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Photonics
Special Issues
Recent Trends in Computational Photonics
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Recent Trends in Computational Photonics

A special issue of Photonics (ISSN 2304-6732).

Deadline for manuscript submissions: closed (20 December 2023) | Viewed by 7560

Special Issue Editors

Dr. Yuntian Chen

E-Mail Website
Guest Editor
School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: computational photonics
Prof. Dr. Wei E. I. Sha

E-Mail Website
Guest Editor
College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310058, China
Interests: computational and applied electromagnetics; nonlinear and quantum electromagnetics; nanophotonics and nanoplasmonics; optoelectronic device simulation; multiphysics analysis and modeling

Special Issue Information

Dear Colleagues,

Computational photonics plays an indispensable role in the study of fundamental optics, and in applied branches such as photonic device design, development, and optimization. This Special Issue aims to advance, enhance, and broaden the combination of algorithms and techniques in computational photonics in the context of the rapid development of optoelectronics technology and industry.

Essentially, computational photonics is used to solve Maxwell’s equations, or the equivalent form of one or the other. At different length scales, that is, the ratio between optical wavelength and the size/feature-size scattering object, Maxwell’s equations can be approximated to different levels of simplicity, and light scattering behavior can be dramatically different. At only one scale, modeling Maxwell’s equations under the influence of complex geometries/materials is already a challenging task; thus, it tends to be more challenging to model Maxwell’s equations at multiple scales. The current Special Issue covers all aspects of computational photonics, with particular emphasis on the multi-scale modelling and optimization of photonic devices. Topics include, but are not limited to:

  • Multi-scale modeling of photonic devices;
  • Finite element algorithm in photonic modeling;
  • FDTD/FEFD algorithm in photonic modeling;
  • Optimization algorithm in photonics;
  • Eigen-mode expansion algorithm in photonic modeling;
  • Fourier modal algorithm in photonic modeling;
  • Domain decomposition algorithm in photonic modeling;
  • Field/ray-tracing algorithm in photonic modeling;
  • Computational adaptive optics;
  • Computational imaging/displays;
  • Computational inverse scattering.

Dr. Yuntian Chen
Dr. Wei E. I. Sha
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Photonics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (5 papers)

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Research

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13 pages, 3381 KiB  
Article
Rotational Bloch Boundary Conditions and the Finite-Element Implementation in Photonic Devices
by Zhanwen Wang, Jingwei Wang, Lida Liu and Yuntian Chen
Photonics 2023, 10(6), 691; https://doi.org/10.3390/photonics10060691 - 16 Jun 2023
Cited by 1 | Viewed by 924
Abstract
This article described the implementation of rotational Bloch boundary conditions in photonic devices using the finite element method (FEM). For the electromagnetic analysis of periodic structures, FEM and Bloch boundary conditions are now widely used. The vast majority of recent research, however, focused [...] Read more.
This article described the implementation of rotational Bloch boundary conditions in photonic devices using the finite element method (FEM). For the electromagnetic analysis of periodic structures, FEM and Bloch boundary conditions are now widely used. The vast majority of recent research, however, focused on applying Bloch boundary conditions to periodic optical systems with translational symmetry. Our research focused on a flexible numerical method that may be applied to the mode analysis of any photonic device with discrete rotational symmetry. By including the Bloch rotational boundary conditions into FEM, we were able to limit the computational domain to the original one periodic unit, thus enhancing computational speed and decreasing memory consumption. When combined with the finite-element method, rotational Bloch boundary conditions will give a potent tool for the mode analysis of photonic devices with complicated structures and rotational symmetry. In the meantime, the degenerated modes we calculated were consistent with group theory. Overall, this study expands the numerical tools of studying rotational photonic devices, and has useful applications in the study and design of optical fibers, sensors, and other photonic devices. Full article
(This article belongs to the Special Issue Recent Trends in Computational Photonics)
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12 pages, 2773 KiB  
Communication
Investigation of Giant Nonlinearity in a Plasmonic Metasurface with Epsilon-Near-Zero Film
by Chenran Liu, Ke Xu, Jian Feng and Ming Fang
Photonics 2023, 10(5), 592; https://doi.org/10.3390/photonics10050592 - 19 May 2023
Viewed by 1134
Abstract
Plasmonic metamaterials can exhibit a variety of physical optical properties that offer extraordinary nonlinear conversion efficiency for ultra-compact nanodevice applications. Furthermore, the optical-rectification effect from the plasmonic nonlinear metasurfaces (NLMSs) can be used as a compact source of deep-subwavelength thickness to radiate broadband [...] Read more.
Plasmonic metamaterials can exhibit a variety of physical optical properties that offer extraordinary nonlinear conversion efficiency for ultra-compact nanodevice applications. Furthermore, the optical-rectification effect from the plasmonic nonlinear metasurfaces (NLMSs) can be used as a compact source of deep-subwavelength thickness to radiate broadband terahertz (THz) signals. Meanwhile, a novel dual-mode metasurface consisting of a split-ring resonator (SRR) array and an epsilon-near-zero (ENZ) layer was presented to boost the THz conversion efficiency further. In this paper, to explore the mechanism of THz generation from plasmonic NLMSs, the Maxwell-hydrodynamic multiphysics model is adopted to investigate complex linear and intrinsic nonlinear dynamics in plasmonics. We solve the multiphysics model using the finite-difference time-domain (FDTD) method, and the numerical results demonstrate the physical mechanism of the THz generation processes which cannot be observed in our previous experiments directly. The proposed method reveals a new approach for developing new types of high-conversion-efficiency nonlinear nanodevices. Full article
(This article belongs to the Special Issue Recent Trends in Computational Photonics)
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11 pages, 3555 KiB  
Communication
Parallelized and Cascadable Optical Logic Operations by Few-Layer Diffractive Optical Neural Network
by Xianjin Liu, Dasen Zhang, Licheng Wang, Ting Ma, Zhenzhen Liu and Jun-Jun Xiao
Photonics 2023, 10(5), 503; https://doi.org/10.3390/photonics10050503 - 26 Apr 2023
Cited by 2 | Viewed by 1333
Abstract
Optical computing has gained much attention due to its high speed, low energy consumption, and the fact that it is naturally parallelizable and multiplexable, etc. Single-bit optical logic gates based on a four-hidden-layer diffractive optical neural network (DONN) have been demonstrated with paired [...] Read more.
Optical computing has gained much attention due to its high speed, low energy consumption, and the fact that it is naturally parallelizable and multiplexable, etc. Single-bit optical logic gates based on a four-hidden-layer diffractive optical neural network (DONN) have been demonstrated with paired apertures. Here, we show a parallel-logic operation strategy based on two-hidden-layer DONN, showcasing their efficiency by multiple-bit (up to 16-bit) optical logic (e.g., NAND) operations. In addition, we demonstrate how NAND-DONN units can be utilized to achieve NOR and AND operations by flipping and cascading the DONN. Full article
(This article belongs to the Special Issue Recent Trends in Computational Photonics)
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Review

