Queue-Channel Capacities with Generalized Amplitude Damping

TL;DR

This paper derives the classical capacity of a symmetric generalized amplitude damping channel and introduces a queue-channel model to analyze the impact of buffering on quantum communication capacity.

Contribution

It provides an exact capacity for the symmetric GAD channel and models the effects of buffering in quantum networks through a novel queue-channel analysis.

Findings

Capacity of symmetric GAD channel equals Shannon capacity of induced BSC.

Capacity can be achieved without entanglement or joint measurements.

Buffering introduces correlated noise, affecting quantum communication capacity.

Abstract

The generalized amplitude damping channel (GADC) is considered an important model for quantum communications, especially over optical networks. We make two salient contributions in this paper apropos of this channel. First, we consider a symmetric GAD channel characterized by the parameter $n=1/2,$ and derive its exact classical capacity, by constructing a specific induced classical channel. We show that the Holevo quantity for the GAD channel equals the Shannon capacity of the induced binary symmetric channel, establishing at once the capacity result and that the GAD channel capacity can be achieved without the use of entanglement at the encoder or joint measurements at the decoder. Second, motivated by the inevitable buffering of qubits in quantum networks, we consider a generalized amplitude damping \emph{queue-channel} -- that is, a setting where qubits suffer a waiting time dependent GAD noise as they wait in a buffer to be transmitted. This GAD queue channel is characterized by non-i.i.d. noise due to correlated waiting times of consecutive qubits. We exploit a conditional independence property in conjunction with additivity of the channel model, to obtain a capacity expression for the GAD queue channel in terms of the stationary waiting time in the queue. Our results provide useful insights towards designing practical quantum communication networks, and highlight the need to explicitly model the impact of buffering.