A chain rule for the quantum relative entropy

TL;DR

This paper establishes a quantum chain rule for relative entropy, demonstrating that adaptive strategies do not outperform non-adaptive ones in quantum channel discrimination, and shows non-additivity of channel relative entropy.

Contribution

It proves a quantum chain rule inequality for relative entropy and applies it to resolve an open problem in quantum channel discrimination.

Findings

Adaptive protocols do not improve error rates over non-adaptive ones in asymmetric channel discrimination.

Quantum channel relative entropy is not additive under tensor products.

The chain rule facilitates analysis of quantum information tasks.

Abstract

The chain rule for the classical relative entropy ensures that the relative entropy between probability distributions on multipartite systems can be decomposed into a sum of relative entropies of suitably chosen conditional distributions on the individual systems. Here, we prove a similar chain rule inequality for the quantum relative entropy in terms of channel relative entropies. The new chain rule allows us to solve an open problem in the context of asymptotic quantum channel discrimination: surprisingly, adaptive protocols cannot improve the error rate for asymmetric channel discrimination compared to non-adaptive strategies. In addition, we give examples of quantum channels showing that the channel relative entropy is not additive under the tensor product.