Trapped ion chain as a neural network

TL;DR

This paper explores how a chain of trapped ions with tunable long-range interactions can serve as a neural network, enabling distributed information storage and potential quantum logic implementations.

Contribution

It introduces a model of a neural network using trapped ion chains with controllable interactions and analyzes its storage capacity and robustness.

Findings

Storage capacity depends on phonon spectrum

Adjusting trapping potential controls network properties

Potential for robust quantum logic implementations

Abstract

We demonstrate the possibility of realizing a neural network in a chain of trapped ions with induced long range interactions. Such models permit to store information distributed over the whole system. The storage capacity of such network, which depends on the phonon spectrum of the system, can be controlled by changing the external trapping potential and/or by applying longitudinal local magnetic fields. The system properties suggest the possibility of implementing robust distributed realizations of quantum logic.