Non-Gaussian noise spectroscopy with a superconducting qubit sensor
Youngkyu Sung,
Félix Beaudoin,
Leigh M. Norris,
Fei Yan,
David K. Kim,
Jack Y. Qiu,
Uwe Lüpke,
Jonilyn L. Yoder,
Terry P. Orlando,
Simon Gustavsson,
Lorenza Viola () and
William D. Oliver ()
Additional contact information
Youngkyu Sung: Massachusetts Institute of Technology
Félix Beaudoin: Dartmouth College
Leigh M. Norris: Dartmouth College
Fei Yan: Massachusetts Institute of Technology
David K. Kim: MIT Lincoln Laboratory
Jack Y. Qiu: Massachusetts Institute of Technology
Uwe Lüpke: Massachusetts Institute of Technology
Jonilyn L. Yoder: MIT Lincoln Laboratory
Terry P. Orlando: Massachusetts Institute of Technology
Simon Gustavsson: Massachusetts Institute of Technology
Lorenza Viola: Dartmouth College
William D. Oliver: Massachusetts Institute of Technology
Nature Communications, 2019, vol. 10, issue 1, 1-8
Abstract:
Abstract Accurate characterization of the noise influencing a quantum system of interest has far-reaching implications across quantum science, ranging from microscopic modeling of decoherence dynamics to noise-optimized quantum control. While the assumption that noise obeys Gaussian statistics is commonly employed, noise is generically non-Gaussian in nature. In particular, the Gaussian approximation breaks down whenever a qubit is strongly coupled to discrete noise sources or has a non-linear response to the environmental degrees of freedom. Thus, in order to both scrutinize the applicability of the Gaussian assumption and capture distinctive non-Gaussian signatures, a tool for characterizing non-Gaussian noise is essential. Here, we experimentally validate a quantum control protocol which, in addition to the spectrum, reconstructs the leading higher-order spectrum of engineered non-Gaussian dephasing noise using a superconducting qubit as a sensor. This first experimental demonstration of non-Gaussian noise spectroscopy represents a major step toward demonstrating a complete spectral estimation toolbox for quantum devices.
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11699-4
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DOI: 10.1038/s41467-019-11699-4
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