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

TL;DR

This paper introduces a sampling-based method for simulating fault-tolerant quantum error correction under coherent noise, enabling analysis of larger surface codes than traditional methods.

Contribution

It presents a novel quasiprobability sampling approach to simulate coherent noise in surface codes, improving feasibility for larger code distances.

Findings

Coherent noise increases logical error rates.

Sampling cost is characterized by channel robustness.

Method enables simulation of larger codes than full state-vector methods.

Abstract

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.