# Computer-automated tuning procedures for semiconductor quantum dot arrays

## TL;DR

This paper presents automated software and feedback protocols for tuning semiconductor quantum dot arrays, reducing manual intervention and enabling rapid, precise control of quantum dot parameters for quantum computing applications.

## Contribution

It introduces a Python-based image analysis toolbox for automated calibration and demonstrates feedback protocols for tuning tunnel couplings in quantum dot arrays.

## Key findings

- Automated calibration of virtual gates reduces user intervention.
- Feedback protocols enable simultaneous tuning of tunnel couplings.
- Modeling interdot barrier response accelerates tuning to GHz regimes.

## Abstract

As with any quantum computing platform, semiconductor quantum dot devices require sophisticated hardware and controls for operation. The increasing complexity of quantum dot devices necessitates the advancement of automated control software and image recognition techniques for rapidly evaluating charge stability diagrams. We use an image analysis toolbox developed in Python to automate the calibration of virtual gates, a process that previously involved a large amount of user intervention. Moreover, we show that straightforward feedback protocols can be used to simultaneously tune multiple tunnel couplings in a triple quantum dot in a computer automated fashion. Finally, we adopt the use of a `tunnel coupling lever arm' to model the interdot barrier gate response and discuss how it can be used to more rapidly tune interdot tunnel couplings to the GHz values that are compatible with exchange gates.