Analog Quantum Optimization

Analog Quantum Optimization is an analog quantum computation paradigm that leverages continuous-time evolution of quantum states in a programmable energy landscape to solve combinatorial optimization problems by guiding the system toward its ground state.

10

Publications

960

Citations

32

Authors

21

Institutions

Publications per year

2017–2026

7

Authors

32

  1. HG
    Helmut G. Katzgraber

    Texas A&M University, United States

    2 publications · 54 citations

    2

    h-index

  2. MT
    Matthias Troyer

    ETH Zurich, Switzerland

    2 publications · 48 citations

    2

    h-index

  3. HY
    Hiroyasu Yamahara

    The University of Tokyo, Japan

    1 publications · 14 citations

    1

    h-index

  4. BH
    Bettina Heim

    Max Planck Institute for the Science of Light, Germany

    1 publications · 11 citations

    1

    h-index

  5. DA
    Daniel A. Lidar

    University of Southern California, United States

    1 publications · 61 citations

    1

    h-index

1–5 of 32

Venues

  1. Quantum Science and Technology

    QST · 1 publications · 17 citations

    1

    h-index

  2. arXiv (Cornell University)

    Repository · 1 publications · 11 citations

    1

    h-index

  3. PRX Quantum

    1 publications · 37 citations

    1

    h-index

  4. Physical review. A/Physical review, A

    PRA · 1 publications · 32 citations

    1

    h-index

  5. Physical Review A

    PRA · 1 publications · 61 citations

    1

    h-index

1–5