Qi Xin, Hai Huang, Chenyu Li, Kewei Shi, Zhaoyu Zhang
{"title":"POST:用于自动、高效预测PCSEL的光子旋流变压器","authors":"Qi Xin, Hai Huang, Chenyu Li, Kewei Shi, Zhaoyu Zhang","doi":"10.1515/nanoph-2025-0317","DOIUrl":null,"url":null,"abstract":"This work designs a model named POST based on the vision transformer (ViT) approach. Across single, double, and even triple lattices, as well as various non-circular complex hole structures, POST enables prediction of multiple optical properties of photonic crystal layers in photonic crystal surface emitting lasers (PCSELs) with high speed and accuracy, without requiring manual intervention, which serves as a comprehensive surrogate for the optical field simulation. In the predictions of quality factor (<jats:italic>Q</jats:italic>) and surface-emitting efficiency (SE) for PCSEL, the R-squared values reach 0.909 and 0.779, respectively. Additionally, it achieves nearly 5,000 predictions per second, significantly lowering simulation costs. The precision and speed of POST predictions lay a solid foundation for future ultra-complex model parameter tuning involving dozens of parameters. It can also swiftly meet designers’ ad-hoc requirements for evaluating photonic crystal properties. The database used for training the POST model is derived from predictions of different photonic crystal structures using the coupled-wave theory (CWT) model. This dataset will be made publicly available to foster interdisciplinary research advancements in materials science and computer science.","PeriodicalId":19027,"journal":{"name":"Nanophotonics","volume":"105 1","pages":""},"PeriodicalIF":6.6000,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"POST: photonic swin transformer for automated and efficient prediction of PCSEL\",\"authors\":\"Qi Xin, Hai Huang, Chenyu Li, Kewei Shi, Zhaoyu Zhang\",\"doi\":\"10.1515/nanoph-2025-0317\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work designs a model named POST based on the vision transformer (ViT) approach. Across single, double, and even triple lattices, as well as various non-circular complex hole structures, POST enables prediction of multiple optical properties of photonic crystal layers in photonic crystal surface emitting lasers (PCSELs) with high speed and accuracy, without requiring manual intervention, which serves as a comprehensive surrogate for the optical field simulation. In the predictions of quality factor (<jats:italic>Q</jats:italic>) and surface-emitting efficiency (SE) for PCSEL, the R-squared values reach 0.909 and 0.779, respectively. Additionally, it achieves nearly 5,000 predictions per second, significantly lowering simulation costs. The precision and speed of POST predictions lay a solid foundation for future ultra-complex model parameter tuning involving dozens of parameters. It can also swiftly meet designers’ ad-hoc requirements for evaluating photonic crystal properties. The database used for training the POST model is derived from predictions of different photonic crystal structures using the coupled-wave theory (CWT) model. This dataset will be made publicly available to foster interdisciplinary research advancements in materials science and computer science.\",\"PeriodicalId\":19027,\"journal\":{\"name\":\"Nanophotonics\",\"volume\":\"105 1\",\"pages\":\"\"},\"PeriodicalIF\":6.6000,\"publicationDate\":\"2025-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nanophotonics\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://doi.org/10.1515/nanoph-2025-0317\",\"RegionNum\":2,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nanophotonics","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1515/nanoph-2025-0317","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
POST: photonic swin transformer for automated and efficient prediction of PCSEL
This work designs a model named POST based on the vision transformer (ViT) approach. Across single, double, and even triple lattices, as well as various non-circular complex hole structures, POST enables prediction of multiple optical properties of photonic crystal layers in photonic crystal surface emitting lasers (PCSELs) with high speed and accuracy, without requiring manual intervention, which serves as a comprehensive surrogate for the optical field simulation. In the predictions of quality factor (Q) and surface-emitting efficiency (SE) for PCSEL, the R-squared values reach 0.909 and 0.779, respectively. Additionally, it achieves nearly 5,000 predictions per second, significantly lowering simulation costs. The precision and speed of POST predictions lay a solid foundation for future ultra-complex model parameter tuning involving dozens of parameters. It can also swiftly meet designers’ ad-hoc requirements for evaluating photonic crystal properties. The database used for training the POST model is derived from predictions of different photonic crystal structures using the coupled-wave theory (CWT) model. This dataset will be made publicly available to foster interdisciplinary research advancements in materials science and computer science.
期刊介绍:
Nanophotonics, published in collaboration with Sciencewise, is a prestigious journal that showcases recent international research results, notable advancements in the field, and innovative applications. It is regarded as one of the leading publications in the realm of nanophotonics and encompasses a range of article types including research articles, selectively invited reviews, letters, and perspectives.
The journal specifically delves into the study of photon interaction with nano-structures, such as carbon nano-tubes, nano metal particles, nano crystals, semiconductor nano dots, photonic crystals, tissue, and DNA. It offers comprehensive coverage of the most up-to-date discoveries, making it an essential resource for physicists, engineers, and material scientists.