Feng R, Tian Y K, Liu Y L, et al. Polarization-multiplexed optical differentiation using topological metasurfaces[J]. Opto-Electron Eng, 2023, 50(9): 230172. doi: 10.12086/oee.2023.230172
Citation: Feng R, Tian Y K, Liu Y L, et al. Polarization-multiplexed optical differentiation using topological metasurfaces[J]. Opto-Electron Eng, 2023, 50(9): 230172. doi: 10.12086/oee.2023.230172

Polarization-multiplexed optical differentiation using topological metasurfaces

    Fund Project: Project supported by National Natural Science Foundation of China (12274105), Heilongjiang Natural Science Funds for Distinguished Young Scholar (JQ2022A001), Fundamental Research Funds for the Central Universities (HIT.OCEF.2021020, 2023FRFK06007), and the Joint Guiding Project of Natural Science Foundation of Heilongjiang Province (LH2023A006). The authors thank the HPC Studio at Physics School of Harbin Institute of Technology for access to computing resources through INSPUR-HPC@PHY.HIT.
More Information
  • Optical analog computing avoids the photoelectric conversion in various application scenarios by directly modulating the optical input in the spatial domain. Therefore, it has become a research focus in many applications such as image processing. In this paper, a polarization-multiplexed optical analog computing metasurface structure based on the Green's function method is designed using topologal optimization. Under different linearly polarized light incidence, this topological metasurface can independently tailor the amplitude and phase of the transmitted light field. It achieves bright-field imaging and one-dimensional second-order differentiation operations in orthogonal polarization states, as well as a polarization- controlled differentiation direction for a multiplexed differential system. These polarization-multiplexed designs can play a vital role in more optical computing application scenarios.
  • 加载中
  • [1] Zhou Y, Zheng H Y, Kravchenko I I, et al. Flat optics for image differentiation[J]. Nat Photonics, 2020, 14(5): 316−323. doi: 10.1038/s41566-020-0591-3

    CrossRef Google Scholar

    [2] Silva A, Monticone F, Castaldi G, et al. Performing mathematical operations with metamaterials[J]. Science, 2014, 343(6167): 160−163. doi: 10.1126/science.1242818

    CrossRef Google Scholar

    [3] Xu C Y, Wang Y L, Zhang C, et al. Optical spatiotemporal differentiator using a bilayer plasmonic grating[J]. Opt Lett, 2021, 46(17): 4418−4421. doi: 10.1364/OL.436033

    CrossRef Google Scholar

    [4] He Y L, Xie Z Q, Yang B, et al. Controllable photonic spin Hall effect with phase function construction[J]. Photonics Res, 2020, 8(6): 963−971. doi: 10.1364/PRJ.388838

    CrossRef Google Scholar

    [5] Yang W J, Yu X Y, Zhang J L, et al. Plasmonic transmitted optical differentiator based on the subwavelength gold gratings[J]. Opt Lett, 2020, 45(8): 2295−2298. doi: 10.1364/OL.390566

    CrossRef Google Scholar

    [6] Zhu T F, Zhou Y H, Lou Y J, et al. Plasmonic computing of spatial differentiation[J]. Nat Commun, 2017, 8: 15391. doi: 10.1038/ncomms15391

    CrossRef Google Scholar

    [7] Kulishov M, Azaña J. Long-period fiber gratings as ultrafast optical differentiators[J]. Opt Lett, 2005, 30(20): 2700−2702. doi: 10.1364/OL.30.002700

    CrossRef Google Scholar

    [8] Liu F F, Wang T, Qiang L, et al. Compact optical temporal differentiator based on silicon microring resonator[J]. Opt Express, 2008, 16(20): 15880−15886. doi: 10.1364/OE.16.015880

    CrossRef Google Scholar

    [9] Huang T L, Zheng A L, Dong J J, et al. Terahertz-bandwidth photonic temporal differentiator based on a silicon-on-isolator directional coupler[J]. Opt Lett, 2015, 40(23): 5614−5617. doi: 10.1364/OL.40.005614

    CrossRef Google Scholar

    [10] Yan S Q, Cheng Z W, Frandsen L H, et al. Bandwidth-adaptable silicon photonic differentiator employing a slow light effect[J]. Opt Lett, 2017, 42(8): 1596−1599. doi: 10.1364/OL.42.001596

    CrossRef Google Scholar

    [11] Ngo N Q. Design of an optical temporal integrator based on a phase-shifted fiber Bragg grating in transmission[J]. Opt Lett, 2007, 32(20): 3020−3022. doi: 10.1364/OL.32.003020

