Predictive modelling of optical beams from grating structure using deep neural network

Predictive modelling of optical beams from grating structure using deep neural network

Integrated grating structure has been widely used in the optical addressing of trapped ion qubits in quantum computing. For accurate optical addressing, the optical properties of light beam coupled out from the grating should be thoroughly understood. In this study, deep neural network (DNN) modelin...

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Bibliographic Details
Main Authors: Lim, Yu Dian, Zhao, Peng, Guidoni, Luca, Likforman, Jean-Pierre, Tan, Chuan Seng
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2023
Subjects:
Engineering::Electrical and electronic engineering::Electronic packaging
Beam Steering
Silicon Photonics
Online Access:https://hdl.handle.net/10356/170738
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Institution: Nanyang Technological University
Language: English
Description
Summary:Integrated grating structure has been widely used in the optical addressing of trapped ion qubits in quantum computing. For accurate optical addressing, the optical properties of light beam coupled out from the grating should be thoroughly understood. In this study, deep neural network (DNN) modeling is used to predict the optical properties of light from silicon nitride (SiN) grating. DNN models with various number of layers (L) and nodes per layer (N) are attempted and optimized. Both overfitted and well-fitted L/N combinations are addressed. The APE values of the overfitted DNNs can reach as low as 5.2%, while the APE values of the well-fitted DNN reaches as low as 7.2%.

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