Data Needs and Challenges of Quantum Dot Devices Automation: Workshop Report

Autor:	Zwolak, Justyna P., Taylor, Jacob M., Andrews, Reed, Benson, Jared, Bryant, Garnett, Buterakos, Donovan, Chatterjee, Anasua, Sarma, Sankar Das, Eriksson, Mark A., Greplová, Eliška, Gullans, Michael J., Hader, Fabian, Kovach, Tyler J., Mundada, Pranav S., Ramsey, Mick, Rasmussen, Torbjoern, Severin, Brandon, Sigillito, Anthony, Undseth, Brennan, Weber, Brian
Rok vydání:	2023
Předmět:	Condensed Matter - Mesoscale and Nanoscale Physics Computer Science - Databases Computer Science - Machine Learning Quantum Physics
Druh dokumentu:	Working Paper
Popis:	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. Comment: White paper/overview based on a workshop held at the National Institute of Standards and Technology, Gaithersburg, MD. 13 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2312.14322 Zobrazit plný text záznamu View this record from Arxiv