Developing a backend physics engine for autotuning quantum dot qubit devices

Autonomous tuning, without human intervention, is becoming increasingly important as arrays of quantum dot (QD) qubits become larger. However, the development and validation of such software are hindered by the need to work with a physical qubit device in a cryostat. Here, we present a digital twin of a QD device – a backend physics engine – developed specifically to enable the testing and development of quantum dot qubit autotuning software. This digital twin simulates the gate-voltage response of a gate-defined Si/SiGe QD qubit device [1, 2], and it is built on MaSQE [3], a Schrodinger-Poisson solver tailored for QD devices. We demonstrate the use of the backend to aid in the development of an autotuning framework known as FrEQuENTS. We present an example showing how QD device simulation not only speeds up the development of the tuning framework, but also enables advancing the autotuner’s performance beyond what would be possible by simply mimicking the behavior of a human scientist in the lab. Together, these tools – FrEQuENTS and the QD digital twin based on MaSQE – offer a powerful platform for further autotuning development. They also offer the prospect of training new users in a fully simulated mode of operation before working with a physical qubit device in a lab-based cryogenic environment.

[1] D.M. Zajac, et al. Phys. Rev. Applied 6, 054013 (2016).

[2] J. P. Dodson, et al. Nanotechnology 31, 505001 (2020).

[3] Christopher R. Anderson, et al. AIP Advances 12, 065123 (2022).