A Single-Ion Information Engine for Charging Quantum Battery

TL;DR

This paper demonstrates a single trapped-ion information engine that efficiently charges a quantum battery using quantized mechanical motion, achieving over 50% of the theoretical maximum efficiency through advanced rapid state discrimination.

Contribution

It introduces an experimental setup where a single ion acts as an information engine to charge a quantum battery, with improved measurement techniques reducing disturbances.

Findings

Charging efficiency exceeds 50% of the theoretical limit.

Rapid state discrimination suppresses measurement-induced disturbances.

Trapped ions are viable platforms for microscopic information engines.

Abstract

Information engines produce mechanical work through measurement and adaptive control. For information engines, the principal challenge lies in how to store the generated work for subsequent utilization. Here, we report an experimental demonstration where quantized mechanical motion serves as a quantum battery and gets charged in repeated cycles by a single trapped-ion information engine. This is enabled by a key technological advancement in rapid state discrimination, allowing us to suppress measurement-induced disturbances. Consequently, we were able to obtain a charging efficiency over 50\% of the theoretical limit at the optimal temperature. The experimental results substantiate that this approach can render trapped ions a promising platform for microscopic information engines with potential applications in the future upon scaling up.