QDFlow Tutorial

QDFlow is an open-source physics simulator for Quantum Dot arrays that generates realistic Charge-Stability Diagrams (CSDs) which mimic experimental data, along with ground-truth labels of the charge state at each point in the CSD.

This tutorial will demonstrate how to use QDFlow to generate realistic, diverse, synthetic datasets suitable for training and benchmarking Machine Learning models as well as other applications in quantum dot research.

This tutorial requires the tutorial_helper.py file, which contains helper functions used to streamline plotting the results. This file is available from the QDFlow GitHub repository, along with the tutorial notebook itself.

• Getting Started
• Generating Datasets
• Distributions
• Custom Distributions
• Correlated Distributions
• Adding Noise
• Ray Data
• Physics Simulation
• Thomas-Fermi Solver
• Capacitance Model