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Research progress of intelligent design of on-chip optical interconnection devices

Du Te Ma Han-Si Jiang Xin-Peng Zhao Fen Zhang Zhao-Jian Wang Zhi-Cheng Peng Zheng Zhang Yi-Yi Zhang Yu-Qing Luo Ming-Yu Zou Hong-Xin Wu Jia-Gui Yan Pei-Guang Zhu Gang-Yi Yu Yang He Xin Chen Huan Zhang Zhen-Fu Yang Jun-Bo

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Research progress of intelligent design of on-chip optical interconnection devices

Du Te, Ma Han-Si, Jiang Xin-Peng, Zhao Fen, Zhang Zhao-Jian, Wang Zhi-Cheng, Peng Zheng, Zhang Yi-Yi, Zhang Yu-Qing, Luo Ming-Yu, Zou Hong-Xin, Wu Jia-Gui, Yan Pei-Guang, Zhu Gang-Yi, Yu Yang, He Xin, Chen Huan, Zhang Zhen-Fu, Yang Jun-Bo
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  • Compared with traditional communication technologies such as electrical interconnection, optical interconnection technology has the advantages of large bandwidth, low energy consumption, anti-interference, etc. Therefore, optical interconnection is becoming an important approach and development trend of short distance and very short distance data terminal communication. As the chip level optical interconnection is implemented, silicon on insulator (SOI) based on-chip optical interconnection has been widely utilized with the support of a series of multiplexing technologies. In recent decades, many on-chip optical interconnection devices have been developed by using conventional design methods such as coupled-mode, multimode interference, and transmission line theories. However, when used in device design, these conventional methods often face the problems such as complex theoretical calculations and high labor costs. Many of the designed devices also encounter the problems of insufficient compactness and integration, and single function.Intelligent design method has the advantages such as pellucid principle, high freedom of optimization, and good material compatibility, which can solve the problems of conventional design methods to a large extent. With the widespread use of intelligent design methods in the design of on-chip optical interconnection devices, three main trends have emerged. Firstly, the size of on-chip optical interconnect device is gradually developing towards ultra compact size. Secondly, the number of intelligently designed controllable on-chip optical interconnect devices is increasing. Thirdly, on-chip optical interconnect devices are gradually developing towards integration and systematization. This paper summarizes the most commonly used intelligent design methods of photonic devices, including intelligent algorithms based intelligent design methods and neural networks based intelligent design methods. Then, the above three important research advances and trends of intelligently designed on-chip optical interconnection devices are analyzed in detail. At the same time, the applications of phase change materials in the design of controllable photonic devices are also reviewed. Finally, the future development of intelligently designed on-chip optical interconnection devices is discussed.
      Corresponding author: Yang Jun-Bo, yangjunbo@nudt.edu.cn
    • Funds: Project supported by the National Natural Science Foundation of China (Grant Nos. 60907003, 61805278, 12272407, 62275269, 62275271), the National Key R&D Program of China (Grant No. 2022YFF0706005), the China Postdoctoral Science Foundation (Grant No. 2018M633704), the Scientific Research Program of National University of Defense Technology, China (Grant Nos. JC13-02-13, ZK17-03-01), the Natural Science Foundation of Hunan Province, China (Grant No. 13JJ3001), and the Program for New Century Excellent Talents in University of Ministry of Education of China (Grant No. NCET-12-0142).
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  • 图 1  典型的GA流程图及GA在片上光子器件设计领域的应用 (a) 一个典型的GA流程图; (b) 利用GA设计的模式可扩展的交叉波导[70]; (c) 利用GA设计的超紧凑偏振旋转器[71]; (d) 利用GA设计的波长路由器[72]

    Figure 1.  Typical flowchart of GA and its application in on-chip photonic devices design: (a) A typical GA flowchart; (b) mode-extensible crossing waveguide designed by GA[70]; (c) ultra-compact polarization rotator designed by GA[71]; (d) wavelength router designed by GA[72].

