Improving quantum communication rates with permutation-invariant codes

TL;DR

This paper enhances quantum communication rates by using permutation-invariant codes and representation theory to compute channel capacities, leading to improved bounds on quantum capacity thresholds for various channels.

Contribution

It introduces a novel method leveraging symmetry and representation theory to efficiently compute quantum channel coherent information, improving capacity bounds for multiple channel models.

Findings

Improved lower bounds on quantum capacities for several channels.

Significant enhancement of quantum capacity thresholds for 2-Pauli and BB84 channels.

Efficient algorithm for computing coherent information using symmetry properties.

Abstract

In this work we improve the quantum communication rates of various quantum channels of interest using permutation-invariant quantum codes. We focus in particular on parametrized families of quantum channels and aim to improve bounds on their quantum capacity threshold, defined as the lowest noise level at which the quantum capacity of the channel family vanishes. These thresholds are important quantities as they mark the noise level up to which faithful quantum communication is theoretically possible. Our method exploits the fact that independent and identically distributed quantum channels preserve any permutation symmetry present at the input. The resulting symmetric output states can be described succinctly using the representation theory of the symmetric and general linear groups, which we use to derive an efficient algorithm for computing the channel coherent information of a permutation-invariant code. Our approach allows us to evaluate coherent information values for a large number of channel copies, e.g., at least 100 channel copies for qubit channels. We apply this method to various physically relevant channel models, including general Pauli channels, the dephrasure channel, the generalized amplitude damping channel, and the damping-dephasing channel. For each channel family we obtain improved lower bounds on their quantum capacities. For example, for the 2-Pauli and BB84 channel families we significantly improve the best known quantum capacity thresholds derived in [Fern, Whaley 2008]. These threshold improvements are achieved using a repetition code-like input state with non-orthogonal code states, which we further analyze in our representation-theoretic framework.