• 文献标题:   Bloch theory-based gradient recovery method for computing topological edge modes in photonic graphene
  • 文献类型:   Article
  • 作  者:   GUO HL, YANG X, ZHU Y
  • 作者关键词:   gradient recovery, superconvergence, edge mode, honeycomb structure, topological photonic
  • 出版物名称:   JOURNAL OF COMPUTATIONAL PHYSICS
  • ISSN:   0021-9991 EI 1090-2716
  • 通讯作者地址:   Tsinghua Univ
  • 被引频次:   3
  • DOI:   10.1016/j.jcp.2018.12.001
  • 出版年:   2019

▎ 摘  要

Photonic graphene, a photonic crystal with honeycomb structures, has been intensively studied in both theoretical and applied fields. Similar to graphene which admits Dirac Fermions and topological edge states, photonic graphene supports novel and subtle propagating modes (edge modes) of electromagnetic waves. These modes have wide applications in many optical systems. In this paper, we propose a novel gradient recovery method based on Bloch theory for the computation of topological edge modes in photonic graphene. Compared to standard finite element methods, this method provides higher order accuracy with the help of gradient recovery technique. This high order accuracy is desired for constructing the propagating electromagnetic modes in applications. We analyze the accuracy and prove the superconvergence of this method. Numerical examples are presented to show the efficiency by computing the edge mode for the P-symmetry and C-symmetry breaking cases in honeycomb structures. (C) 2018 Elsevier Inc. All rights reserved.