RQC Seminar

11th RQC Seminar

  • 講演者

    Prof. Anton Frisk Kockum
    (Department of Microtechnology and Nanoscience, Chalmers University of Technology.）

  • 日程

    2022年8月16日（火）16:00-17:00（JST）

  • 開催場所

    ハイブリッド（Zoom ・ 理研　和光事業所　本部棟2階大会議室）

  • 講演タイトル

    Quantum state and process tomography with machine learning and gradient descent

  • お問合せ

    rqc_info[at]ml.riken.jp

講演概要
The ability to quickly and accurately characterise quantum states and dynamics is crucial for the development of quantum technologies. However, the problem of learning a general quantum state or process has exponential complexity in the size of the quantum system. In this talk, I will present some recent progress we have made for both quantum state and process tomography. For state tomography, I will show how generative adversarial neural networks can outperform standard methods in terms of both the amount of time and data needed [1,2]. For process tomography, I will show how optimization using constrained gradient descent can work both for instances with little data and for larger systems, regimes which previously required two different methods [3].

References
[1] S. Ahmed et al., Phys. Rev. Lett. 127, 140502 (2021)
[2] S. Ahmed et al., Phys. Rev. Res. 3, 033278 (2021)
[3] S. Ahmed et al., in preparation.


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