Sampling-based quasiprobability simulation for fault-tolerant quantum error correction on the surface codes under coherent noise

We propose a sampling-based simulation for fault-tolerant quantum error correction under coherent noise. A mixture of incoherent and coherent noise, possibly due to over-rotation, is decomposed into Clifford channels with a quasiprobability distribution. Then, an unbiased estimator of the logical error probability is constructed by sampling Clifford channels with an appropriate postprocessing. We characterize the sampling cost via the channel robustness and find that the proposed sampling-based method is feasible even for planar surface codes with relatively large code distances intractable for full state-vector simulations. As a demonstration, we simulate repetitive faulty syndrome measurements on the planar surface code of distance 5 with 81 qubits. We find that the coherent error increases the logical error rate. This is a practical application of the quasiprobability simulation for a meaningful task and would be useful to explore experimental quantum error correction on the near-term quantum devices.

Automated summary

This study proposes a sampling-based simulation method for fault-tolerant quantum error correction under coherent noise. By sampling Clifford channels and conducting appropriate postprocessing, an unbiased estimator of the logical error probability is constructed. The research finds that the proposed method is feasible even for relatively large code distances of planar surface codes compared to full state-vector simulations.