Ultrahigh Error Threshold for Surface Codes with Biased Noise. (arXiv:1708.08474v3 [quant-ph] UPDATED)

We show that a simple modification of the surface code can exhibit an
enormous gain in the error correction threshold for a noise model in which
Pauli Z errors occur more frequently than X or Y errors. Such biased noise,
where dephasing dominates, is ubiquitous in many quantum architectures. In the
limit of pure dephasing noise we find a threshold of 43.7(1)% using a tensor
network decoder proposed by Bravyi, Suchara and Vargo. The threshold remains
surprisingly large in the regime of realistic noise bias ratios, for example
28.2(2)% at a bias of 10. The performance is in fact at or near the hashing
bound for all values of the bias. The modified surface code still uses only
weight-4 stabilizers on a square lattice, but merely requires measuring
products of Y instead of Z around the faces, as this doubles the number of
useful syndrome bits associated with the dominant Z errors. Our results
demonstrate that large efficiency gains can be found by appropriately tailoring
codes and decoders to realistic noise models, even under the locality
constraints of topological codes.

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