All-rf-based coarse-tuning algorithm for quantum devices using machine learning

Radio-frequency measurements could satisfy DiVincenzo’s readout criterion in future large-scale solid-state quantum processors, as they allow for high bandwidths and frequency multiplexing. However, the scalability potential of this readout technique can only be leveraged if quantum device tuning is performed using exclusively radio-frequency measurements, that is, without resorting to current measurements. We demonstrate an algorithm that performs automatic coarse tuning of double quantum dots with only radio-frequency measurements by exploiting their bandwidth and impedance matching. The tuning was completed within a few minutes with minimal prior knowledge about the device. Our results show that it is possible to eliminate the need for transport measurements for quantum-dot tuning, paving the way for more scalable device architectures.

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Publication Details

Journal
Physical Review Applied
Published
2025-11-10
DOI
https://doi.org/10.1103/v11m-dbhm
Citations
2
Primary Topic
Quantum and electron transport phenomena
Type
article
Field-Weighted Citation Impact
2.49

Funders

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article

All-rf-based coarse-tuning algorithm for quantum devices using machine learning

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2 citations
Physical Review Applied
Quantum and electron transport phenomena
2.49
article

All-rf-based coarse-tuning algorithm for quantum devices using machine learning

Georgios Katsaros, Natalia Ares, Daniel Chrastina, Daniel Jirovec, Federico Fedele, Joseph Hickie, Barnaby van Straaten, Andrea Ballabio, Florian Vigneau, Giovanni Isella
article en
2 citations

Abstract

Radio-frequency measurements could satisfy DiVincenzo’s readout criterion in future large-scale solid-state quantum processors, as they allow for high bandwidths and frequency multiplexing. However, the scalability potential of this readout technique can only be leveraged if quantum device tuning is performed using exclusively radio-frequency measurements, that is, without resorting to current measurements. We demonstrate an algorithm that performs automatic coarse tuning of double quantum dots with only radio-frequency measurements by exploiting their bandwidth and impedance matching. The tuning was completed within a few minutes with minimal prior knowledge about the device. Our results show that it is possible to eliminate the need for transport measurements for quantum-dot tuning, paving the way for more scalable device architectures.

Physical Review AppliedVol. 24(5)
Institute of Science and Technology Austria (AT), University of Oxford (GB), Politecnico di Milano (IT)
Silicon Valley Community Foundation, Foundational Questions Institute, Institute of Science and Technology Austria, Austrian Science Fund, Engineering and Physical Sciences Research Council
Openalex Percentile: Top 9%
Quantum and electron transport phenomena
2.49
DOIOpen Access PDFOpenAlex
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All-rf-based coarse-tuning algorithm for quantum devices using machine learning — Georgios Katsaros, Natalia Ares, et al. · Physical Review Applied (2025) | TGRS Research Map | TGRS