



@article {3396,
	title = {Data Needs and Challenges of Quantum Dot Devices Automation: Workshop Report},
	year = {2023},
	month = {12/21/2023},
	abstract = {<p>Gate-defined quantum dots are a promising candidate system to realize scalable, coupled qubit systems and serve as a fundamental building block for quantum computers. However, present-day quantum dot devices suffer from imperfections that must be accounted for, which hinders the characterization, tuning, and operation process. Moreover, with an increasing number of quantum dot qubits, the relevant parameter space grows sufficiently to make heuristic control infeasible. Thus, it is imperative that reliable and scalable autonomous tuning approaches are developed. In this report, we outline current challenges in automating quantum dot device tuning and operation with a particular focus on datasets, benchmarking, and standardization. We also present ideas put forward by the quantum dot community on how to overcome them.</p>},
	doi = {https://doi.org/10.48550/arXiv.2312.14322},
	url = {https://arxiv.org/abs/2312.14322},
	author = {Justyna P. Zwolak and Jacob M. Taylor and Reed Andrews and Jared Benson and Garnett Bryant and Donovan Buterakos and Anasua Chatterjee and Sankar Das Sarma and Mark A. Eriksson and Eli{\v s}ka Greplov{\'a} and Michael Gullans and Fabian Hader and Tyler J. Kovach and Pranav S. Mundada and Mick Ramsey and Torbjoern Rasmussen and Brandon Severin and Anthony Sigillito and Brennan Undseth and Brian Weber}
}
