SciPost Submission Page
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
by Jan Adrian Krzywda, Weikun Liu, Evert van Nieuwenburg, Oswin Krause
Submission summary
| Authors (as registered SciPost users): | Jan Krzywda |
| Submission information | |
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| Preprint Link: | https://arxiv.org/abs/2404.02064v1 (pdf) |
| Code repository: | https://github.com/condensedAI/QDarts |
| Date submitted: | 2024-04-04 10:41 |
| Submitted by: | Krzywda, Jan |
| Submitted to: | SciPost Physics Codebases |
| Ontological classification | |
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| Academic field: | Physics |
| Specialties: |
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| Approach: | Computational |
Abstract
We present QDarts, an efficient simulator for realistic charge stability diagrams of quantum dot array (QDA) devices in equilibrium states. It allows for pinpointing the location of concrete charge states and their transitions in a high-dimensional voltage space (via arbitrary two-dimensional cuts through it), and includes effects of finite tunnel coupling, non-constant charging energy and a simulation of noisy sensor dots. These features enable close matching of various experimental results in the literature, and the package hence provides a flexible tool for testing QDA experiments, as well as opening the avenue for developing new methods of device tuning.
Current status:
Reports on this Submission
Report 1 by Matias Urdampilleta on 2024-7-11 (Invited Report)
Strengths
1- the present approach and code tackles an important problem in semiconductor spin qubit: how to distribute charges in an array
2- the code is well structured and in comparison with a brute force approach is efficient
3- the code and model allow to track and identify charge state in the array
4- it can reproduce data realistically by accounting for noise model on charge sensor
Weaknesses
1- difficulty to install the code for a non-python expert (no pip install)
2- the code returns some errors for particular points in gate space
3- the model is based on an open system, the possibility to close it and work with a finite number of charge would be a plus
Report
Krzydwa et al. present a physical model of the electrostatic of quantum dots which allows to extract the stable charge configuration of an array of quantum dot and simulate the response of the sensor to charge transition.
This work is very timely as we can see with few papers submitted at the same time on ArXiv which try to adress this need in the community with different approaches .
Moreover, the model is refined to account for the noise and the tunnel coupling and is tested against experimental data which are quantitatively reproduced.
The model is implemented in a python code which is accessible and properly documented. As experimentalists working on this problem, we found the code easy to use (while a bit difficult to install) and quite efficient in term of speed.
We have bench-marked this code against our own which has a more brute force approach and found the present code to be much more efficient in particular toward a large number of quantum dots and charge number. We would therefore encourage experimentalists to use this code to simulate their charge stability diagram of an open array.
There are still some functionalities that are missing and which could definitely benefit to the community to simulate more complex array. These are recommendations, and a bit beyond our expertise to estimate the technical feasibility.
First of all, the ability to work with a finite number of charge in the array would be very helpful to simulate isolated arrays which is a widely used approach in experiments (see Flentje, et al. Nat Commun. 8, 501 (2017) or Meyer et al. Nano Lett. 24, 11593 (2023) or Yang, et al. Nature 580, 350–354 (2020).)
Second, instead of using charge detection, probing the quantum capacitance through gate-based reflectometry would be a nice functionality. For instance, reproducing RF signal on stability diagrams for different parameters such as tunnel coupling, lever arm, frequency etc… would be extremely useful. This readout method is believed to be scalable approach to control and read spins in large array (Crippa, et al. Nat Commun 10, 2776 (2019), Veldhorst, et al. Nat Commun 8, 1766 (2017).)
Requested changes
We do not request particular change apart from facilitating the installation with better documentation.
Recommendation
Publish (meets expectations and criteria for this Journal)