Descrições efetivas em mecânica quântica: um problema de inferência bayesiana

Abstract

Throughout the years, various efforts have been made to reinterpret quantum mechanics from new perspectives. This work relies upon the approach that frames quantum theory as a generalized formalism for Bayesian inference. Although this standpoint revives the old debate about quantum logic, it nonetheless takes seriously the idea that there are other forms of probabilistic assignments—other than the classical ones. Our study embeds the conventional coarse-graining problem within a Bayesian inference setting. We investigate whether generalized inference techniques can be employed to establish necessary and sufficient conditions for the emergence of macroscopic quantum dynamics. As this abstract already hints, we will see that the quantum inference framework, as usually proposed, has its limitations. Furthermore, we will explore how Petz’s recovery maps can potentially circumvent these limitations, to find an optimal (in a certain sense) emergent map that remains consistent with the problem across virtually any coarse-graining scenario.