IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-42921-z.html
   My bibliography  Save this article

Dispersion engineered metasurfaces for broadband, high-NA, high-efficiency, dual-polarization analog image processing

Author

Listed:
  • Michele Cotrufo

    (City University of New York
    University of Rochester)

  • Akshaj Arora

    (City University of New York
    Graduate Center of the City University of New York)

  • Sahitya Singh

    (City University of New York
    Graduate Center of the City University of New York)

  • Andrea Alù

    (City University of New York
    Graduate Center of the City University of New York)

Abstract

Optical metasurfaces performing analog image processing – such as spatial differentiation and edge detection – hold the potential to reduce processing times and power consumption, while avoiding bulky 4 F lens systems. However, current designs have been suffering from trade-offs between spatial resolution, throughput, polarization asymmetry, operational bandwidth, and isotropy. Here, we show that dispersion engineering provides an elegant way to design metasurfaces where all these critical metrics are simultaneously optimized. We experimentally demonstrate silicon metasurfaces performing isotropic and dual-polarization edge detection, with numerical apertures above 0.35 and spectral bandwidths of 35 nm around 1500 nm. Moreover, we introduce quantitative metrics to assess the efficiency of these devices. Thanks to the low loss nature and dual-polarization response, our metasurfaces feature large throughput efficiencies, approaching the theoretical maximum for a given NA. Our results pave the way for low-loss, high-efficiency and broadband optical computing and image processing with free-space metasurfaces.

