The XZZX surface code

Unknown author(s)

Nature Communications · 2021 · 247 citations · 56 references

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TL;DR

Fault‑tolerant quantum computing requires quantum error‑correcting codes for large‑scale calculations. The study aims to design practical quantum error‑correcting codes that perform well against realistic noise with modest resources. The authors show that tailoring a code to the noise structure yields favourable sub‑threshold resource scaling. The XZZX surface code achieves a universal error threshold matching the hashing bound for all single‑qubit Pauli noise, exceeds it for realistic noise ranges, and, with a practical decoder, surpasses prior thresholds even with unreliable syndrome measurements, while preserving these benefits in fault‑tolerant computation.

Abstract

Performing large calculations with a quantum computer will likely require a fault-tolerant architecture based on quantum error-correcting codes. The challenge is to design practical quantum error-correcting codes that perform well against realistic noise using modest resources. Here we show that a variant of the surface code-the XZZX code-offers remarkable performance for fault-tolerant quantum computation. The error threshold of this code matches what can be achieved with random codes (hashing) for every single-qubit Pauli noise channel; it is the first explicit code shown to have this universal property. We present numerical evidence that the threshold even exceeds this hashing bound for an experimentally relevant range of noise parameters. Focusing on the common situation where qubit dephasing is the dominant noise, we show that this code has a practical, high-performance decoder and surpasses all previously known thresholds in the realistic setting where syndrome measurements are unreliable. We go on to demonstrate the favourable sub-threshold resource scaling that can be obtained by specialising a code to exploit structure in the noise. We show that it is possible to maintain all of these advantages when we perform fault-tolerant quantum computation.

References

56