Bilinear dynamic mode decomposition for quantum control

Goldschmidt, Andy; Kaiser, E.; DuBois, J. L.; Brunton, S. L.; Kutz, J. N.

doi:10.1088/1367-2630/abe972

Title: Bilinear dynamic mode decomposition for quantum control

Journal Article · 21 March 2021 · New Journal of Physics

DOI: https://doi.org/10.1088/1367-2630/abe972 · OSTI ID:1835484

;

; DuBois, J. L.; Brunton, S. L.;

Abstract Data-driven methods for establishing quantum optimal control (QOC) using time-dependent control pulses tailored to specific quantum dynamical systems and desired control objectives are critical for many emerging quantum technologies. We develop a data-driven regression procedure, bilinear dynamic mode decomposition (biDMD), that leverages time-series measurements to establish quantum system identification for QOC. The biDMD optimization framework is a physics-informed regression that makes use of the known underlying Hamiltonian structure. Further, the biDMD can be modified to model both fast and slow sampling of control signals, the latter by way of stroboscopic sampling strategies. The biDMD method provides a flexible, interpretable, and adaptive regression framework for real-time, online implementation in quantum systems. Further, the method has strong theoretical connections to Koopman theory, which approximates nonlinear dynamics with linear operators. In comparison with many machine learning paradigms minimal data is needed to construct a biDMD model, and the model is easily updated as new data is collected. We demonstrate the efficacy and performance of the approach on a number of representative quantum systems, showing that it also matches experimental results.

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

Sponsoring Organization:: USDOE; USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: AC52-07NA27344

OSTI ID:: 1835484

Report Number(s):: LLNL-JRNL-816759

Journal Information:: New Journal of Physics, Journal Name: New Journal of Physics Journal Issue: 3 Vol. 23; ISSN 1367-2630

Publisher:: IOP PublishingCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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