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arXiv · 1806.10910

Machine learning with controllable quantum dynamics of a nuclear spin ensemble in a solid

Makoto Negoro·Kosuke Mitarai·Keisuke Fujii·Kohei Nakajima·Masahiro Kitagawa
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Abstract

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.

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Makoto Negoro, Kosuke Mitarai, Keisuke Fujii, Kohei Nakajima, Masahiro Kitagawa. 2018-06-28. Machine learning with controllable quantum dynamics of a nuclear spin ensemble in a solid. https://arxiv.org/abs/1806.10910

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