    图 2  PSO算法的流程图及PSO算法在光子器件设计领域的应用 (a) PSO算法的流程图; (b) 利用PSO算法设计的片上偏振分束器[74]; (c) 利用PSO算法优化设计的单层超临界透镜的SEM图[75]; (d) 利用PSO算法设计的片上多模式功率分束器[76]

    Figure 2.  Flowchart of PSO algorithm and its application in photonic devices design: (a) Flowchart of PSO algorithm; (b) on-chip polarization beam splitter designed by PSO algorithm[74]; (c) SEM image of single-layer supercritical lens optimized by PSO algorithm[75]; (d) on-chip multi-mode power beam splitter designed by PSO algorithm[76].

    图 3  DBS算法的流程图及DBS算法在光子器件设计领域的应用 (a) DBS算法具体优化流程图; (b) 基于DBS算法设计的偏振分束器的结构图, 以及波长为1550 nm的TE和TM通过该器件时的光场图[79]; (c) 利用改良的DBS算法设计的离散化纳米结构的侧视图[80]; (d) 利用DBS算法设计的双通道波长解复用器及不同波长的光通过该器件时的光场图[81]

    Figure 3.  Flowchart of DBS algorithm and its application in photonic device design: (a) Flowchart of DBS algorithm; (b) structure diagram of the polarization beam splitter designed by DBS algorithm, and the light field diagram of TE and TM with a wavelength of 1550 nm passing through the device[79]; (c) side view of the discretized nanostructures designed by the improved DBS algorithm[80]; (d) dual-channel wavelength demultiplexer designed by DBS algorithm, and the optical field diagram when light of different wavelengths passing through the device[81].

    图 4  AM在光子器件设计领域的应用 (a) 利用AM设计的功率分束器[86]; (b), (c) 基于AM提出的两种非线性光子器件[87]; (d) 使用AM优化的垂直光栅耦合器[88]

    Figure 4.  Application of AM in photonic device design: (a) Power splitter designed by AM[86]; (b), (c) two nonlinear photonic devices designed by AM[87]; (d) vertical grating couplers optimized by AM[88].

    图 5  神经网络在光子器件设计领域的应用 (a) 基于人工神经网络架构设计的布拉格光栅[114]; (b) 利用深度神经网络设计的光栅耦合器[115]; (c) 用来预测超表面中的超原子光响应的PNN架构[116]

    Figure 5.  Application of neural network in photonic device design: (a) Bragg grating based on ANN architecture[114]; (b) grating couplers designed using DNN[115]; (c) PNN architecture for predicting meta-atom light responses in metasurfaces[116].

    图 6  用来解决一些具体技术问题的神经网络架构 (a) “正、逆向串联”神经网络示意图以及利用该网络设计的多层膜系结构 [117]; (b) 基于GA的深度神经网络[118]; (c) 利用少样本数据增强迭代算法优化得到的二维可编程手性超材料[119]; (d) 一种基于全局深度学习的逆设计框架的训练和设计过程[120]

    Figure 6.  Neural network architectures used to solve some specific technical problems: (a) Schematic of the “forward and backward series” neural network and the multilayer structure designed by this network[117]; (b) GA-based DNN[118]; (c) two-dimensional programmable chiral metamaterial optimized by data enhanced iterative few-sample algorithm[119]; (d) training and design process of an inverse design framework based on global deep learning[120].

    图 7  几种由不同方法设计的功率分束器及对比 (a)利用PSO算法设计的波长不敏感的单模功率分束器[124]; (b) 利用传统方法设计的基于S形曲线脊波导的波长不敏感单模功率分束器[125]; (c) 传统方法设计双模功率分束器的原理示意图(左)和基于对称优化的DBS算法设计的双模功率分束器(右) [126]; (d) 利用多种算法分阶段优化设计的超宽波段适用的双模功率分束器[127]; (e) 基于传统方法设计的任意分束比的功率分束器架构示意图[128]; (f) 基于QPSO算法设计的几种不同分束比的功率分束器[129]

    Figure 7.  Several power splitters designed by different methods and their comparison: (a) Wavelength insensitive single-mode power splitter designed by PSO algorithm[124]; (b) wavelength insensitive single-mode power splitter based on S-shaped curved ridge waveguide designed by conventional methods[125]; (c) schematic of dual-mode power splitter designed by conventional method (left) and dual-mode power splitter designed by symmetric-optimize-DBS algorithm (right)[126]; (d) dual-mode power splitter suitable for ultra-wide band optimized by multiple algorithms[127]; (e) schematic of the power splitter with arbitrary split ratio designed by conventional methods[128]; (f) power splitters with different split ratios designed by QPSO algorithm[129].

