2023
DOI: 10.1002/lpor.202200536
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Broadband, Low‐Crosstalk, and Massive‐Channels OAM Modes De/Multiplexing Based on Optical Diffraction Neural Network

Abstract: Optical communication technology based on the wavelength, time, polarization, and complex amplitude of light is approaching a bottleneck, while the spatial dimension is relatively unexplored. Orbital angular momentum (OAM) beams are an important group of spatial light beams that are promising for increasing the optical communication capacity based on their orthogonality. To effectively utilize this spatial dimension of light, broadband and low‐crosstalk OAM mode de/multiplexing devices are indispensable. In th… Show more

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Cited by 12 publications
(10 citation statements)
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“…Multicasting Extended communication link [95][96][97][98][99][100][101][102][103][104][105][106][107][108][109][110][111][112] Switching Exchanging data [113][114][115][116][117][118][119][120][121][122][123][124][125][126][127] Filtering Extracting specific channel [128][129][130][131][132][133][134][135][136][137][138][139][140] Hopping Anti-interference [141][142][143][144]…”
Section: Oam-rd Schematic Diagram Function Referencementioning
confidence: 99%
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“…Multicasting Extended communication link [95][96][97][98][99][100][101][102][103][104][105][106][107][108][109][110][111][112] Switching Exchanging data [113][114][115][116][117][118][119][120][121][122][123][124][125][126][127] Filtering Extracting specific channel [128][129][130][131][132][133][134][135][136][137][138][139][140] Hopping Anti-interference [141][142][143][144]…”
Section: Oam-rd Schematic Diagram Function Referencementioning
confidence: 99%
“…Exchanging data [113][114][115][116][117][118][119][120][121][122][123][124][125][126][127] Filtering…”
Section: Oam Channel Multicastingmentioning
confidence: 99%
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“…2019年, Fontaine等 [60] 提出了一种特殊的变 换方法, 用于将笛卡尔坐标系中的点(x, y)转换为 处理能力 [67−72] . 然而, 这些方法主要集中在对单个 涡旋光束的模式转换.…”
Section: 涡旋光束具有螺旋相位结构unclassified
“…[10] Various applications, from image processing to data encryption, have been demonstrated with DNNs using terahertz radiation. [17][18][19][20] Research efforts have focused on developing DNNs for visible wavelengths for potential novel applications including optical computing, fluorescence imaging, and 3D holographic displays. [21][22][23] However, shorter wavelengths present a challenge for DNNs in the context of fabricating submicrometer DOI: 10.1002/adpr.202300310 Diffractive neural networks (DNNs) are emerging as a new machine learning hardware based on optical diffraction with parallel and high-throughput information processing.…”
Section: Introductionmentioning
confidence: 99%