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<p>An open, dynamic, and electromagnetically invisible space has been constructed using reconfigurable metasurfaces and self-play reinforcement learning. A model named MetaSeeker is proposed to optimize the cloaking performance of randomly distributed metasurfaces. The hidden objects can move freely within the constructed invisible space, with environmental similarity of 99.5%. This advancement provides an innovative solution for cloaking technologies in complex environments.</p><p></p>

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An open invisible space enabled by reconfigurable metasurfaces and self-play reinforcement learning

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月15日

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  • Xinman Yin,
  • Yanyu Zhao

摘要

An open, dynamic, and electromagnetically invisible space has been constructed using reconfigurable metasurfaces and self-play reinforcement learning. A model named MetaSeeker is proposed to optimize the cloaking performance of randomly distributed metasurfaces. The hidden objects can move freely within the constructed invisible space, with environmental similarity of 99.5%. This advancement provides an innovative solution for cloaking technologies in complex environments.