论文标题
NISQ时代的最佳量子储存计算
Optimal quantum reservoir computing for the NISQ era
论文作者
论文摘要
通用易于断层量子计算机需要数百万量动物的错误率较低。由于这项技术是多年来的，因此嘈杂的中间量子量子（NISQ）计算引起了极大的兴趣。在此设置中，量子储层计算是一种相关的机器学习算法。它的简单性训练和实施允许在当今可用的机器上执行具有挑战性的计算。在这封信中，我们提供了一个选择最佳量子储层的标准，需要很少和简单的门。我们的发现表明，它们比其他大门的其他常用模型更好，并且还提供了量子储层计算与量子状态复杂性理论之间的理论差距的见解。
Universal fault-tolerant quantum computers require millions of qubits with low error rates. Since this technology is years ahead, noisy intermediate-scale quantum (NISQ) computation is receiving tremendous interest. In this setup, quantum reservoir computing is a relevant machine learning algorithm. Its simplicity of training and implementation allows to perform challenging computations on today available machines. In this Letter, we provide a criterion to select optimal quantum reservoirs, requiring few and simple gates. Our findings demonstrate that they render better results than other commonly used models with significantly less gates, and also provide insight on the theoretical gap between quantum reservoir computing and the theory of quantum states complexity.
