On approximate quantum error correction for symmetric noise

TL;DR

This paper enhances approximate quantum error correction by introducing a measurement-based scheme for extracting good encoder-decoder pairs and employs symmetry-based dimension reduction to improve computational efficiency, bridging theory and practice.

Contribution

It introduces a measurement-based rounding scheme for AQEC and combines noise and permutational symmetries for efficient hierarchy evaluation.

Findings

Effective extraction of encoder-decoder pairs from the hierarchy.

Symmetry-based dimension reduction improves computational feasibility.

Numerical examples demonstrate practical effectiveness.

Abstract

We revisit the extendability-based semi-definite programming hierarchy introduced by Berta et al. [Mathematical Programming, 1 - 49 (2021)], which provides converging outer bounds on the optimal fidelity of approximate quantum error correction (AQEC). As our first contribution, we introduce a measurement-based rounding scheme that extracts inner sequences of certifiably good encoder-decoder pairs from this outer hierarchy. To address the computational complexity of evaluating fixed levels of the hierarchy, we investigate the use of symmetry-based dimension reduction. In particular, we combine noise symmetries - such as those present in multiple copies of the qubit depolarizing channel - with the permutational symmetry arising from the extendability of the optimization variable. This framework is illustrated through basic, but already challenging numerical examples that showcase its practical effectiveness. Our results contribute to narrowing the gap between theoretical developments in quantum information theory and their practical applications in the analysis of small-scale quantum error-correcting codes.