Quantum Metrology and Sensing V

ORAL · W38 · ID: 47200

Presentations

  • ORAL

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    Publication: planned paper: Optimal Bayesian experiment design implemented in adaptable hardware
    planned paper: Simplified algorithms for adaptive experiment design in parameter estimation

    Presenters

    • Sean M Blakley

      • National Institute of Standards and Technology
      • National Institute of Standards and Tech

    Authors

    • Sean M Blakley

      • National Institute of Standards and Technology
      • National Institute of Standards and Tech

    • Robert D McMichael

      • National Institute of Standards and Technology

    View abstract →

  • ORAL

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    Publication: R. D. McMichael, S. Dushenko and S. Blakley, Sequential Bayesian experiment design for
    adaptive Ramsey sequence measurements, J. Appl. Phys. 130, 144401 (2021);

    Presenters

    • Robert D McMichael

      • National Institute of Standards and Technology

    Authors

    • Sean M Blakley

      • National Institute of Standards and Technology
      • National Institute of Standards and Tech

    • Robert D McMichael

      • National Institute of Standards and Technology

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  • ORAL

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    Presenters

    • Denis R Candido

      • University of Iowa
      • Department of Physics and Astronomy, University of Iowa

    Authors

    • Denis R Candido

      • University of Iowa
      • Department of Physics and Astronomy, University of Iowa

    • Michael E Flatté

      • University of Iowa
      • Department of Physics and Astronomy, University of Iowa

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  • ORAL

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    Presenters

    • Yoav Romach

      • Quantum Machines
      • Customer Success Engineer, Quantum Machines

    Authors

    • Yonatan Cohen

      • Quantum Machines

    • Yoav Romach

      • Quantum Machines
      • Customer Success Engineer, Quantum Machines

    • Niv Drucker

      • Quantum Machines

    • Nir Halay

      • Quantum Machines

    • Nissim Ofek

      • Quantum Machines
      • Quantum Machines, Israel

    • Inbar Zohar

      • Weizmann Institute of Science

    • Amit Finkler

      • Weizmann Institute of Science

    • Nabeel Aslam

      • Harvard
      • Harvard University

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  • ORAL

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    Presenters

    • Kaoru Yamamoto

      • NTT Computer and Data Science Laboratories, NTT Corporation

    Authors

    • Kaoru Yamamoto

      • NTT Computer and Data Science Laboratories, NTT Corporation

    • Suguru Endo

      • NTT Corporation
      • NTT Computer and Data Science Laboratories, NTT Corporation

    • Hideaki Hakoshima

      • Osaka University
      • Center for Quantum Information and Quantum Biology, Osaka University

    • Yuichiro Matsuzaki

      • AIST
      • Research Center for Emerging Computing Technologies, National institute of Advanced Industrial Science and Technology (AIST)
      • National Institute of Advanced Industrial Science and Technology

    • Yuuki Tokunaga

      • NTT Corporation
      • NTT Computer and Data Science Laboratories, NTT Corporation

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  • ORAL

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    Publication: Shin, D., Cupertino, A., de Jong, M. H., Steeneken, P. G., Bessa, M. A., & Norte, R. A. (2021). Spiderweb nanomechanical resonators via Bayesian optimization: inspired by nature and guided by machine learning. Advanced Materials. Accepted

    Presenters

    • Dongil Shin

      • Delft University of Technology

    Authors

    • Dongil Shin

      • Delft University of Technology

    • Andrea Cupertino

      • Delft University of Technology

    • Matthijs H de Jong

      • Delft University of Technology

    • Peter G Steeneken

      • Delft University of Technology
      • TU Delft

    • Miguel A Bessa

      • Delft University of Technology

    • Richard A Norte

      • Delft University of Technology

    View abstract →

  • ORAL

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    Publication: [1] Albertinale et al., arXiv:2102.01415 (2021)
    [2] Le Dantec et al., arXiv:2106.14974 (2021)
    [3] Bienfait et al., Nature 531, 74–77 (2016)
    [4] Lescanne et al., Phys. Rev. X 10, 021038 (2020)
    [5] Ranjan et al., Appl. Phys. Lett. 116, 184002 (2020)

    Presenters

    • Eric Billaud

      • CEA Saclay

    Authors

    • Eric Billaud

      • CEA Saclay

    View abstract →