Autonomous bootstrapping of quantum dot devices

Journal Article (2025)
Author(s)

Anton Zubchenko (TU Delft - QuTech Advanced Research Centre, University of Copenhagen, TU Delft - QRD/Chatterjee Lab, Kavli institute of nanoscience Delft)

Danielle Middlebrooks (National Institute of Standards and Technology)

Torbjørn Rasmussen (University of Copenhagen)

Lara Lausen (University of Copenhagen)

Ferdinand Kuemmeth (Quantum Machines (QM), University of Copenhagen, Universität Regensburg)

Anasua Chatterjee (University of Copenhagen, TU Delft - QuTech Advanced Research Centre, Kavli institute of nanoscience Delft, TU Delft - QRD/Chatterjee Lab, TU Delft - QN/Chatterjee Lab)

Justyna P. Zwolak (University of Maryland, National Institute of Standards and Technology)

Research Group
QRD/Chatterjee Lab
DOI related publication
https://doi.org/10.1103/PhysRevApplied.23.014072 Final published version
More Info
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Publication Year
2025
Language
English
Research Group
QRD/Chatterjee Lab
Issue number
1
Volume number
23
Article number
014072
Downloads counter
189
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Abstract

Semiconductor quantum dots (QDs) are a promising platform for multiple different qubit implementations, all of which are voltage controlled by programmable gate electrodes. However, as the QD arrays grow in size and complexity, tuning procedures that can fully autonomously handle the increasing number of control parameters are becoming essential for enabling scalability. We propose a bootstrapping algorithm for initializing a depletion-mode QD device in preparation for subsequent phases of tuning. During bootstrapping, the QD device functionality is validated, all gates are characterized, and the QD charge sensor is made operational. We demonstrate the bootstrapping protocol in conjunction with a coarse-tuning module, showing that the combined algorithm can efficiently and reliably take a cooled-down QD device to a desired global-state configuration in under 8 min, with a success rate of 96%. Finally, by following heuristic approaches to QD device initialization and combining the efficient ray-based measurement with the rapid radio-frequency reflectometry measurements, the proposed algorithm establishes a reference in terms of performance, reliability, and efficiency against which alternative algorithms can be benchmarked.

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