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22 pages, 10357 KiB  
Review
Deep Learning and Adjoint Method Accelerated Inverse Design in Photonics: A Review
by Zongyong Pan and Xiaomin Pan
Photonics 2023, 10(7), 852; https://doi.org/10.3390/photonics10070852 - 23 Jul 2023
Cited by 3 | Viewed by 2245
Abstract
For photonic applications, the inverse design method plays a critical role in the optimized design of photonic devices. According to its two ingredients, inverse design in photonics can be improved from two aspects: to find solutions to Maxwell’s equations more efficiently and to [...] Read more.
For photonic applications, the inverse design method plays a critical role in the optimized design of photonic devices. According to its two ingredients, inverse design in photonics can be improved from two aspects: to find solutions to Maxwell’s equations more efficiently and to employ a more suitable optimization scheme. Various optimization algorithms have been employed to handle the optimization: the adjoint method (AM) has become the one of the most widely utilized ones because of its low computational cost. With the rapid development of deep learning (DL) in recent years, inverse design has also benefited from DL algorithms, leading to a new pattern of photon inverse design. Unlike the AM, DL can be an efficient solver of Maxwell’s equations, as well as a nice optimizer, or even both, in inverse design. In this review, we discuss the development of the AM and DL algorithms in inverse design, and the advancements, advantages, and disadvantages of the AM and DL algorithms in photon inverse design. Full article
(This article belongs to the Special Issue Recent Trends in Computational Photonics)
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19 pages, 3652 KiB  
Review
Advanced Numerical Methods for Graphene Simulation with Equivalent Boundary Conditions: A Review
by Yansheng Gong and Na Liu
Photonics 2023, 10(7), 712; https://doi.org/10.3390/photonics10070712 - 22 Jun 2023
Cited by 1 | Viewed by 1016
Abstract
Since the discovery of graphene, due to its excellent optical, thermal, mechanical and electrical properties, it has a broad application prospect in energy, materials, biomedicine, electromagnetism and other fields. A great quantity of researches on the physical mechanism of graphene has been applied [...] Read more.
Since the discovery of graphene, due to its excellent optical, thermal, mechanical and electrical properties, it has a broad application prospect in energy, materials, biomedicine, electromagnetism and other fields. A great quantity of researches on the physical mechanism of graphene has been applied to engineering in electromagnetism and optics. To study the properties of graphene, different kinds of numerical methods such as the mixed finite element method (Mixed FEM), the mixed spectral element method (Mixed SEM), Method of Auxiliary Sources (MAS), discontinuous Galerkin time-domain method (DGTD) and interior penalty discontinuous Galerkin time domain (IPDG) have been developed for simulating the electromagnetic field effects of graphene and equivalent boundary conditions such as impedance transmission boundary condition (ITBC), surface current boundary condition (SCBC), impedance matrix boundary condition (IMBC) and surface impedance boundary condition (SIBC) have been employed to replace graphene in the computational domain. In this work, the numerical methods with equivalent boundary conditions are reviewed, and some examples are provided to illustrate their applicability. Full article
(This article belongs to the Special Issue Recent Trends in Computational Photonics)
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