Kavli Affiliate: Eliska Greplova
| First 5 Authors: Valentina Gualtieri, Charles Renshaw-Whitman, Vinicius Hernandes, Eliska Greplova,
| Summary:
We introduce QDsim, a python package tailored for the rapid generation of
charge stability diagrams in large-scale quantum dot devices, extending beyond
traditional double or triple dots. QDsim is founded on the constant interaction
model from which we rephrase the task of finding the lowest energy charge
configuration as a convex optimization problem. Therefore, we can leverage the
existing package CVXPY, in combination with an appropriate powerful solver, for
the convex optimization which streamlines the creation of stability diagrams
and polytopes. Through multiple examples, we demonstrate how QDsim enables the
generation of large-scale dataset that can serve a basis for the training of
machine-learning models for automated tuning algorithms. While the package
currently does not support quantum effects beyond the constant interaction
model, QDsim is a tool that directly addresses the critical need for
cost-effective and expeditious data acquisition for better tuning algorithms in
order to accelerate the development of semiconductor quantum devices.
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