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This paper advances the theoretical foundations of quantum inference by extending Bayesian retrodiction axioms from finite-dimensional systems to infinite-dimensional von Neumann algebras. It critically examines whether the Petz recovery map is a unique structural necessity or merely an algorithmic tool within this broader mathematical framework. Such foundational work is essential for developing robust, scalable quantum machine learning models that operate beyond current qubit limitations.
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Bayesian inference and retrodiction for faithful states on von Neumann algebras

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arXiv:2608.20001v1 Announce Type: cross Abstract: Retrodiction is the act of inferring a cause from its effects, the most common example of which is Bayesian inference. Retrodiction can be defined by its structural process-theoretic properties, which are mathematically captured by category theory. This categorical definition of retrodiction has recently been shown to potentially isolate the Petz recovery map as a unique universal candidate for quantum Bayesian inference. This paper extends these results to the infinite-dimensional setting on von Neumann algebras. In the process, we provide a pedagogical review of the Petz recovery map in infinite dimensions and its relation to the more commonly used expression in the finite-dimensional setting. We formalize the open question as to whether these categorical axioms for retrodiction do in fact uniquely characterize the Petz recovery map. If such a characterization holds, this would show that Bayesian inversion and the Petz recovery map are structural necessities and not simply useful algorithms for classical and quantum inference.

Abstract:Retrodiction is the act of inferring a cause from its effects, the most common example of which is Bayesian inference. Retrodiction can be defined by its structural process-theoretic properties, which are mathematically captured by category theory. This categorical definition of retrodiction has recently been shown to potentially isolate the Petz recovery map as a unique universal candidate for quantum Bayesian inference. This paper extends these results to the infinite-dimensional setting on von Neumann algebras. In the process, we provide a pedagogical review of the Petz recovery map in infinite dimensions and its relation to the more commonly used expression in the finite-dimensional setting. We formalize the open question as to whether these categorical axioms for retrodiction do in fact uniquely characterize the Petz recovery map. If such a characterization holds, this would show that Bayesian inversion and the Petz recovery map are structural necessities and not simply useful algorithms for classical and quantum inference.

Comments are welcome! 30 pages + appendix + bibliography

Operator Algebras (math.OA); Category Theory (math.CT); Quantum Physics (quant-ph)

arXiv:2608.20001 [math.OA]

(or arXiv:2608.20001v1 [math.OA] for this version)

https://doi.org/10.48550/arXiv.2608.20001 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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