Relative-belief inference in quantum information theory
Y. S. Teo, S. U. Shringarpure, H. Jeong, N. Prasannan, B. Brecht, C., Silberhorn, M. Evans, D. Mogilevtsev, and L. L. Sanchez-Soto

TL;DR
This paper introduces a Bayesian relative belief framework for evaluating hypotheses in quantum systems, demonstrating its effectiveness in quantum state reconstruction and model certification using real experimental data.
Contribution
It develops a Bayesian relative belief approach for quantum hypothesis testing, model dimension certification, and state reconstruction, with practical applications to photon source quality assessment.
Findings
The method reliably tracks multiphoton emissions with lossy detectors.
It selects Hilbert space dimensions consistent with information criteria.
The approach can certify models and estimate quantum system dimensions.
Abstract
We introduce the framework of Bayesian relative belief that directly evaluates whether or not the experimental data at hand supports a given hypothesis regarding a quantum system by directly comparing the prior and posterior probabilities for the hypothesis. In model-dimension certification tasks, we show that the relative belief procedure typically chooses Hilbert spaces that are never smaller in dimension than those selected from optimizing a broad class of information criteria, including Akaike's criterion. As a concrete and focused exposition of this powerful evidence-based technique, we apply the relative belief procedure to an important application: state reconstruction of imperfect quantum sources. In particular, just by comparing prior and posterior probabilities based on data, we demonstrate its capability of tracking multiphoton emissions using (realistically lossy)…
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Taxonomy
TopicsStatistical Mechanics and Entropy
