Conditional expectation and Bayes' rule for quantum random variables and positive operator valued measures

TL;DR

This paper develops a mathematical framework for quantum probability measures and random variables, introducing quantum expectation, change of measure, and a quantum Bayes' rule to deepen understanding of quantum probabilistic structures.

Contribution

It introduces a quantum analogue of expectation, change of measure, and Bayes' rule, advancing the mathematical foundation of quantum probability theory.

Findings

Defined quantum expectation for quantum random variables

Proved quantum Radon-Nikodym derivative identities

Formulated a quantum Bayes' rule

Abstract

A quantum probability measure is a function on a sigma-algebra of subsets of a (locally compact and Hausdorff) sample space that satisfies the formal requirements for a measure, but whose values are positive operators acting on a complex Hilbert space, and a quantum random variable is a measurable operator valued function. Although quantum probability measures and random variables are used extensively in quantum mechanics, some of the fundamental probabilistic features of these structures remain to be determined. In this paper we take a step toward a better mathematical understanding of quantum random variables and quantum probability measures by introducing a quantum analogue for the expected value of a quantum random variable relative to a quantum probability measure. In so doing we are led to theorems for a change of quantum measure and a change of quantum variables. We also introduce a quantum conditional expectation which results in quantum versions of some standard identities for Radon-Nikodym derivatives. This allows us to formulate and prove a quantum analogue of Bayes' rule.