基于凸优化的鲁棒量子纠错
Robust Quantum Error Correction via Convex Optimization
摘要:
我们提出了一个半定规划优化方法量子纠错,产生代码和恢复程序,对噪声信道的显着变化是强大的。我们的方法使我们能够优化编码,恢复,或两者兼而有之,并服从近似显着提高计算成本,同时保持保真度。我们使用标准[5,1,3]码作为基准,用数值方法说明了我们的理论。我们优化的编码和恢复产生的一致性是由1-2个数量级的随机酉权重-2错误相比,[5,1,3]与标准恢复代码。我们观察到类似的改善4量子比特消相干的子空间代码。
英文摘要:
We present a semidefinite program optimization approach to quantum error correction that yields codes and recovery procedures that are robust against significant variations in the noise channel. Our approach allows us to optimize the encoding, recovery, or both, and is amenable to approximations that significantly improve computational cost while retaining fidelity. We illustrate our theory numerically for optimized 5-qubit codes, using the standard [5,1,3] code as a benchmark. Our optimized encoding and recovery yields fidelities that are uniformly higher by 1-2 orders of magnitude against random unitary weight-2 errors compared to the [5,1,3] code with standard recovery. We observe similar improvement for a 4-qubit decoherence-free subspace code.
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