Compressed Optimization of Device Architectures (CODA) for semiconductor quantum devices

TL;DR

The paper introduces CODA, a protocol for efficiently controlling semiconductor quantum dot devices by identifying minimal voltage adjustments, improving tuning efficiency and aiding device design comparison.

Contribution

The paper presents CODA, a novel method for sparse control of quantum devices and a metric for comparing device architectures, demonstrated on simulated quantum dot systems.

Findings

CODA outperforms common nonlinear optimizers in tuning efficiency.

It identifies minimal voltage changes needed for device control.

Optimal device scaling reduces control complexity.

Abstract

Recent advances in nanotechnology have enabled researchers to manipulate small collections of quantum mechanical objects with unprecedented accuracy. In semiconductor quantum dot qubits, this manipulation requires controlling the dot orbital energies, tunnel couplings, and the electron occupations. These properties all depend on the voltages placed on the metallic electrodes that define the device, whose positions are fixed once the device is fabricated. While there has been much success with small numbers of dots, as the number of dots grows, it will be increasingly useful to control these systems with as few electrode voltage changes as possible. Here, we introduce a protocol, which we call the Compressed Optimization of Device Architectures (CODA), in order to both efficiently identify sparse sets of voltage changes that control quantum systems, and to introduce a metric which can be used to compare device designs. As an example of the former, we apply this method to simulated devices with up to 100 quantum dots and show that CODA automatically tunes devices more efficiently than other common nonlinear optimizers. To demonstrate the latter, we determine the optimal lateral scale for a triple quantum dot, yielding a simulated device that can be tuned with small voltage changes on a limited number of electrodes.