Event Details
Whispering-Gallery-Mode Simulation Using Recurrent Neural Network
Presenter: Haobin Luo
Supervisor:
Date: Tue, November 26, 2024
Time: 11:00:00 - 00:00:00
Place: Remote Via Zoom
ABSTRACT
Abstract:
This project outlines whispering gallery mode (WGM) microcavity simulation using recurrent neural networks (RNNs). Firstly, the perturbed WGM mode field distributions are predicted with RNN. Secondly, overlap integrals of WGM fields at two consecutive cavity cross-sections are also predicted using RNN. Compared to traditional numerical simulation methods, which are typically resource-intensive and time-consuming, this RNN approach significantly reduces both computational power and processing time. This RNN framework is ready to be integrated to the cylindrical mode match method to simulate wave propagating in microcavities at high efficiency.
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