Enhancing Qubit Readout with Autoencoders

Luchi, Piero; Trevisanutto, Paolo E.; Roggero, Alessandro; DuBois, Jonathan L.; Rosen, Yaniv J.; Turro, Francesco; Amitrano, Valentina; Pederiva, Francesco

doi:10.1103/physrevapplied.20.014045

Enhancing Qubit Readout with Autoencoders

Journal Article · Thu Jul 20 00:00:00 EDT 2023 · Physical Review Applied

DOI:https://doi.org/10.1103/physrevapplied.20.014045· OSTI ID:1993136

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Univ. of Trento (Italy); Istituto Nazionale di Fisica Nucleare, Trento (Italy). Trento Institute for Fundamental Physics and Applications (INFN-TIFPA)
Science and Technology Facilities Council (STFC) (United Kingdom)
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

In addition to the need for stable and precisely controllable qubits, quantum computers take advantage of good readout schemes. Superconducting qubit states can be inferred from the readout signal transmitted through a dispersively coupled resonator. Here, this work proposes a readout classification method for superconducting qubits based on a neural network pretrained with an autoencoder approach. A neural network is pretrained with qubit readout signals as autoencoders in order to extract relevant features from the data set. Afterward, the pretrained-network inner-layer values are used to perform a classification of the inputs in a supervised manner. We demonstrate that this method can enhance classification performance, particularly for short- and long-time measurements where more traditional methods present inferior performance.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); USDOE Laboratory Directed Research and Development (LDRD) Program; European Union (EU)

Grant/Contract Number:: AC52-07NA27344

OSTI ID:: 1993136

Report Number(s):: LLNL-JRNL-842516; 1064905

Journal Information:: Physical Review Applied, Journal Name: Physical Review Applied Journal Issue: 1 Vol. 20; ISSN 2331-7019

Publisher:: American Physical Society (APS)Copyright Statement

Country of Publication:: United States

Language:: English

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