    CrossRef Google Scholar

    [12] Ferrera M, Park Y, Razzari L, et al. On-chip CMOS-compatible all-optical integrator[J]. Nat Commun, 2010, 1(1): 29. doi: 10.1038/ncomms1028

    CrossRef Google Scholar

    [13] Zangeneh-Nejad F, Khavasi A. Spatial integration by a dielectric slab and its planar graphene-based counterpart[J]. Opt Lett, 2017, 42(10): 1954−1957. doi: 10.1364/OL.42.001954

    CrossRef Google Scholar

    [14] Wang X, Zhou F, Yan S Q, et al. Broadband on-chip integrator based on silicon photonic phase-shifted Bragg grating[J]. Photonics Res, 2017, 5(3): 182−186. doi: 10.1364/PRJ.5.000182

    CrossRef Google Scholar

    [15] Kwon H, Sounas D, Cordaro A, et al. Nonlocal metasurfaces for optical signal processing[J]. Phys Rev Lett, 2018, 121(17): 173004. doi: 10.1103/PhysRevLett.121.173004

    CrossRef Google Scholar

    [16] Woods D, Naughton T J. Photonic neural networks[J]. Nat Phys, 2012, 8(4): 257−259. doi: 10.1038/nphys2283

    CrossRef Google Scholar

    [17] Wu C M, Yu H S, Lee S, et al. Programmable phase-change metasurfaces on waveguides for multimode photonic convolutional neural network[J]. Nat Commun, 2021, 12(1): 96. doi: 10.1038/s41467-020-20365-z

    CrossRef Google Scholar

    [18] Shen Y C, Harris N C, Skirlo S, et al. Deep learning with coherent nanophotonic circuits[J]. Nat Photonics, 2017, 11(7): 441−446. doi: 10.1038/nphoton.2017.93

    CrossRef Google Scholar

    [19] Huo P C, Zhang C, Zhu W Q, et al. Photonic spin-multiplexing metasurface for switchable spiral phase contrast imaging[J]. Nano Lett, 2020, 20(4): 2791−2798. doi: 10.1021/acs.nanolett.0c00471

    CrossRef Google Scholar

    [20] He Q, Zhang F, Pu M B, et al. Monolithic metasurface spatial differentiator enabled by asymmetric photonic spin-orbit interactions[J]. Nanophotonics, 2021, 10(1): 741−748. doi: 10.1515/nanoph-2020-0366

    CrossRef Google Scholar

    [21] Gao H, Fan X, Wang Y, et al. Multi-foci metalens for spectra and polarization ellipticity recognition and reconstruction[J]. Opto-Electron Sci, 2023, 2: 220026. doi: 10.29026/oes.2023.220026

    CrossRef Google Scholar

    [22] Khonina S N, Kazanskiy N L, Butt M A, et al. Optical multiplexing techniques and their marriage for on-chip and optical fiber communication: a review[J]. Opto-Electron Adv, 2022, 5: 210127. doi: 10.29026/oea.2022.210127

    CrossRef Google Scholar

    [23] Liu Y M, Zhang X. Metamaterials: a new frontier of science and technology[J]. Chem Soc Rev, 2011, 40(5): 2494−2507. doi: 10.1039/c0cs00184h

    CrossRef Google Scholar

    [24] Liu W W, Li Z C, Li Z, et al. Energy-tailorable spin-selective multifunctional metasurfaces with full fourier components[J]. Adv Mater, 2019, 31(32): 1901729. doi: 10.1002/adma.201901729

    CrossRef Google Scholar

    [25] Feng H, Li Q T, Wan W P, et al. Spin-switched three-dimensional full-color scenes based on a dielectric meta-hologram[J]. ACS Photonics, 2019, 6(11): 2910−2916. doi: 10.1021/acsphotonics.9b01017

    CrossRef Google Scholar

    [26] Fan Q, Zhu W Q, Liang Y Z, et al. Broadband generation of photonic spin-controlled arbitrary accelerating light beams in the visible[J]. Nano Lett, 2018, 19(2): 1158−1165. doi: 10.1021/acs.nanolett.8b04571

    CrossRef Google Scholar

    [27] Huang K, Deng J, Leong H S, et al. Ultraviolet Metasurfaces of≈80% Efficiency with Antiferromagnetic Resonances for Optical Vectorial Anti-Counterfeiting[J]. Laser Photonics Rev, 2019, 13(5): 1800289. doi: 10.1002/lpor.201800289

