Feedback-Optimized Operations with Linear Ion Crystals

TL;DR

This paper introduces a feedback-controlled method for transporting and manipulating linear ion crystals, achieving high success rates and robustness, which could advance ion-based quantum computing.

Contribution

The authors develop a feedback-based control scheme for ion crystal operations that does not require precise prior electric potential modeling.

Findings

Transport success probability exceeds 99.8%

Effective ion splitting and merging demonstrated

Robustness against experimental errors shown

Abstract

We report on transport operations with linear crystals of 40Ca+ ions by applying complex electric time-dependent potentials. For their control we use the information obtained from the ions' fluorescence. We demonstrate that by means of this feedback technique, we can transport a predefined number of ions and also split and unify ion crystals. The feedback control allows for a robust scheme, compensating for experimental errors as it does not rely on a precisely known electrical modeling of the electric potentials in the ion trap beforehand. Our method allows us to generate a self-learning voltage ramp for the required process. With an experimental demonstration of a transport with more than 99.8 % success probability, this technique may facilitate the operation of a future ion based quantum processor.