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Quantum Application Team

  • Worldwide progress of R&D of quantum computers will create new businesses.Establish a business development environment is required for creating use cases of quantum computers and human resources development.
  • In the short term, building an ecosystem where the benefits from industrial applications is used for investment in new technology development.
  • In the mid- to long-term, expand the scope and scale of application of quantum computers by using large-scale, gate-based quantum computers that are expected to be used in actual industrial applications.
  • Integrate Quantum -AI technology into existing informatics research in collaboration with AIST’s diverse fields. Encourage the creation of use cases through cross-industry fusion—such as Quantum x Bio, Quantum x Material, Quantum x Computer Aided Engineering (CAE), and Quantum x Finance—driven by user companies.
  • Team Research Theme

    Theory of Quantum Computers and Quantum Annealing

  • Simulation technology for superconducting quantum circuits
  • Exploration of applications such as artificial intelligence, quantum chemical computation, CAE, finance, etc.

  • To achieve practical quantum computers and quantum annealing machines, essential components include device design, algorithm development, and application exploration using theory and simulation technology. At AIST, we are developing superconducting quantum circuit simulation technology and quantum algorithms, and exploring their potential applications in fields such as artificial intelligence, quantum chemical computation, CAE and finance. Additionally, we conduct theoretical research on quantum sensing, quantum IoT, and quantum control.

    Quantum chemical calculations using quantum annealing

    Quantum annealing applied to chemical calculations

    Quantum circuits for quantum machine learning

    Quantum circuits for quantum machine learning




    Quantum Circuit Automation Powered by Generative AI


    Staff Members

    photo position & name field of expertise
    Team Leader,
    Yohichi SUZUKI
    Applied research on quantum computers, Equilibrium and non-equilibrium statistical physics
    Joint Appointed Fellow,
    Tadashi KADOWAKI
    Applied research on quantum computers, Quantum CAE, AI4Science
    Senior Researcher,
    Yuta MIZUNO
    Quantum algorithms, dynamical systems, optimization, chemical reactions
    Researcher,
    Shunya MINAMI
    Statistical machine learning, artificial intelligence, financial engineering, materials informatics
    Researcher,
    Haruka AKISHIMA
    Researcher,
    SUDEERA GUNATHILAKA Sudeera Gunathilaka
    Unconventional computing architectures (Coherent computing, Quantum computing etc.), Optimisation algorithms (Nonlinear, Combinatorial etc.), High-Performance computing
    Invited Senior Researcher,
    Yusuke HAMA
    quantum algorithms for optimization, machine learning, and materials informatics quantum circuit transpilation quantum error mitigation, suppression, and correction
    Concurrent post,
    Toshihiro KATASHITA
    Concurrent post,
    Hisao NAKAMURA
    First principles simulation of chemical reaction, optical response, and electric and thermal transport in device materials
    Concurrent post,
    Katsuhiro ENDO
    Concurrent post,
    Takeaki TANIGUCHI
    Concurrent post,
    Naoya OKADA
    Concurrent post,
    Takenobu NAKAMURA
    Application of topological data Analysis for material science ; Molecular dynamics simulation for soft material, Free energy calculation ; Non-equilibrium statistical mechanics
    Concurrent post,
    Kotaro MAKINO
    Concurrent post,
    Naoki SHIGA
    Development of next generation drug discovery technology using quantum computers and AI
    Elucidation of the role and biosynthesis mechanism of functional RNA and their application towards drug discovery
    Concurrent post,
    Hisashi ANBUTSU
    Development of next generation drug discovery technology using quantum computers and AI
    Genome analysis of difficult-to-isolate and difficult-to-culture symbiotic bacteria

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