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<p>Plasmonic skyrmions are electromagnetic counterparts of topologically stable quasiparticles and could potentially be used as robust information carriers. However, practical applications require tunable devices that can encode the topological structures. Here we report a programmable platform that can encode plasmonic skyrmions with diverse topologies, including Néel-type skyrmions and merons. We synthesize harmonic skyrmions in the temporal dimension using ultrafast coding and apply the skyrmions in communication and sensing applications. In particular, we show that the programmable topological skyrmions can be used in robust and multichannel wireless communications, suggesting that the approach could provide communications in turbulent noise channels and extreme conditions. Together with a convolutional neural network, we also show that the platform can be used in the intelligent sensing of 20 animal figurines, achieving high recognition accuracy.</p>

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Programmable skyrmions for communication and sensing

  • 期刊论文

  • 发表日期：

    2026年4月29日

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  • Long Chen,
  • Xin Yu Li,
  • Yijie Shen,
  • Ze Gu,
  • Jian Lin Su,
  • Qiang Xiao,
  • Si Qi Huang,
  • Shi Long Qin,
  • Qian Ma,
  • Jian Wei You,
  • Tie Jun Cui

摘要

Plasmonic skyrmions are electromagnetic counterparts of topologically stable quasiparticles and could potentially be used as robust information carriers. However, practical applications require tunable devices that can encode the topological structures. Here we report a programmable platform that can encode plasmonic skyrmions with diverse topologies, including Néel-type skyrmions and merons. We synthesize harmonic skyrmions in the temporal dimension using ultrafast coding and apply the skyrmions in communication and sensing applications. In particular, we show that the programmable topological skyrmions can be used in robust and multichannel wireless communications, suggesting that the approach could provide communications in turbulent noise channels and extreme conditions. Together with a convolutional neural network, we also show that the platform can be used in the intelligent sensing of 20 animal figurines, achieving high recognition accuracy.