  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.

Mesoscale and Nanoscale Physics;Quantum Physics