Strong converse exponents for a quantum channel discrimination problem and quantum-feedback-assisted communication

TL;DR

This paper establishes the optimal strong converse exponents for quantum channel discrimination involving replacer channels, demonstrating the asymptotic optimality of non-adaptive strategies and refining the understanding of quantum-feedback-assisted capacity.

Contribution

It proves a quantum Stein's lemma for this setting, identifies the optimal strong converse exponent, and links the mutual information to the error exponent in channel discrimination.

Findings

Adaptive strategies offer no asymptotic advantage over non-adaptive tensor-power strategies.

The strong converse exponent for channel discrimination is explicitly characterized.

The mutual information of a quantum channel equals the optimal type II error exponent in worst-case discrimination.

Abstract

This paper studies the difficulty of discriminating between an arbitrary quantum channel and a "replacer" channel that discards its input and replaces it with a fixed state. We show that, in this particular setting, the most general adaptive discrimination strategies provide no asymptotic advantage over non-adaptive tensor-power strategies. This conclusion follows by proving a quantum Stein's lemma for this channel discrimination setting, showing that a constant bound on the Type I error leads to the Type II error decreasing to zero exponentially quickly at a rate determined by the maximum relative entropy registered between the channels. The strong converse part of the lemma states that any attempt to make the Type II error decay to zero at a rate faster than the channel relative entropy implies that the Type I error necessarily converges to one. We then refine this latter result by identifying the optimal strong converse exponent for this task. As a consequence of these results, we can establish a strong converse theorem for the quantum-feedback-assisted capacity of a channel, sharpening a result due to Bowen. Furthermore, our channel discrimination result demonstrates the asymptotic optimality of a non-adaptive tensor-power strategy in the setting of quantum illumination, as was used in prior work on the topic. The sandwiched Renyi relative entropy is a key tool in our analysis. Finally, by combining our results with recent results of Hayashi and Tomamichel, we find a novel operational interpretation of the mutual information of a quantum channel N as the optimal type II error exponent when discriminating between a large number of independent instances of N and an arbitrary "worst-case" replacer channel chosen from the set of all replacer channels.