RQC Colloquium

33rd RQC Colloquium

  • 講演者

    Prof. Dong Daoyi
    (Australian AI Institute, University of Technology Sydney, Australia)

  • 日程

    2025年4月4日（金）16:00-17:00（JST）

  • 開催場所

    Hybrid (Zoom・Wako C61 Welfare and Conference Building, 2F Large Meeting Room)

  • 講演タイトル

    Optimization and error analysis in quantum tomography, and quantum autoencoders

  • お問合せ

    rqc_colloquium_inquiry[at]ml.riken.jp

  • 登録フォーム

    https://krs2.riken.jp/m/rqc_registration_form

講演概要
Quantum technology is a promising future technology where unique quantum characteristics are taken advantage of to develop faster computation, securer communication, and high-precision sensing than their classical (non-quantum) counterparts. Quantum tomography is a fundamental task for developing powerful quantum technology. In this talk, we will first introduce several results on optimization, adaptivity, and error analysis in quantum state tomography, quantum detector tomography, quantum Hamiltonian identification, and quantum process tomography. In particular, we will present several error bounds and show how to design adaptive algorithms to achieve optimal scaling. Then we will introduce learning control for quantum autoencoders which are an important tool for quantum data compression.
Flyer: 33rd RQC Colloquium Flyer

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