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Reply to: Deep reinforced learning heuristic tested on spin-glass ground states: The larger picture

Author

Listed:
  • Changjun Fan

    (National University of Defense Technology)

  • Mutian Shen

    (Washington University in St. Louis)

  • Zohar Nussinov

    (Washington University in St. Louis
    University of Oxford)

  • Zhong Liu

    (National University of Defense Technology)

  • Yizhou Sun

    (University of California)

  • Yang-Yu Liu

    (Brigham and Women’s Hospital and Harvard Medical School
    University of Illinois at Urbana-Champaign)

Abstract

No abstract is available for this item.

Suggested Citation

  • Changjun Fan & Mutian Shen & Zohar Nussinov & Zhong Liu & Yizhou Sun & Yang-Yu Liu, 2023. "Reply to: Deep reinforced learning heuristic tested on spin-glass ground states: The larger picture," Nature Communications, Nature, vol. 14(1), pages 1-4, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41108-w
    DOI: 10.1038/s41467-023-41108-w
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    References listed on IDEAS

    as
    1. Romá, F. & Risau-Gusman, S. & Ramirez-Pastor, A.J. & Nieto, F. & Vogel, E.E., 2009. "The ground state energy of the Edwards–Anderson spin glass model with a parallel tempering Monte Carlo algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2821-2838.
    2. Changjun Fan & Mutian Shen & Zohar Nussinov & Zhong Liu & Yizhou Sun & Yang-Yu Liu, 2023. "Searching for spin glass ground states through deep reinforcement learning," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. Stefan Boettcher, 2023. "Deep reinforced learning heuristic tested on spin-glass ground states: The larger picture," Nature Communications, Nature, vol. 14(1), pages 1-3, December.
    4. S. Boettcher, 2005. "Extremal optimization for Sherrington-Kirkpatrick spin glasses," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 46(4), pages 501-505, August.
    Full references (including those not matched with items on IDEAS)

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