Hybrid spin and anomalous spin-momentum locking in photonic time crystals

Spin-momentum locking is an intrinsic property of evanescent electromagnetic waves, which implies that the transverse spin is locked with the dispersive momentum obeying the left-hand screw rule. More importantly, it fundamentally governs the polarization and transport of surface modes, resulting in the discovery of efficient spin-direction couplers, unidirectional guided waves, and photonic spin lattices. Modeling of time-varying media involves the dispersion effect, which is widely available in materials capable of dynamic modulation, potentially redefining a spin-momentum locking phenomenon. In this work, by introducing a nonlocal dispersive photonic time crystal interface model, we unveil the anomalous spin-momentum locking of surface electromagnetic waves due to time modulation. It is found that the interaction between multiple surface modes occurs under slight modulation, which is due to the hybridization of the spin angular momentum induced by the strong dispersion properties of the surface waves. In addition, we also consider the modulation amplitude and the modulation frequency as new degrees of freedom in the model, which enables the evolution of anomalous spin-momentum locking of surface plasmon polariton modes. Our work provides a unique perspective for a deeper understanding of spin-polarized transport induced by anomalous spin-momentum locking in time-varying photonic material systems, paving the way for engineering the spin structure and topological properties of electromagnetic waves with promising applications in the fields of spin optics and topological photonics.

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Publication Details

Journal
Physical review. B./Physical review. B
Published
2025-02-10
DOI
https://doi.org/10.1103/physrevb.111.075304
Citations
5
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
12.40

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article

Hybrid spin and anomalous spin-momentum locking in photonic time crystals

Chengxun Yuan, Jingfeng Yao, Ying Wang, Xin Ye et al.
5 citations
Physical review. B./Physical review. B
Neural Networks and Reservoir Computing
12.40
article

Hybrid spin and anomalous spin-momentum locking in photonic time crystals

Chengxun Yuan, Jingfeng Yao, Ying Wang, Xin Ye, Zhongxiang Zhou
article en
5 citations

Abstract

Spin-momentum locking is an intrinsic property of evanescent electromagnetic waves, which implies that the transverse spin is locked with the dispersive momentum obeying the left-hand screw rule. More importantly, it fundamentally governs the polarization and transport of surface modes, resulting in the discovery of efficient spin-direction couplers, unidirectional guided waves, and photonic spin lattices. Modeling of time-varying media involves the dispersion effect, which is widely available in materials capable of dynamic modulation, potentially redefining a spin-momentum locking phenomenon. In this work, by introducing a nonlocal dispersive photonic time crystal interface model, we unveil the anomalous spin-momentum locking of surface electromagnetic waves due to time modulation. It is found that the interaction between multiple surface modes occurs under slight modulation, which is due to the hybridization of the spin angular momentum induced by the strong dispersion properties of the surface waves. In addition, we also consider the modulation amplitude and the modulation frequency as new degrees of freedom in the model, which enables the evolution of anomalous spin-momentum locking of surface plasmon polariton modes. Our work provides a unique perspective for a deeper understanding of spin-polarized transport induced by anomalous spin-momentum locking in time-varying photonic material systems, paving the way for engineering the spin structure and topological properties of electromagnetic waves with promising applications in the fields of spin optics and topological photonics.

Physical review. B./Physical review. BVol. 111(7)
Harbin Institute of Technology (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Affordable and clean energy
Openalex Percentile: Top 2%
Neural Networks and Reservoir Computing
12.40
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