Capacity Region for Quantum Wiretap Coding

TL;DR

This paper reviews classical wiretap coding, then extends the concepts to quantum wiretap coding, providing a capacity region characterized by one-letter information measures and using Bayesian networks for parallel treatment.

Contribution

It offers one of the first comprehensive treatments of quantum wiretap coding, generalizing classical results with a focus on capacity regions and Bayesian network frameworks.

Findings

Capacity region characterized by one-letter information measures.

Parallel treatment of classical and quantum wiretap coding.

Introduction of quantum Bayesian networks for analysis.

Abstract

This paper follows very closely a famous paper by Csisz\'{a}r and K\"{o}rner about classical (non-quantum) wiretap coding. Our paper gives a self-contained and slightly novel review of some important results of the paper by Csisz\'{a}r and K\"{o}rner. Then we present a generalization of those results to the quantum realm, thus giving one of the first half-decent treatments of quantum wiretap coding. Like Csisz\'{a}r and K\"{o}rner, we too find a capacity region (i.e., the maximal achievable region of rates) characterized in terms of one-letter informations. We try to make our treatment of quantum wiretap coding as parallel a possible to our treatment of classical wiretap coding. This parallel treatment is facilitated by the use of CB nets (classical Bayesian networks) for the classical case and QB nets (quantum Bayesian networks) for the quantum one.