Multi-resonant silicon nanoantennas by evolutionary multi-objective optimization

被引:3
|
作者
Wiecha, Peter R. [1 ]
Arbouet, Arnaud [1 ]
Girard, Christian [1 ]
Lecestre, Aurelie [2 ]
Larrieu, Guilhem [2 ]
Paillard, Vincent [1 ]
机构
[1] Univ Toulouse, CNRS, CEMES, Toulouse, France
[2] Univ Toulouse, CNRS, LAAS, INP, Toulouse, France
来源
COMPUTATIONAL OPTICS II | 2018年 / 10694卷
关键词
PLASMONIC NANOANTENNAS; INVERSE DESIGN; 2ND-HARMONIC GENERATION; DIELECTRIC NANOANTENNAS; SCATTERING PROPERTIES; OPTICAL ANTENNAS; COLOR; NANOSTRUCTURES; METASURFACES; RADIATION;
D O I
10.1117/12.2315123
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Photonic nanostructures have attracted a tremendous amount of attention in the recent past. Via their size, shape and material it is possible to engineer their optical response to user-defined needs. Tailoring of the optical response is usually based on a reference geometry for which subsequent variations to the initial design are applied. Such approach, however, might fail if optimum nanostructures for complex optical responses are searched. As example we can mention the case of complex structures with several simultaneous optical resonances. We propose an approach to tackle the problem in the inverse way: In a first step we define the desired optical response as function of the nanostructure geometry. This response is numerically evaluated using the Green Dyadic Method for fully retarded electro-dynamical simulations. Eventually, we optimize multiple of such objective functions concurrently, using an evolutionary multi-objective optimization algorithm, which is coupled to the electro-dynamical simulations code. A great advantage of this optimization technique is, that it allows the implicit and automatic consideration of technological limitations like the electron beam lithography resolution. Explicitly, we optimize silicon nanostructures such that they provide two user-defined resonance wavelengths, which can be individually addressed by crossed incident polarizations.
引用
收藏
页数:7
相关论文
共 50 条
  • [1] Evolutionary Multi-Objective Optimization for Multi-Resonant Photonic Nanostructures
    Wiecha, Peter R.
    Arbouet, Arnaud
    Girard, Christian
    Lecestre, Aurelie
    Larrieu, Guilhem
    Paillard, Vincent
    2016 IEEE NANOTECHNOLOGY MATERIALS AND DEVICES CONFERENCE (NMDC), 2016,
  • [2] Evolutionary multi-objective optimization of colour pixels based on dielectric nanoantennas
    Wiecha P.R.
    Arbouet A.
    Girard C.
    Lecestre A.
    Larrieu G.
    Paillard V.
    Wiecha, Peter R. (peter.wiecha@cemes.fr), 1600, Nature Publishing Group (12): : 163 - 169
  • [3] Evolutionary multi-objective optimization of colour pixels based on dielectric nanoantennas
    Wiecha, Peter R.
    Arbouet, Arnaud
    Girard, Christian
    Lecestre, Aurelie
    Larrieu, Guilhem
    Paillard, Vincent
    NATURE NANOTECHNOLOGY, 2017, 12 (02) : 163 - 169
  • [4] Evolutionary Multi-Objective Optimization
    Deb, Kalyanmoy
    GECCO-2010 COMPANION PUBLICATION: PROCEEDINGS OF THE 12TH ANNUAL GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, 2010, : 2577 - 2602
  • [5] Evolutionary multi-objective optimization
    Coello Coello, Carlos A.
    Hernandez Aguirre, Arturo
    Zitzler, Eckart
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 181 (03) : 1617 - 1619
  • [6] Hyper multi-objective evolutionary algorithm for multi-objective optimization problems
    Guo, Weian
    Chen, Ming
    Wang, Lei
    Wu, Qidi
    SOFT COMPUTING, 2017, 21 (20) : 5883 - 5891
  • [7] Multi-Objective Factored Evolutionary Optimization and the Multi-Objective Knapsack Problem
    Peerlinck, Amy
    Sheppard, John
    2022 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2022,
  • [8] Hyper multi-objective evolutionary algorithm for multi-objective optimization problems
    Weian Guo
    Ming Chen
    Lei Wang
    Qidi Wu
    Soft Computing, 2017, 21 : 5883 - 5891
  • [9] Evolutionary Multi-objective Diversity Optimization
    Anh Viet Do
    Guo, Mingyu
    Neumann, Aneta
    Neumann, Frank
    PARALLEL PROBLEM SOLVING FROM NATURE-PPSN XVIII, PT IV, PPSN 2024, 2024, 15151 : 117 - 134
  • [10] Evolutionary multi-objective optimization and visualization
    Obayashi, S
    New Developments in Computational Fluid Dynamics, 2005, 90 : 175 - 185