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Mizuta Kaoru  水田 郁

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水田 郁  ミズタ カオル

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Researcher Number 70963700
Other IDs
Affiliation (Current) 2026: 大阪大学, 量子情報・量子生命研究センター, 准教授
Affiliation (based on the past Project Information) *help 2024: 東京大学, 大学院工学系研究科(工学部), 助教
Review Section/Research Field
Principal Investigator
Basic Section 13010:Mathematical physics and fundamental theory of condensed matter physics-related
Keywords
Principal Investigator
非平衡量子系 / 量子計算 / 時間依存系 / 量子アルゴリズム
  • Research Projects

    (1 results)
  • Research Products

    (4 results)
  •  Optimal quantum algorithm for time-dependent nonequilibrium systemsPrincipal Investigator

    • Principal Investigator
      水田 郁
    • Project Period (FY)
      2024 – 2028
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 13010:Mathematical physics and fundamental theory of condensed matter physics-related
    • Research Institution
      The University of Tokyo

All 2025 2024

All Journal Article Presentation

  • [Journal Article] Nearly optimal quasienergy estimation and eigenstate preparation of time-periodic Hamiltonians by Sambe space formalism2025

    • Author(s)
      Mizuta Kaoru
    • Journal Title

      Physical Review Research

      Volume: 7 Issue: 1 Pages: 013068-013068

    • DOI

      10.1103/physrevresearch.7.013068

    • Data Source
      KAKENHI-PROJECT-24K16974
  • [Presentation] Explicit error bounds with commutator scaling for time-dependent product and multi-product formulas2025

    • Author(s)
      Kaoru Mizuta
    • Organizer
      QIP2025
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-24K16974
  • [Presentation] 非平衡量子多体系の物理と最適な量子アルゴリズム2024

    • Author(s)
      水田 郁
    • Organizer
      第12回量子ソフトウェア研究会
    • Invited
    • Data Source
      KAKENHI-PROJECT-24K16974
  • [Presentation] Efficient quantum algorithms for simulating time-dependent Hamiltonians2024

    • Author(s)
      Kaoru Mizuta
    • Organizer
      ISSP workshop "New Trends in Condensed Matter Theory 2024"
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-24K16974

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