    图 8  几种由不同方法设计的模式(分解)复用器及对比 (a) 基于DBS算法设计的二阶模式复用器[130]; (b)基于锥形定向耦合器的二阶模式复用器[131]; (c), (d) 两种由DBS算法设计的四阶模式(分解)复用器[132,133]; (e)八阶模式/偏振(分解)复用器的光学显微镜成像图[134]

    Figure 8.  Several mode (de)multiplexers designed by different methods and their comparison: (a) Two-mode multiplexer based on the DBS algorithm[130]; (b) two-mode multiplexer based on conical directional coupler[131]; (c), (d) two kinds of four-mode (de)multiplexers designed by the DBS algorithm[132,133]; (e) optical microscope image of the eight-mode/polarization (de)multiplexers[134].

    图 9  几种由不同方法设计的单、多模弯曲波导及对比 (a) 基于DBS算法设计的单模式90°弯曲波导[133]; (b) 传统方法设计的基于修正欧拉曲线的多模90°弯曲波导[136]; (c) 利用DBS算法设计的双模90°弯曲波导[137]; (d) 基于TO的使用了灰度刻蚀技术的三模90°弯曲波导[138]; (e) 利用DBS算法设计的三模90°弯曲波导[139]; (f) 利用DBS算法设计的三模90°弯曲波导的模拟光场分布示意图

    Figure 9.  Comparison of several single- and multi-mode bending waveguides designed by different methods: (a) Single-mode 90° bending waveguide designed by DBS algorithm[133]; (b) four-mode 90° bending waveguide based on modified Euler curve designed by conventional methods[136]; (c) two-mode 90° bending waveguide designed by DBS algorithm[137]; (d) three-mode 90° bending waveguide based on TO using grayscale etching technology[138]; (e) three-mode 90° bending waveguide designed by the DBS algorithm[139]; (f) schematic of simulated light field distribution of the three-mode 90° bending waveguide in (e).

    图 10  几种利用智能设计方法优化传统光互连器件得到的结果及其对比器件 (a) 利用PSO算法优化反锥形耦合器结构设计出的片上偏振分束器[74]; (b) 完全基于传统耦合模理论设计的偏振分束器[140]; (c) 利用AM优化耦合区域间隙设计的几种用于不同波长条件下的偏振分束器, 以及其中的横向和纵向的模拟电磁场密度分布[141]; (d) 利用带有制造约束的水平集方法设计的功率分束器, 以及其中的模拟电磁场密度分布[142]

    Figure 10.  Several results obtained by using intelligent design methods to optimize conventional optical interconnect devices, and their comparison devices: (a) On-chip polarization beam splitter designed by using the PSO algorithm to optimize the anti-conical coupler[74]; (b) polarization beam splitters designed by conventional methods[140]; (c) several polarization beam splitters designed for different wavelength conditions using the AM to optimize the coupling region gap, and their simulated electromagnetic field density distributions[141]; (d) power splitter designed using a level set method with manufacturing constraints, and the simulated electromagnetic field density distribution in it[142].

    图 11  相变材料的典型相变过程和相变材料在可调控光器件领域的应用 (a) 一个典型的相变过程的示意图; (b)基于相变材料设计的全光神经突触网络; (c) 基于相变材料设计的相变存储器单元; (d) 基于相变材料设计的可调控超表面

    Figure 11.  Typical phase change process of phase change materials and their application in the field of controllable optical devices: (a) Diagram of a typical phase change process; (b) all-optical synaptic networks based on phase change materials; (c) phase-change memory cell based on phasechange material; (d) controllable metasurface based on phase change material.

    图 12  基于传统方法设计的可调控片上光互连器件 (a) 几种可调控方向性耦合开关的光学显微镜图和细节部分的SEM图[150]; (b) 一种高消光比的可调控光开关的结构示意图和调控效果光场图[157]

    Figure 12.  Controllable on-chip optical interconnection devices designed by traditional methods: (a) Optical microscope images of several controllable directional coupling switches and the SEM images of their details[150]; (b) structural and performance of the optical switch with a high ER[157].

