Inverse design of topological valley-locked slow light rainbow trapper based on physics-aware latent diffusion model

Valley photonic crystals (VPCs), leveraging topologically protected edge states, provide robust mechanisms for light wave manipulation and propagation. The design of VPCs primarily relies on the configuration and arrangement of the unit cell structures. In conventional structural design, the trial-and-error approach relying on prior structural templates and full-wave simulations leads to significant inefficiencies. In recent years, various inverse design algorithms have been widely adopted for structural generation. However, these methods often fail to meet the demands of multi-objective structural generation under limited physical constraints. We propose a physics-aware latent diffusion model (PALDM). This generative framework enables efficient generation of VPC unit cell structures by embedding physics-aware constraints into the latent diffusion process. Using PALDM, we designed ten different unit cell structures with parametric gradient variations. The topological slow light waveguide composed of these structures achieved slow light rainbow trapping in the topological bandgap, validating the capability of PALDM to generate VPCs with tailored frequency response. The physics-aware approach thus offers a pathway for advanced topological photonic device design.

Authors

Institutions

Publication Details

Journal
Optics Express
Published
2025-08-25
DOI
https://doi.org/10.1364/oe.573199
Primary Topic
Orbital Angular Momentum in Optics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Inverse design of topological valley-locked slow light rainbow trapper based on physics-aware latent diffusion model

Yan Ren, Hangzhao Liu, Hai Lin, Rui Zhou et al.
Optics Express
Orbital Angular Momentum in Optics
article

Inverse design of topological valley-locked slow light rainbow trapper based on physics-aware latent diffusion model

Yan Ren, Hangzhao Liu, Hai Lin, Rui Zhou, Yanwen Wu, Ying Zhang
article en

Abstract

Valley photonic crystals (VPCs), leveraging topologically protected edge states, provide robust mechanisms for light wave manipulation and propagation. The design of VPCs primarily relies on the configuration and arrangement of the unit cell structures. In conventional structural design, the trial-and-error approach relying on prior structural templates and full-wave simulations leads to significant inefficiencies. In recent years, various inverse design algorithms have been widely adopted for structural generation. However, these methods often fail to meet the demands of multi-objective structural generation under limited physical constraints. We propose a physics-aware latent diffusion model (PALDM). This generative framework enables efficient generation of VPC unit cell structures by embedding physics-aware constraints into the latent diffusion process. Using PALDM, we designed ten different unit cell structures with parametric gradient variations. The topological slow light waveguide composed of these structures achieved slow light rainbow trapping in the topological bandgap, validating the capability of PALDM to generate VPCs with tailored frequency response. The physics-aware approach thus offers a pathway for advanced topological photonic device design.

Optics ExpressVol. 33(18)
Central China Normal University (CN), Instituto de Ciencia de Materiales de Madrid (ES)
Sustainable cities and communities
Openalex Percentile: Top 83%
Orbital Angular Momentum in Optics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.