Suggested Citation

  • Michele Cotrufo & Akshaj Arora & Sahitya Singh & Andrea Alù, 2023. "Dispersion engineered metasurfaces for broadband, high-NA, high-efficiency, dual-polarization analog image processing," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-42921-z
    DOI: 10.1038/s41467-023-42921-z
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-42921-z
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-023-42921-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Farzad Zangeneh-Nejad & Romain Fleury, 2019. "Topological analog signal processing," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    2. J. Feldmann & N. Youngblood & C. D. Wright & H. Bhaskaran & W. H. P. Pernice, 2019. "All-optical spiking neurosynaptic networks with self-learning capabilities," Nature, Nature, vol. 569(7755), pages 208-214, May.
    3. Tengfeng Zhu & Cheng Guo & Junyi Huang & Haiwen Wang & Meir Orenstein & Zhichao Ruan & Shanhui Fan, 2021. "Topological optical differentiator," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
    4. Tengfeng Zhu & Yihan Zhou & Yijie Lou & Hui Ye & Min Qiu & Zhichao Ruan & Shanhui Fan, 2017. "Plasmonic computing of spatial differentiation," Nature Communications, Nature, vol. 8(1), pages 1-6, August.
    5. Wim Bogaerts & Daniel Pérez & José Capmany & David A. B. Miller & Joyce Poon & Dirk Englund & Francesco Morichetti & Andrea Melloni, 2020. "Programmable photonic circuits," Nature, Nature, vol. 586(7828), pages 207-216, October.
    6. Tengfeng Zhu & Cheng Guo & Junyi Huang & Haiwen Wang & Meir Orenstein & Zhichao Ruan & Shanhui Fan, 2021. "Publisher Correction: Topological optical differentiator," Nature Communications, Nature, vol. 12(1), pages 1-1, December.
    7. MohammadSadegh Faraji-Dana & Ehsan Arbabi & Amir Arbabi & Seyedeh Mahsa Kamali & Hyounghan Kwon & Andrei Faraon, 2018. "Compact folded metasurface spectrometer," Nature Communications, Nature, vol. 9(1), pages 1-8, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jérôme Sol & David R. Smith & Philipp Hougne, 2022. "Meta-programmable analog differentiator," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    2. Yurou Jia & Suying Zhang & Xuan Zhang & Houyou Long & Caibin Xu & Yechao Bai & Ying Cheng & Dajian Wu & Mingxi Deng & Cheng-Wei Qiu & Xiaojun Liu, 2024. "Compact meta-differentiator for achieving isotropically high-contrast ultrasonic imaging," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    3. Zi Wang & Lorry Chang & Feifan Wang & Tiantian Li & Tingyi Gu, 2022. "Integrated photonic metasystem for image classifications at telecommunication wavelength," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    4. Xinwei Wang & Hao Wang & Jinlu Wang & Xingsi Liu & Huijie Hao & You Sin Tan & Yilei Zhang & He Zhang & Xiangyan Ding & Weisong Zhao & Yuhang Wang & Zhengang Lu & Jian Liu & Joel K. W. Yang & Jiubin Ta, 2023. "Single-shot isotropic differential interference contrast microscopy," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    5. Zi-Lan Deng & Meng-Xia Hu & Shanfeng Qiu & Xianfeng Wu & Adam Overvig & Xiangping Li & Andrea Alù, 2024. "Poincaré sphere trajectory encoding metasurfaces based on generalized Malus’ law," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
    6. Yang Liu & Mingchuan Huang & Qiankun Chen & Douguo Zhang, 2022. "Single planar photonic chip with tailored angular transmission for multiple-order analog spatial differentiator," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    7. Ibrahim Tanriover & Sina Abedini Dereshgi & Koray Aydin, 2023. "Metasurface enabled broadband all optical edge detection in visible frequencies," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    8. Steven Becker & Dirk Englund & Birgit Stiller, 2024. "An optoacoustic field-programmable perceptron for recurrent neural networks," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
    9. Georgy Ermolaev & Kirill Voronin & Denis G. Baranov & Vasyl Kravets & Gleb Tselikov & Yury Stebunov & Dmitry Yakubovsky & Sergey Novikov & Andrey Vyshnevyy & Arslan Mazitov & Ivan Kruglov & Sergey Zhu, 2022. "Topological phase singularities in atomically thin high-refractive-index materials," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    10. Biye Xie & Renwen Huang & Shiyin Jia & Zemeng Lin & Junzheng Hu & Yao Jiang & Shaojie Ma & Peng Zhan & Minghui Lu & Zhenlin Wang & Yanfeng Chen & Shuang Zhang, 2023. "Bulk-local-density-of-state correspondence in topological insulators," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    11. Wen Zhou & Bowei Dong & Nikolaos Farmakidis & Xuan Li & Nathan Youngblood & Kairan Huang & Yuhan He & C. David Wright & Wolfram H. P. Pernice & Harish Bhaskaran, 2023. "In-memory photonic dot-product engine with electrically programmable weight banks," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    12. Ali Momeni & Romain Fleury, 2022. "Electromagnetic wave-based extreme deep learning with nonlinear time-Floquet entanglement," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    13. Sajjad Abdollahramezani & Omid Hemmatyar & Mohammad Taghinejad & Hossein Taghinejad & Alex Krasnok & Ali A. Eftekhar & Christian Teichrib & Sanchit Deshmukh & Mostafa A. El-Sayed & Eric Pop & Matthias, 2022. "Electrically driven reprogrammable phase-change metasurface reaching 80% efficiency," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    14. Ui Yeon Won & Quoc An Vu & Sung Bum Park & Mi Hyang Park & Van Dam Do & Hyun Jun Park & Heejun Yang & Young Hee Lee & Woo Jong Yu, 2023. "Multi-neuron connection using multi-terminal floating–gate memristor for unsupervised learning," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    15. H. H. Zhu & J. Zou & H. Zhang & Y. Z. Shi & S. B. Luo & N. Wang & H. Cai & L. X. Wan & B. Wang & X. D. Jiang & J. Thompson & X. S. Luo & X. H. Zhou & L. M. Xiao & W. Huang & L. Patrick & M. Gu & L. C., 2022. "Space-efficient optical computing with an integrated chip diffractive neural network," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    16. Yang Yang & Robert J. Chapman & Ben Haylock & Francesco Lenzini & Yogesh N. Joglekar & Mirko Lobino & Alberto Peruzzo, 2024. "Programmable high-dimensional Hamiltonian in a photonic waveguide array," Nature Communications, Nature, vol. 15(1), pages 1-7, December.
    17. Zhaoyi Li & Raphaël Pestourie & Joon-Suh Park & Yao-Wei Huang & Steven G. Johnson & Federico Capasso, 2022. "Inverse design enables large-scale high-performance meta-optics reshaping virtual reality," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    18. Brandon Born & Sung-Hoon Lee & Jung-Hwan Song & Jeong Yub Lee & Woong Ko & Mark L. Brongersma, 2023. "Off-axis metasurfaces for folded flat optics," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    19. Mark Dong & Julia M. Boyle & Kevin J. Palm & Matthew Zimmermann & Alex Witte & Andrew J. Leenheer & Daniel Dominguez & Gerald Gilbert & Matt Eichenfield & Dirk Englund, 2023. "Synchronous micromechanically resonant programmable photonic circuits," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    20. Xiaoyun Yuan & Yong Wang & Zhihao Xu & Tiankuang Zhou & Lu Fang, 2023. "Training large-scale optoelectronic neural networks with dual-neuron optical-artificial learning," Nature Communications, Nature, vol. 14(1), pages 1-10, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-42921-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.