For which positive integers p<qp< qp<q do the equalities Tk=∫RxkF(dx)T^k =\int _{\mathbb {R}} x^k F(\mathrm {d\hspace {.1ex}} x)Tk=∫R​xkF(dx) , k=p,qk=p, qk=p,q , imply that F is a spectral measure? In the present paper, we completely solve the second problem. The answer is affirmative if ppp is odd and qqq is even, and negative otherwise. The case (p,q)=(1,2)(p,q)=(1,2)(p,q)=(1,2) closely related to intrinsic noise operator was solved by several authors including Kruszyński and de Muynck, as well as Kiukas, Lahti, and Ylinen. The counterpart of the second problem concerning the multiplicativity of unital positive linear maps on C∗C^*C∗ -algebras is also provided.
We study two relevant characterizations of a commutative positive operator valued measure (POVM) F . The first one is a Choquet type of an integral representation. It introduces a measure ν on the space of the projection valued measures (PVMs) and describes F as an integral over this space. The second one represents a commutative POVM F as the randomization of a single PVM E by means of a Markov kernel μ . We show that one can be derived from the other. We also elaborate upon some previous results on Choquet’s representation of Markov kernels and find a functional relationship between ν and μ . Finally, we analyze some relevant particular cases and provide some physically relevant examples which include the unsharp position observables.