Quantum and classical probability as Bayes-optimal observation
Sven Aerts

TL;DR
This paper introduces a formal framework where Bayes-optimal observation explains quantum probabilities, deriving the Born rule and providing an interpretation of single measurement outcomes as least dependent on the observer's state.
Contribution
It presents a novel formalization of observation that unifies classical and quantum probability through Bayes-optimality, deriving the Born rule from first principles.
Findings
Bayes-optimal observation reproduces the Born rule in quantum mechanics.
The outcome assignment is invariant under unitary transformations.
Single outcomes are least dependent on the observer's state, providing an interpretation of measurement results.
Abstract
We propose a simple abstract formalisation of the act of observation, in which the system and the observer are assumed to be in a pure state and their interaction deterministically changes the states such that the outcome can be read from the state of the observer after the interaction. If the observer consistently realizes the outcome which maximizes the likelihood ratio that the outcome pertains to the system under study (and not to his own state), he will be called Bayes-optimal. We calculate the probability if for each trial of the experiment the observer is in a new state picked randomly from his set of states, and the system under investigation is taken from an ensemble of identical pure states. For classical statistical mixtures, the relative frequency resulting from the maximum likelihood principle is an unbiased estimator of the components of the mixture. For repeated…
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Taxonomy
TopicsQuantum Mechanics and Applications · Quantum Information and Cryptography · Advanced Thermodynamics and Statistical Mechanics
