SciPost logo

SciPost Submission Page

QDsim: A user-friendly toolbox for simulating large-scale quantum dot devices

by Valentina Gualtieri, Charles Renshaw-Whitman, Vinicius Hernandes, Eliska Greplova

Submission summary

Authors (as registered SciPost users): Valentina Gualtieri
Submission information
Preprint Link: https://arxiv.org/abs/2404.02712v2  (pdf)
Code repository: https://gitlab.com/QMAI/papers/qdsim
Date accepted: 2024-08-27
Date submitted: 2024-08-05 15:41
Submitted by: Gualtieri, Valentina
Submitted to: SciPost Physics Codebases
Ontological classification
Academic field: Physics
Specialties:
  • Condensed Matter Physics - Computational
Approach: Computational

Abstract

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.

Current status:
Accepted in target Journal

Editorial decision: For Journal SciPost Physics Codebases: Publish
(status: Editorial decision fixed and (if required) accepted by authors)

Login to report or comment