    CrossRef Google Scholar

    [28] Zhang C, Divitt S, Fan Q B, et al. Low-loss metasurface optics down to the deep ultraviolet region[J]. Light Sci Appl, 2020, 9: 55. doi: 10.1038/s41377-020-0287-y

    CrossRef Google Scholar

    [29] Wesemann L, Rickett J, Song J C, et al. Nanophotonics enhanced coverslip for phase imaging in biology[J]. Light Sci Appl, 2021, 10(1): 98. doi: 10.1038/s41377-021-00540-7

    CrossRef Google Scholar

    [30] Zhu T F, Guo C, Huang J Y, et al. Topological optical differentiator[J]. Nat Commun, 2021, 12(1): 680. doi: 10.1038/s41467-021-20972-4

    CrossRef Google Scholar

    [31] Long O Y, Guo C, Wang H W, et al. Isotropic topological second-order spatial differentiator operating in transmission mode[J]. Opt Lett, 2021, 46(13): 3247−3250. doi: 10.1364/OL.430699

    CrossRef Google Scholar

    [32] Ruan Z C. Spatial mode control of surface Plasmon polariton excitation with gain medium: from spatial differentiator to integrator[J]. Opt Lett, 2015, 40(4): 601−604. doi: 10.1364/OL.40.000601

    CrossRef Google Scholar

    [33] Liu M Z, Zhu W Q, Huo P C, et al. Multifunctional metasurfaces enabled by simultaneous and independent control of phase and amplitude for orthogonal polarization states[J]. Light Sci Appl, 2021, 10: 107. doi: 10.1038/s41377-021-00552-3

    CrossRef Google Scholar

    [34] Fan Q B, Liu M Z, Zhang C, et al. Independent amplitude control of arbitrary orthogonal states of polarization via dielectric metasurfaces[J]. Phys Rev Lett, 2020, 125(26): 267402. doi: 10.1103/PhysRevLett.125.267402

    CrossRef Google Scholar

    [35] Zhang F, Pu M B, Li X, et al. All-dielectric metasurfaces for simultaneous giant circular asymmetric transmission and wavefront shaping based on asymmetric photonic spin-orbit interactions[J]. Adv Funct Mater, 2017, 27: 1704295. doi: 10.1002/adfm.201704295

    CrossRef Google Scholar

    [36] Miller O. Photonic design: from fundamental solar cell physics to computational inverse design[D]. Berkeley: University of California, 2012.

    Google Scholar

  • With the continuous development of information technology, the requirements for signal processing in various application scenarios have become higher and higher, and the data capacity has also shown explosive growth. The processing of large amounts of data has become a worldwide problem. However, existing electronic technologies have limitations in terms of speed and power consumption, making it difficult to achieve real-time, high-throughput signal processing. In recent years, with the image spatial differentiation playing an increasingly important role in signal processing and other application fields, and the continuous advancement of micro-nano processing technology, optical analog computing has attracted much attention. It avoids the photoelectric conversion in various application scenarios by directly modulating the optical input in the spatial domain. There are two distinct approaches to realize the optical analog computing, one is based on the 4F optical systems, while the other is metasurface structures based on the Green's function method. Among them, the recently developed dielectric metasurfaces can realize various mathematical operations of optical signals, such as differentiation and integration, and has become one of the most interesting scientific and engineering topics. This paper presents the design of polarization-multiplexed optical analog computing metasurfaces based on the Green's function method. Numerical simulations using the Finite-Difference Time-Domain (FDTD) method were conducted to investigate the performance of the designed metasurfaces. The final single-layer metasurface structure is entirely binary after topological optimization, which can be constructed using titanium dioxide (TiO2) and air. Under different linearly polarized light incidences, this topological metasurface can independently tailor the amplitude and phase of the transmitted light field to achieve spatial optical differentiation functionalities. Two polarization-multiplexed dual-function analog computing metasurfaces were simulated and verified with the computational results meeting the expected design theory. One of them achieves bright-field imaging and one-dimensional second-order differentiation operations in orthogonal polarization states. The other design is a multiplexed differential system that can control the second-order differentiation operation direction in accordance with different orthogonal linear polarization states. For TE-polarized incidence, one-dimensional second-order differentiation is achieved in the x-direction, with no transmission in the y-direction. For TM-polarized incidence, one-dimensional second-order differentiation occurs in the y-direction, with no transmission in the x-direction, enabling the extraction of edge information in different directions for the orthogonal polarization states. These polarization- multiplexed designs can play a role in more optical computing application scenarios.

  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Figures(6)

Article Metrics

Article views() PDF downloads() Cited by()

Access History
Article Contents

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint