Recoverability for optimized quantum $f$-divergences
Li Gao, Mark M. Wilde

TL;DR
This paper introduces refined data-processing inequalities for optimized quantum f-divergences, linking distinguishability measures to recoverability of quantum states, with implications for quantum reversibility and extensions to von Neumann algebras.
Contribution
The work provides new physically meaningful refinements of the data-processing inequality for optimized quantum f-divergences, including the sandwiched Rényi entropy, and extends results to general von Neumann algebras.
Findings
Refined bounds relate divergence differences to recovery accuracy.
Implications for quantum sufficiency and perfect reversibility.
Extension of results to infinite-dimensional von Neumann algebra settings.
Abstract
The optimized quantum -divergences form a family of distinguishability measures that includes the quantum relative entropy and the sandwiched R\'enyi relative quasi-entropy as special cases. In this paper, we establish physically meaningful refinements of the data-processing inequality for the optimized -divergence. In particular, the refinements state that the absolute difference between the optimized -divergence and its channel-processed version is an upper bound on how well one can recover a quantum state acted upon by a quantum channel, whenever the recovery channel is taken to be a rotated Petz recovery channel. Not only do these results lead to physically meaningful refinements of the data-processing inequality for the sandwiched R\'enyi relative entropy, but they also have implications for perfect reversibility (i.e., quantum sufficiency) of the optimized…
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