Superscattering of Underwater Sound via Deep Learning Approach
Wenjie Miao, Zhiang Linghu, Qiujiao Du, Pai Peng, and Fengming Liu*
School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, China
Abstract ：We design a multilayer cylindrical structure to realize superscattering of underwater sound. Because of the near degeneracy of resonances in multiple channels of the structure, the scattering contributions from these resonances can overlap to break the single-channel limit of subwavelength objects. However, tuning the design parameters to achieve the target response is an optimization process that is tedious and time-consuming. Here, we demonstrate that a well-trained tandem neural network can deal with this problem efficiently, which can not only forwardly predict the scattering spectra of the multilayer structure with high precision, but also inversely design the required structural parameters efficiently.
收稿日期: 2022-10-29
出版日期: 2022-12-26
:
43.60.Np
(Acoustic signal processing techniques for neural nets and learning systems)
43.60.Pt
(Signal processing techniques for acoustic inverse problems)
03.65.Nk
(Scattering theory)
[1] Liu Z Y, Zhang X X, Mao Y W, Zhu Y Y, Yang Z Y, Chan C T, and Sheng P 2000 Science 289 1734 [2] Pendry J B, Schurig D, and Smith D R 2006 Science 312 1780 [3] Cummer S A, Christensen J, and Alu A 2016 Nat. Rev. Mater. 1 16001 [4] Ma G C and Sheng P 2016 Sci. Adv. 2 e1501595 [5] Assouar B, Liang B, Wu Y, Li Y, Cheng J C, and Jing Y 2018 Nat. Rev. Mater. 3 460 [6] Aizpurua J, Hanarp P, Sutherland D S, Kall M, Bryant G W, F J, and de Abajo G 2003 Phys. Rev. Lett. 90 057401 [7] Tribelsky M I and Lykyanchuk B S 2006 Phys. Rev. Lett. 97 263902 [8] Leonhardt U 2006 Science 312 1777 [9] Schurig D, Mock J J, Justice B J, Cummer S A, Pendry J B, Starr A F, and Smith D R 2006 Science 314 977 [10] Zhu X F, Liang B, Kan W W, Zou X Y, and Cheng J S 2011 Phys. Rev. Lett. 106 014301 [11] Zhang S, Xia C G, and Fang N 2011 Phys. Rev. Lett. 106 024301 [12] Chen Y Y, Liu H J, Reilly M, Bae H, and Yu M 2014 Nat. Commun. 5 5247 [13] Fleury R, Sounas D, and Alu A 2015 Nat. Commun. 6 5905 [14] Lu G X, Ding E L, Wang Y Y, Ping X Y, Cui J, Liu X Z, and Liu X J 2017 Appl. Phys. Lett. 110 123507 [15] Bogue R 2017 Sens. Rev. 37 305 [16] Fan X D, Zhu Y F, Liang B, Cheng J C, and Zhang L K 2018 Phys. Rev. Appl. 9 034035 [17] Landi M, Zhao J J, Prather W E, Wu Y, and Zhang L K 2018 Phys. Rev. Lett. 120 114301 [18] Liu F M, Zhang S, Luo L C, Li W P, Wang Z Y, and Ke M Z 2019 Phys. Rev. Appl. 12 064063 [19] Luo J, Li X, Zhang X Y, Guo J J, Liu W, Lai Y, Zhan Y H, and Huang M 2021 Opt. Express 29 10527 [20] Peurifoy J, Shen Y C, Jing L, Yang Y, Cano-Renteria F, DeLacy B G, Joannopoulos J D, Tegmark M, and Soljacic M 2018 Sci. Adv. 4 eaar4206 [21] So S, Mun J, and Rho J 2019 ACS Appl. Mater. Interfaces 11 24264 [22] Liu Q S, Hang R L, Song H H, and Li Z 2018 IEEE Trans. Geosci. Remote Sens. 56 117 [23] Orazbayev B and Fleury R 2020 Phys. Rev. X 10 031029 [24] Qian C, Zheng B, Shen Y C, Jing L, Li E P, Shen L, and Chen H S 2020 Nat. Photon. 14 383 [25] Luo Y T, Li P Q, Li D T, Peng Y G, Geng Z G, Xie S H, Li Y, Alu A, Zhu J, and Zhu X F 2020 Research 2020 8757403 [26] Liu D J, Tan Y X, Khoram E F, and Yu Z F 2018 ACS Photon. 5 1365 [27] Ahmed W W, Farhat M, Zhang X L, and Wu Y 2021 Phys. Rev. Res. 3 013142
[1]
.
2023, Vol. 40 
