Automated In Situ Optimization and Disorder Mitigation in a Quantum Device

We investigate automated optimization of the potential landscape in a quantum point contact device, using a <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"> <a:mn>3</a:mn> <a:mo>×</a:mo> <a:mn>3</a:mn> </a:math> gate array patterned atop the constriction. Optimization is performed using the covariance matrix adaptation evolutionary strategy, for which we introduce a metric for how “steplike” 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 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.