# Magneto-Ionic Physical Reservoir Computing in Perpendicularly Magnetized Heterostructures

## TL;DR

This paper demonstrates a magneto-ionic device that can perform reservoir computing by leveraging ion migration dynamics for efficient temporal data classification.

## Contribution

The novelty lies in using perpendicularly magnetized heterostructures for physical reservoir computing with magneto-ionics.

## Key findings

- The device exhibited nonlinear ion migration dynamics and short-term memory.
- It successfully distinguished between sine and square waveforms in pulse data.
- Performance metrics showed STM of 1.44 and parity check capacity of 2 for 24 virtual nodes.

## Abstract

Recent progress in
magneto-ionics offers exciting potential to
leverage its energy efficiency for implementing physical reservoir
computing (PRC). In this work, we experimentally demonstrate the classification
of temporal data using a perpendicularly magnetized magneto-ionic
(MI) heterostructure. The device was specifically engineered to induce
nonlinear ion migration dynamics, which in turn imparted nonlinearity
and short-term memory (STM) to the magnetization. These key features
for enabling reservoir computing were investigated, and the role of
the ion migration mechanism, along with its history-dependent influence
on STM, was explained. These attributes were utilized to distinguish
between sine and square waveforms within a randomly distributed set
of pulses. Additionally, two important performance metricsSTM
and parity check capacity were quantified, yielding promising
values of 1.44 and 2 for 24 virtual nodes, respectively, comparable
to those of other state-of-the-art reservoirs. Our work paves the
way for exploiting the relaxation dynamics of solid-state MI platforms
and developing energy-efficient MI reservoir computing devices.