Acta Photonica Sinica, Volume. 52, Issue 9, 0923003(2023)
Design Photonic Crystal All-optical Logic Gates Using Machine Learning
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Fig. 2. Forward performance characterization and inverse structure prediction model of photonic crystal waveguide
Fig. 3. Mean squared error of the forward and inverse network verification sets
Fig. 4. The relationship between the predicted value of the neural network model and the actual value
Table 1. AND logic gate truth table
View tableView in ArticleTable 1. AND logic gate truth table
Input port-A Input port-B Output port-C Output power 0 0 0 0 1 0 0 0.09Pin 0 1 0 0.08Pin 1 1 1 0.79Pin
Table 2. NOT logic gate truth table
View tableView in ArticleTable 2. NOT logic gate truth table
Input port-A Port-B（Activate port） Output port-C Output power 1 1 0 0.17Pin 0 1 1 0.72Pin
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Jianwei CHEN, Ran HAO, Chunlian ZHAN, Shangzhong JIN, Pengju ZHANG, Xingang ZHUANG, Feng FEI. Design Photonic Crystal All-optical Logic Gates Using Machine Learning[J]. Acta Photonica Sinica, 2023, 52(9): 0923003
Paper Information
Category: Optical Device
Received: Apr. 4, 2023
Accepted: Apr. 28, 2023
Published Online: Oct. 24, 2023
The Author Email: HAO Ran (ran.hao@cjlu.edu.cn)
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