论文标题
误差相关性提高变分量子算法的性能的能力
Ability of error correlations to improve the performance of variational quantum algorithms
论文作者
论文摘要
量子近似优化算法（QAOA）具有在嘈杂的中间尺度量子（NISQ）设备上提供有用的量子优势的潜力。不相关的噪声对诸如QAOA等变异量子算法的影响已经进行了深入研究。然而，最近的实验结果表明，影响NISQ设备的误差显着相关。我们基于经典的环境波动器引入了一个空间和时间（非马克维亚）相关错误的模型。该模型允许边缘化时空误差概率和相关强度独立变化。使用此模型，我们研究了相关随机噪声对QAOA的影响。我们发现有证据表明，随着固定局部误差概率的增加，QAOA的性能会提高噪声的相关时间或相关长度。这表明噪声相关本身并不需要对诸如QAOA等NISQ算法有害。
The quantum approximate optimization algorithm (QAOA) has the potential of providing a useful quantum advantage on noisy intermediate-scale quantum (NISQ) devices. The effects of uncorrelated noise on variational quantum algorithms such as QAOA have been studied intensively. Recent experimental results, however, show that the errors impacting NISQ devices are significantly correlated. We introduce a model for both spatially and temporally (non-Markovian) correlated errors based on classical environmental fluctuators. The model allows for the independent variation of the marginalized spacetime-local error probability and the correlation strength. Using this model, we study the effects of correlated stochastic noise on QAOA. We find evidence that the performance of QAOA improves as the correlation time or correlation length of the noise is increased at fixed local error probabilities. This shows that noise correlations in themselves need not be detrimental for NISQ algorithms such as QAOA.
