  Physical reservoir computing has recently been attracting attention for its
ability to significantly reduce the computational resources required to process
time-series data. However, the physical reservoirs that have been reported to
date have had insufficient expression power, and most of them have a large
volume, which makes their practical application difficult. Herein we describe
the development of a Li+-electrolyte based ion-gating reservoir (IGR), with
ion-electron coupled dynamics, for use in high performance physical reservoir
computing. A variety of synaptic responses were obtained in response to past
experience, which responses were stored as transient charge density patterns in
an electric double layer, at the Li+-electrolyte/diamond interface.
Performance, which was tested using a nonlinear autoregressive moving-average
(NARMA) task, was found to be excellent, with a NMSE of 0.023 for NARMA2, which
is the highest for any physical reservoir reported to date. The maximum
Lyapunov exponent of the IGR was 0.0083: the edge of chaos state enabling the
best computational capacity. The IGR described herein opens the way for
high-performance and integrated neural network devices.
