Machine learning with controllable quantum dynamics of a nuclear spin ensemble in a solid
Makoto Negoro, Kosuke Mitarai, Keisuke Fujii +2 more
We experimentally demonstrate quantum machine learning using NMR based on a framework of quantum reservoir computing. Reservoir computing is for exploiting natural nonlinear dynamics with large degrees of freedom, which is called a reservoir, for a machine learning purpose. Here we propose a concrete physical implementation of a quantum reservoir using controllable dynamics of a nuclear spin ensemble in a molecular solid. In this implementation, we demonstrate learning of nonlinear functions with binary or continuous variable inputs with low mean squared errors. Our implementation and demonstration paves a road toward exploiting quantum computational supremacy in NMR ensemble systems for information processing with reachable technologies.
arXiv:1806.10910•Jun 28, 2018•22 citations