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arXiv:2509.22594

Quantum Measurement Trees, I: Two Preliminary Examples of Induced Contextual Boolean Algebras

Peter J. Hammond

Published Sep 26, 2025• 0 citations
arXivHTMLPDF

Abstract

Quantum randomness evidently transcends the classical framework of random variables defined on a single comprehensive Kolmogorov probability space. One prominent example is the quantum double-slit experiment due to Feynman (1951, 1966). A related non-quantum example, inspired by Boole (1862) and Vorob$'$ev (1962), has three two-valued random variables $X$, $Y$ and $Z$, where the pairs $X, Y$ and $X, Z$ are perfectly correlated, yet $Y, Z$ are perfectly anti-correlated. Such examples can be accommodated using a ``multi-measurable'' space with several different $ σ$-algebras of measurable events. This concept due to Vorob$'$ev (1962) allows construction of: 1) a measurable meta\-space whose elements combine a point in the original sample space with a variable ``contextual'' Boolean algebra; 2) a parametric family of probability meta\-spaces, each of which is a Kolmogorov probability space that represents a two-stage stochastic process where a random choice from the original sample space is preceded by the random choice of a contextual Boolean algebra in the multi-measurable space. Subsequent work will explore how quantum experimental results can be described using a quantum measurement tree with one or more preparation nodes where an experimental configuration is determined that governs the probability distribution of relevant quantum observables.

