Speckle-Driven Single-Shot Orbital Angular Momentum Recognition with Ultra-Low Sampling Density
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arXiv
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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866917141906718720 |
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| author | Wang, Zhiyuan Li, Haoran Zhong, Tianting Zhao, Qi R V, Vinu Li, Huanhao Yu, Zhipeng Pu, Jixiong Chen, Ziyang Yuan, Xiaocong Lai, Puxiang |
| author_facet | Wang, Zhiyuan Li, Haoran Zhong, Tianting Zhao, Qi R V, Vinu Li, Huanhao Yu, Zhipeng Pu, Jixiong Chen, Ziyang Yuan, Xiaocong Lai, Puxiang |
| contents | Orbital angular momentum (OAM) recognition of vortex beams is critical for applications ranging from optical communications to quantum technologies. However, conventional approaches designed for free-space propagation struggle when light passes through scattering media, such as multimode fibers (MMF), and often rely on high-resolution sensors with tens of thousands of pixels to record detailed intensity profiles. Here, by harnessing scattering media as intrinsic encoders rather than detrimental factors, we introduce a speckle-driven OAM recognition technique termed patially multiplexed points detection (SMPD). This method extracts intensity information from a few spatially distributed points in a speckle plane, where object feature is naturally multiplexed, thereby transforming scattering from a detrimental effect into an efficient encoding mechanism while drastically reducing sampling requirements. Remarkably, it achieves over 99% retrieval accuracy for OAMs recognition using just 16 sampling points, corresponding to a sampling density of 0.024% compared with conventional imaging-based approaches. Furthermore, spatiotemporally interleaved vortex beams decoding, highcapacity OAM-multiplexed communication, MNIST, and Fashion-MNIST classification are implemented to verify the versatility of SMPD. This work establishes a scalable strategy for efficient optical information processing and fiberbased sensing in complex environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_04658 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Speckle-Driven Single-Shot Orbital Angular Momentum Recognition with Ultra-Low Sampling Density Wang, Zhiyuan Li, Haoran Zhong, Tianting Zhao, Qi R V, Vinu Li, Huanhao Yu, Zhipeng Pu, Jixiong Chen, Ziyang Yuan, Xiaocong Lai, Puxiang Optics Orbital angular momentum (OAM) recognition of vortex beams is critical for applications ranging from optical communications to quantum technologies. However, conventional approaches designed for free-space propagation struggle when light passes through scattering media, such as multimode fibers (MMF), and often rely on high-resolution sensors with tens of thousands of pixels to record detailed intensity profiles. Here, by harnessing scattering media as intrinsic encoders rather than detrimental factors, we introduce a speckle-driven OAM recognition technique termed patially multiplexed points detection (SMPD). This method extracts intensity information from a few spatially distributed points in a speckle plane, where object feature is naturally multiplexed, thereby transforming scattering from a detrimental effect into an efficient encoding mechanism while drastically reducing sampling requirements. Remarkably, it achieves over 99% retrieval accuracy for OAMs recognition using just 16 sampling points, corresponding to a sampling density of 0.024% compared with conventional imaging-based approaches. Furthermore, spatiotemporally interleaved vortex beams decoding, highcapacity OAM-multiplexed communication, MNIST, and Fashion-MNIST classification are implemented to verify the versatility of SMPD. This work establishes a scalable strategy for efficient optical information processing and fiberbased sensing in complex environments. |
| title | Speckle-Driven Single-Shot Orbital Angular Momentum Recognition with Ultra-Low Sampling Density |
| topic | Optics |
| url | https://arxiv.org/abs/2310.04658 |