Generalized quantum asymptotic equipartition
Kun Fang, Hamza Fawzi, Omar Fawzi

TL;DR
This paper extends the quantum asymptotic equipartition property to non-i.i.d. quantum state sets, providing convergence guarantees, efficient estimation methods, and implications for quantum hypothesis testing and resource theories.
Contribution
It introduces a generalized quantum AEP for non-i.i.d. sets, establishing convergence of divergences to the quantum relative entropy with practical estimation methods.
Findings
Quantum divergences converge to the relative entropy between sets.
Efficient convex optimization methods for estimation.
New framework for robust quantum resource theory.
Abstract
The asymptotic equipartition property (AEP) states that in the limit of a large number of independent and identically distributed (i.i.d.) random experiments, the output sequence is virtually certain to come from the typical set, each member of which is almost equally likely. This property is a form of the law of large numbers and lies at the heart of information theory. In this work, we prove a generalized quantum AEP beyond the i.i.d. framework where the random samples are drawn from two sets of quantum states. In particular, under suitable assumptions on the sets, we prove that all operationally relevant divergences converge to the quantum relative entropy between the sets. More specifically, both the quantum hypothesis testing relative entropy (a smoothed form of the min-relative entropy) and the smoothed max-relative entropy approach the regularized relative entropy between the…
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Taxonomy
TopicsStochastic Gradient Optimization Techniques · Adversarial Robustness in Machine Learning · Wireless Communication Security Techniques