DOI
10.48550/arxiv.2509.22594

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Quantum randomness evidently transcends the classical framework of random variables defined on a single comprehensive Kolmogorov probability space. One prominent example is the quantum double-slit experiment due to Feynman (1951, 1966). A related non-quantum example, inspired by Boole (1862) and Vorob′'′ev (1962), has three two-valued random variables XXX, YYY and ZZZ, where the pairs X,YX, YX,Y and X,ZX, ZX,Z are perfectly correlated, yet Y,ZY, ZY,Z are perfectly anti-correlated. Such examples can be accommodated using a multi-measurable'' space with several different $ σ$-algebras of measurable events. This concept due to Vorob$'$ev (1962) allows construction of: 1) a measurable meta\-space whose elements combine a point in the original sample space with a variable contextual'' Boolean algebra; 2) a parametric family of probability meta-spaces, each of which is a Kolmogorov probability space that represents a two-stage stochastic process where a random choice from the original sample space is preceded by the random choice of a contextual Boolean algebra in the multi-measurable space. Subsequent work will explore how quantum experimental results can be described using a quantum measurement tree with one or more preparation nodes where an experimental configuration is determined that governs the probability distribution of relevant quantum observables.
Quantum randomness evidently transcends the classical framework of random variables defined on a single comprehensive Kolmogorov probability space. One prominent example is the quantum double-slit experiment owing to Feynman (Feynman 1951 In Second Berkeley Symposium on Mathematical Statistics and Probability (ed. J. Neyman), pp. 533-541 (doi:10.1525/9780520411586-039)). A related non-quantum example, inspired by Boole (Boole 1862 Phil. Trans. R. Soc. Lond. 152, 225-252 (doi:10.1098/rstl.1862.0015)) and Vorob'ev (Vorob'ev 1962 Theory Probab. Appl.7, 147-163 (doi:10.1137/1107014)), has three two-valued random variables X, Y and Z, where the pairs X, Y and X, Z are perfectly correlated, yet Y, Z are perfectly anti-correlated. Such examples can be accommodated using a 'multi-measurable' space with several different sigma-algebras of measurable events. This concept, owing to Vorob'ev (Vorob'ev 1962 Theory Probab. Appl.7, 147-163 (doi:10.1137/1107014)), allows construction of (i) a measurable metaspace whose elements combine a point in the original sample space with a variable 'contextual' Boolean algebra; (ii) a parametric family of 'probability metaspaces', each of which is a Kolmogorov probability space that represents a two-stage stochastic process where a random choice from the original sample space is preceded by the random choice of a contextual Boolean algebra in the multi-measurable space. Subsequent work will explore how quantum experimental results can be described using a quantum measurement tree with one or more preparation nodes, where an experimental configuration is determined that governs the probability distribution of relevant quantum observables. This article is part of the theme issue 'Quantum theory and topology in models of decision making (Part 2)'.
Kolmogorov's foundation of probability takes measure spaces, σσσ-algebras, and probability measures as basic objects. It is, however, widely recognized that this classical framework is inadequate for random phenomena involving quantum effects, and more generally for \emph{quantum-like} situations. A broader formulation is provided by an algebraic viewpoint: one starts from an algebra of random variables equipped with a distinguished linear functional -- the \emph{state} -- interpreted as expectation. In this sense, the approach can also be viewed as a modern reading of ideas already implicit in early probability (e.g., the Bernoullis), while its contemporary form has been developed and used extensively in quantum physics. The algebraic framework accommodates both classical and quantum-like behaviours, yet it remains underused in classical probability and uncertainty quantification, where it can nevertheless open new perspectives and clarify structural features. Although the language carries a physics flavor, the subject is purely probabilistic. The key distinction between classical and quantum-like behaviour is \emph{commutativity}: its failure produces the characteristic effects of quantum-like situations. The rise of quantum computing is a prominent setting in which such behaviour may become relevant even for practitioners in computational science. Here we focus on the purely algebraic core of the approach. By restricting attention to finite-dimensional algebras, we avoid many analytical subtleties while retaining the main ideas, their classical limit, and their applicability to quantum-like models and quantum computation.
The main aim of this report is to inform the quantum information community about investigations on the problem of probabilistic compatibility of a family of random variables: a possibility to realize such a family on the basis of a single probability measure (to construct a single Kolmogorov probability space). These investigations were started hundred of years ago by J. Boole (who invented Boolean algebras). The complete solution of the problem was obtained by Soviet mathematician Vorobjev in 60th. Surprisingly probabilists and statisticians obtained inequalities for probabilities and correlations among which one can find the famous Bell's inequality and its generalizations. Such inequalities appeared simply as constraints for probabilistic compatibility. In this framework one can not see a priori any link to such problems as nonlocality and "death of reality" which are typically linked to Bell's type inequalities in physical literature. We analyze the difference between positions of mathematicians and quantum physicists. In particular, we found that one of the most reasonable explanations of probabilistic incompatibility is mixing in Bell's type inequalities statistical data from a number of experiments performed under different experimental contexts.
We demonstrate that the contextual approach to Kolmogorov probability model gives the possibility to unify this conventional model of probability with the quantum (Hilbert space) probability model. In fact, the Kolmogorov model can exhibit all distinguishing features of the quantum probability model. In particular, by using the contextual (interference) formula of total probability one can construct complex amplitudes of Kolmogorov probabilities. There exists a natural Hilbert space structure on the space of those complex amplitudes. Classical (Kolmogorovian) random variables are represented by in general noncommutative operators in the Hilbert space of complex amplitudes. The existence of such a contextual representation of the Kolmogorovian model looks very surprising in the view of the orthodox quantum tradition. Supported by EU-network “Quantum Probability and Applications”.
Since 1933, when Kolmogorov laid the foundations for probability and statistics as we know them today [1], it has been recognized that propositions asserting that such and such an event occurred as a consequence of the execution of a particular random experiment tend to band together and form a Boolean algebra. In 1936, Birkhoff and von Neumann [2] suggested that the so-called logic of quantum mechanics should not be a Boolean algebra, but rather should form what is now called a modular ortholattice [3]. Presumably, the departure from Boolean algebras encountered in quantum mechanics can be attributed to the fact that in quantum mechanics, one must consider more than one physical experiment, e.g., an experiment measuring position, an experiment measuring charge, an experiment measuring momentum, etc., and, because of the uncertainty principle, these experiments need not admit a common refinement in terms of which the Kolmogorov theory is directly applicable. Mackey's Axioms I–VI for quantum mechanics [4] imply that the logic of quantum mechanics should be a σ-orthocomplete orthomodular poset [5]. Most contemporary practitioners of quantum logic seem to agree that a quantum logic is (at least) an orthomodular poset [6], [7], [8], [9], [10] or some variation thereof [11]. P. D. Finch [12] has shown that every completely orthomodular poset is the logic arising from sets of Boolean logics, where these sets have a structure similar to the structures generally given to quantum logic. In all of these versions of quantum logic, a fundamental relation, the relation of compatibility or commutativity, plays a decisive role.