Improving error suppression with noise-aware decoding

TL;DR

This paper shows that calibrating quantum error correction decoders to the specific noise characteristics of a device significantly improves error suppression, making fault-tolerant quantum computing more practical.

Contribution

The authors introduce a noise-aware decoding protocol that uses circuit-level noise characterization for improved quantum error correction performance.

Findings

Noise-aware decoding increases error suppression exponentially with code distance.

Calibration can be performed rapidly, within seconds, on superconducting quantum computers.

The method approaches near-optimal decoding performance based on the true noise model.

Abstract

We demonstrate that the performance of quantum error correction can be improved with noise-aware decoders that are calibrated to the likelihood of physical error configurations in a device. We show that noise-aware decoding increases the error suppression factor of the surface code, yielding reductions in the logical error rate that increase exponentially with the code distance. Our calibration protocol involves circuit-level Pauli noise characterisation experiments with averaged circuit eigenvalue sampling. This enables decoder calibration at the scales required for fault-tolerant quantum computation and near-optimal decoding when compared to the true noise model. Our results indicate that these noise characterisation experiments could be performed and processed in seconds for superconducting quantum computers. This establishes the practicality and utility of noise-aware decoding for quantum error correction at scale.