    图 13  利用智能设计方法设计的可调控片上光互连器件 (a) 基于DBS算法设计的一种可调控模式转换器[168]; (b) 基于DBS算法设计的可调控三模式纳米光子波导开关[169]; (c) 基于像素化相变材料设计的功率分束比可调的功率分束器[170]; (d) 基于DBS算法设计的任意功率分束比的功率分束器[171]

    Figure 13.  Controllable on-chip optical interconnection devices designed by intelligent methods: (a) Controllable mode converter based on the DBS algorithm[168]; (b) controllable three-mode nanophotonic waveguide switch based on the DBS algorithm[169]; (c) power splitter with arbitrary split ratio based on pixelated phase change material[170]; (d) power splitter with arbitrary split ratio based on the DBS algorithm[171].

    图 14  智能化设计的多用途集成光互连器件 (a) 波长分解复用光栅耦合器的SEM成像图[172]; (b) 波长分解复用光栅耦合器的工作原理; (c) 模式转换偏振分束器的SEM成像图[79]; (d)不同偏振态的光输入模式转换偏振分束器后该器件横截面中的模拟电磁场密度分布[79]

    Figure 14.  Multi-purpose integrated optical interconnection devices designed by intelligent methods: (a) SEM image of the wavelength demultiplexing grating coupler[172]; (b) working principle of the wavelength demultiplexing grating coupler; (c) SEM image of the mode-switching polarization beam splitter[79]; (d) the density distribution of the simulated electromagnetic field in the device[79].

    图 15  智能化设计的模块化集成光互连器件 (a) 模块化集成的可调谐模式产生器[173]; (b) 模块化集成的偏振转换器[174]; (c) 由光子晶体光栅和聚焦波长解复用器直接相连得到的模块化集成光互连器件[176]; (d) 模块化集成的偏振分束转换器, 由双层结构的偏振转换器和模式分解复用器直接相连而成[177]

    Figure 15.  Modular integrated optical interconnect devices designed by intelligent methods: (a) Modular integrated tunable mode generator[173]; (b) modular integrated polarization converters[174]; (c) modular integrated focusing wavelength demultiplexer[176]; (d) modular integrated polarization beam-splitting converter[177].

    图 16  智能化设计的多层光互连系统 (a) 基于氮化硅波导的层间垂直耦合器[181]; (b) 利用GA设计的层间光栅耦合器[182]; (c) 基于硅波导的层间反射镜[183]; (d) 采用智能设计方法设计的硅层间光学通道[184]

    Figure 16.  Multi-layer optical interconnection systems designed by intelligent methods: (a) Interlayer vertical coupler based on silicon nitride waveguide[181]; (b) interlayer grating coupler designed by the GA[182]; (c) interlayer reflectors based on silicon waveguides[183]; (d) silicon interlayer optical channel designed by intelligent method[184].

    表 1  相同功能的智能化设计和传统方法设计的功率分束器的尺寸对比

    Table 1.  Size comparison of power beam splitters designed by intelligent and conventional design methods with the same function.

    功率分束器类型智能化设计结果
    最大长度/μm
    传统设计结果
    最大长度/μm
    波长不敏感单模2>25
    双模2.88/5.4>200
    任意分束比1.5>45
    DownLoad: CSV

    表 2  相同(似)功能的智能化设计和传统方法设计的模式(分解)复用器的尺寸对比

    Table 2.  Size comparison of mode (de)multiplexers designed by intelligent and traditional design methods with the same (like) function.

    模式(分解)复用器类型智能化设计结果
    最大长度/μm
    传统设计结果
    最大长度
    二阶3十微米量级
    四阶/八阶(含偏振态)6/4.8百微米量级
    DownLoad: CSV

    表 3  相同(似)功能的智能化设计和传统方法设计的90°弯曲波导的尺寸对比

    Table 3.  Size comparison of bendings designed by intelligent and traditional design methods with the same (like) function.

    弯曲波导类型智能化设计结果
    转弯半径/μm
    传统设计结果
    转弯半径/μm
    三模2.7578.8
    其他多模<3.6(双模)45(4种TM模式)
    DownLoad: CSV
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Metrics
  • Abstract views:  4794
  • PDF Downloads:  188
  • Cited By: 0
Publishing process
  • Received Date:  30 April 2023
  • Accepted Date:  01 August 2023
  • Available Online:  19 August 2023
  • Published Online:  20 September 2023

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