A package for simulating realistic quantum dot arrays and their charge transitions.
Project description
QDarts
Efficient Quantum Dot array transition simulator.
Description
We provide an efficient simulation package, QDarts, generating realistic charge conductance signals from medium, more than 10 quantum dot arrays. By levering the polytope finding algorithm from O. Krause, A. Chatterjee, F. Kuemmeth and E. van Nieuwenburg, Learning coulomb diamonds in large quantum dot arrays, SciPost Physics 13(4), 084 (2022), the QDarts allows for:
- Transition finding in high-dimensional voltage space,
- Selection of arbitrary cuts in the voltage space,
- Simulating effects of finite tunnel couplings,
- Including non-constant charging energies,
- Simulation of multiple sensor dot,
- Tunable noise parameters,
- User-friendly interface.
Installation
The package supports Python 3.6 and later. To install the package, run the following command:
pip install qdarts
Manuscript
The package is based on the manuscript by Krzywda et al., QDarts: A Quantum Dot Array Transition Simulator for finding charge transitions in the presence of finite tunnel couplings, non-constant charging energies and sensor dots. The manuscript has been submitted to the SciPost Physics Codebases.
Examples
The package provides a simple example to demonstrate the usage of the package. The example is available in the examples qatpack/examples folder. The example demonstrates the simulation of a quantum dot array with sensor dots, tunnel couplings, and non-constant charging energy.
As a proof of principle, in the example we reconstruct the figure from the paper Neyens et al., which shows the measured charge conductance signal from two sensor dots, which detect simultanous four-dot transition in the quantum dot array. The figure, visible below, has been computed in about a minute on a standard laptop.
Files in this repository
qdarts
|-- qdarts
|-- model.py
|-- noise_processes.py
|-- experiment.py
|-- plotting.py
|-- polytope.py
|-- simulator.py
|-- tunneling_simulator.py
|-- util_functions.py
|-- examples
|-- examples_scipost.ipynb # notebook to reproduce figures from paper
|-- README.md
|-- LICENCE.md
|-- CITATION.cff
Roadmap
The package is under active development. The future plans include:
- Adding barrier gates,
- Including realistic noise processes, including 1/f noise,
- Adding more examples,
- Adding a method for generating capacitance matrices from:
- QD array layout,
- Experimental data,
- Finite element method simulations,
- Scaling up to larger quantum dot arrays N>10,
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