High-sensitivity computational miniaturized terahertz spectrometer using a plasmonic filter array and a modified multilayer residual CNN
Spectrometer miniaturization is desired for handheld and portable applications, yet nearly no miniaturized spectrometer is reported operating within terahertz (THz) waveband. Computational strategy, which can acquire incident spectral information through encoding and decoding it using optical device...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2023-11-01
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| Series: | Nanophotonics |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/nanoph-2023-0581 |
| _version_ | 1827620660322500608 |
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| author | Liu Mengjuan Yang Meichen Zhu Jiaqi Zhu He Wang Yao Ren Ziyang Zhai Yihui Zhu Haiming Shan Yufeng Qi Hongxing Duan Junli Wu Huizhen Dai Ning |
| author_facet | Liu Mengjuan Yang Meichen Zhu Jiaqi Zhu He Wang Yao Ren Ziyang Zhai Yihui Zhu Haiming Shan Yufeng Qi Hongxing Duan Junli Wu Huizhen Dai Ning |
| author_sort | Liu Mengjuan |
| collection | DOAJ |
| description | Spectrometer miniaturization is desired for handheld and portable applications, yet nearly no miniaturized spectrometer is reported operating within terahertz (THz) waveband. Computational strategy, which can acquire incident spectral information through encoding and decoding it using optical devices and reconstruction algorithms, respectively, is widely employed in spectrometer miniaturization as artificial intelligence emerges. We demonstrate a computational miniaturized THz spectrometer, where a plasmonic filter array tailors the spectral response of a blocked-impurity-band detector. Besides, an adaptive deep-learning algorithm is proposed for spectral reconstructions with curbing the negative impact from the optical property of the filter array. Our spectrometer achieves modest spectral resolution (2.3 cm−1) compared with visible and infrared miniaturized spectrometers, outstanding sensitivity (e.g., signal-to-noise ratio, 6.4E6: 1) superior to common benchtop THz spectrometers. The combination of THz optical devices and reconstruction algorithms provides a route toward THz spectrometer miniaturization, and further extends the applicable sphere of the THz spectroscopy technique. |
| first_indexed | 2024-03-09T10:51:09Z |
| format | Article |
| id | doaj.art-1d92494267c94602957f60b9b410707e |
| institution | Directory Open Access Journal |
| issn | 2192-8614 |
| language | English |
| last_indexed | 2024-03-09T10:51:09Z |
| publishDate | 2023-11-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Nanophotonics |
| spelling | doaj.art-1d92494267c94602957f60b9b410707e2023-12-01T07:18:54ZengDe GruyterNanophotonics2192-86142023-11-0112234375438510.1515/nanoph-2023-0581High-sensitivity computational miniaturized terahertz spectrometer using a plasmonic filter array and a modified multilayer residual CNNLiu Mengjuan0Yang Meichen1Zhu Jiaqi2Zhu He3Wang Yao4Ren Ziyang5Zhai Yihui6Zhu Haiming7Shan Yufeng8Qi Hongxing9Duan Junli10Wu Huizhen11Dai Ning12Zhejiang Province Key Laboratory of Quantum Technology and Devices, School of Physics, and State Key Laboratory of Silicon and Advanced Semiconductor Materials, Zhejiang University, Hangzhou310058, ChinaHangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, Zhejiang310024, ChinaZhejiang Province Key Laboratory of Quantum Technology and Devices, School of Physics, and State Key Laboratory of Silicon and Advanced Semiconductor Materials, Zhejiang University, Hangzhou310058, ChinaHangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, Zhejiang310024, ChinaZhejiang Province Key Laboratory of Quantum Technology and Devices, School of Physics, and State Key Laboratory of Silicon and Advanced Semiconductor Materials, Zhejiang University, Hangzhou310058, ChinaZhejiang Province Key Laboratory of Quantum Technology and Devices, School of Physics, and State Key Laboratory of Silicon and Advanced Semiconductor Materials, Zhejiang University, Hangzhou310058, ChinaZhejiang Province Key Laboratory of Quantum Technology and Devices, School of Physics, and State Key Laboratory of Silicon and Advanced Semiconductor Materials, Zhejiang University, Hangzhou310058, ChinaZhejiang Province Key Laboratory of Quantum Technology and Devices, School of Physics, and State Key Laboratory of Silicon and Advanced Semiconductor Materials, Zhejiang University, Hangzhou310058, ChinaHangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, Zhejiang310024, ChinaHangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, Zhejiang310024, ChinaHangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, Zhejiang310024, ChinaZhejiang Province Key Laboratory of Quantum Technology and Devices, School of Physics, and State Key Laboratory of Silicon and Advanced Semiconductor Materials, Zhejiang University, Hangzhou310058, ChinaHangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, Zhejiang310024, ChinaSpectrometer miniaturization is desired for handheld and portable applications, yet nearly no miniaturized spectrometer is reported operating within terahertz (THz) waveband. Computational strategy, which can acquire incident spectral information through encoding and decoding it using optical devices and reconstruction algorithms, respectively, is widely employed in spectrometer miniaturization as artificial intelligence emerges. We demonstrate a computational miniaturized THz spectrometer, where a plasmonic filter array tailors the spectral response of a blocked-impurity-band detector. Besides, an adaptive deep-learning algorithm is proposed for spectral reconstructions with curbing the negative impact from the optical property of the filter array. Our spectrometer achieves modest spectral resolution (2.3 cm−1) compared with visible and infrared miniaturized spectrometers, outstanding sensitivity (e.g., signal-to-noise ratio, 6.4E6: 1) superior to common benchtop THz spectrometers. The combination of THz optical devices and reconstruction algorithms provides a route toward THz spectrometer miniaturization, and further extends the applicable sphere of the THz spectroscopy technique.https://doi.org/10.1515/nanoph-2023-0581computational miniaturized terahertz spectrometerplasmonic filtersadaptive deep-learning algorithm |
| spellingShingle | Liu Mengjuan Yang Meichen Zhu Jiaqi Zhu He Wang Yao Ren Ziyang Zhai Yihui Zhu Haiming Shan Yufeng Qi Hongxing Duan Junli Wu Huizhen Dai Ning High-sensitivity computational miniaturized terahertz spectrometer using a plasmonic filter array and a modified multilayer residual CNN Nanophotonics computational miniaturized terahertz spectrometer plasmonic filters adaptive deep-learning algorithm |
| title | High-sensitivity computational miniaturized terahertz spectrometer using a plasmonic filter array and a modified multilayer residual CNN |
| title_full | High-sensitivity computational miniaturized terahertz spectrometer using a plasmonic filter array and a modified multilayer residual CNN |
| title_fullStr | High-sensitivity computational miniaturized terahertz spectrometer using a plasmonic filter array and a modified multilayer residual CNN |
| title_full_unstemmed | High-sensitivity computational miniaturized terahertz spectrometer using a plasmonic filter array and a modified multilayer residual CNN |
| title_short | High-sensitivity computational miniaturized terahertz spectrometer using a plasmonic filter array and a modified multilayer residual CNN |
| title_sort | high sensitivity computational miniaturized terahertz spectrometer using a plasmonic filter array and a modified multilayer residual cnn |
| topic | computational miniaturized terahertz spectrometer plasmonic filters adaptive deep-learning algorithm |
| url | https://doi.org/10.1515/nanoph-2023-0581 |
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