1. Ultrahigh Error Threshold for Surface Codes with Biased Noise
- Author
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Massachusetts Institute of Technology. Laboratory for Nuclear Science, Flammia, Steven Thomas, Tuckett, David K., Bartlett, Stephen D., Massachusetts Institute of Technology. Laboratory for Nuclear Science, Flammia, Steven Thomas, Tuckett, David K., and Bartlett, Stephen D.
- Abstract
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., United States. Army Research Office (Grant W911NF-14-1-0098), Australian Research Council (Project CE110001013), Australian Research Council (Future Fellowship FT130101744), United States. Army Research Office (Grant W911NF-14-1-0103)
- Published
- 2018