Automated in situ optimization and disorder mitigation in a quantum device

TL;DR

This paper demonstrates automated in situ optimization of a quantum device's potential landscape using evolutionary strategies, improving conductance quantization and mitigating disorder both in simulation and real experiments.

Contribution

It introduces a novel optimization approach for quantum devices, combining simulation and experimental validation to enhance device performance and disorder mitigation.

Findings

Successful in situ optimization in simulation and experiment

Improved conductance quantization after optimization

Effective disorder mitigation in quantum point contact devices

Abstract

We investigate automated in situ optimization of the potential landscape in a quantum point contact device, using a $3 \times 3$ gate array patterned atop the constriction. Optimization is performed using the covariance matrix adaptation evolutionary strategy, for which we introduce a metric for how "step-like" the conductance is as the channel becomes constricted. We first perform the optimization of the gate voltages in a tight-binding simulation and show how such in situ tuning can be used to mitigate a random disorder potential. The optimization is then performed in a physical device in experiment, where we also observe a marked improvement in the quantization of the conductance resulting from the optimization procedure.