Quantization of topological edge mode in a one-dimensional photonic crystal heterostructure

被引:0
|
作者
Singh, Ankit [1 ,2 ]
Tiwari, Akhilesh [2 ,3 ]
Shahrukh, N. I. S. H. A. N. T.
Kumar, Nishant [2 ,3 ]
Kumar, Pramod [2 ,3 ]
机构
[1] CNR, Inst Appl Sci & Intelligent Syst, I-80078 Naples, Italy
[2] Indian Inst Informat Technol Allahabad, Dept Appl Sci, Modeling & Simulat Lab, Prayagraj 211015, India
[3] Indian Inst Informat Technol Allahabad, Dept Appl Sci, Spintron & Meta Mat Lab, Prayagraj 211015, India
关键词
ZAK PHASE; BAND;
D O I
10.1364/JOSAB.535052
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
The study of topological phases of matter has seen significant advancements in recent years, largely driven by the discovery and exploration of their distinctive topological edge states. Here, we delve into the edge properties of a one-dimensional periodic multilayer structure. The analysis reveals that this system exhibits characteristics akin to the Su-Schrieffer-Heeger model in optics. The theoretical analysis explores the impact of multiple interfaces on the emergence of a topological edge mode (TEM) within the structure. The proposed heterostructure functions as a general beam splitter. Moreover, when the interface is doubled, the heterostructure exhibits two TEM states, resulting from the quantization of an incoming beam into its two equally orthogonal constituents. As the number of interfaces increases, more quantized TEM states occur within the photonic bandgap. Also, it identifies that the quality factor of the original TEM mode at 382.08 THz frequency linearly increases with respect to the number of interfaces. The outcome suggests potential applications in photonic sensors, optoelectronics, and photonic devices, indicating the heterostructure's pivotal role in advancing these fields. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.
引用
收藏
页码:2373 / 2380
页数:8
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