Siqi Yao, Kun Fang (Oct 03 2025).
Abstract: Recent studies have introduced the worst-case quantum divergence as a key measure in quantum information. Here we show that such divergences can be understood from the perspective of the resource theory of asymmetric distinguishability, which utilizes the asymmetric distinguishability between a pair of quantum states as resource. In our work, we extend this framework to settings with partial information, where the goal is to distinguish between sets of quantum states rather than individual states. Within this setting, we characterize optimal rates for resource distillation and dilution using (smoothed) one-shot divergences and regularized divergences. Our framework further exhibits a reversibility property: resource interconversions can be achieved without loss at rates determined entirely by regularized divergences. These results offer a broad operational interpretation of divergences between state sets and generalize existing resource theories to encompass incomplete information scenarios.
