Data needs and challenges for quantum dot devices automation

Justyna P. Zwolak; Jacob M. Taylor; Reed W. Andrews; Jared Benson; Garnett W. Bryant; Donovan Buterakos; Anasua Chatterjee; Sankar Das Sarma; Mark A. Eriksson; Eliška Greplová; Michael J. Gullans; Fabian Hader; Tyler J. Kovach; Pranav S. Mundada; Mick Ramsey; Torbjørn Rasmussen; Brandon Severin; Anthony Sigillito; Brennan Undseth; Brian Weber

doi:10.1038/s41534-024-00878-x

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arXiv · 2312.14322

Data needs and challenges for quantum dot devices automation

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Abstract

Gate-defined quantum dots are a promising candidate system for realizing scalable, coupled qubit systems and serving 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. This meeting report outlines current challenges in automating quantum dot device tuning and operation with a particular focus on datasets, benchmarking, and standardization. We also present insights and ideas put forward by the quantum dot community on how to overcome them. We aim to provide guidance and inspiration to researchers invested in automation efforts.

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cond-mat.mes-hall cs.DB cs.LG quant-ph

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Justyna P. Zwolak, Jacob M. Taylor, Reed W. Andrews, Jared Benson, Garnett W. Bryant, Donovan Buterakos, Anasua Chatterjee, Sankar Das Sarma, Mark A. Eriksson, Eliška Greplová, Michael J. Gullans, Fabian Hader, Tyler J. Kovach, Pranav S. Mundada, Mick Ramsey, Torbjørn Rasmussen, Brandon Severin, Anthony Sigillito, Brennan Undseth, Brian Weber. 2023-12-21. Data needs and challenges for quantum dot devices automation. https://doi.org/10.1038/s41534-024-00878-x

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