Quantum Network Discrimination

TL;DR

This paper investigates the fundamental limits of discriminating complex quantum networks, especially superchannels, and explores strategies, bounds, and applications like quantum illumination.

Contribution

It introduces a framework for quantum network discrimination, providing bounds, strategies, and extending the theory beyond simple channels to complex networks.

Findings

Fundamental bounds on asymptotic discrimination rates for quantum superchannels.

Analysis of strategies and the strong converse exponent in network discrimination.

Application to active quantum illumination problem.

Abstract

Discrimination between objects, in particular quantum states, is one of the most fundamental tasks in (quantum) information theory. Recent years have seen significant progress towards extending the framework to point-to-point quantum channels. However, with technological progress the focus of the field is shifting to more complex structures: Quantum networks. In contrast to channels, networks allow for intermediate access points where information can be received, processed and reintroduced into the network. In this work we study the discrimination of quantum networks and its fundamental limitations. In particular when multiple uses of the network are at hand, the rooster of available strategies becomes increasingly complex. The simplest quantum network that capturers the structure of the problem is given by a quantum superchannel. We discuss the available classes of strategies when considering $n$ copies of a superchannel and give fundamental bounds on the asymptotically achievable rates in an asymmetric discrimination setting. Furthermore, we discuss achievability, symmetric network discrimination, the strong converse exponent, generalization to arbitrary quantum networks and finally an application to an active version of the quantum illumination problem.