Predicting Molecular Properties Using Photonic Chip-Based Machine Learning Approach
- Resource Type
- Conference
- Authors
- Lau, J.; Zhang, H.; Wan, L.; Shi, L.; Lee, C. -K.; Kwek, L. C.; Liu, A. Q.
- Source
- 2022 Conference on Lasers and Electro-Optics (CLEO) Lasers and Electro-Optics (CLEO), 2022 Conference on. :1-2 May, 2022
- Subject
- Photonics and Electrooptics
Neural network hardware
Integrated optics
Quantum mechanics
Optical computing
Machine learning
Mechanical factors
Pattern recognition
(130.3120) Integrated optics devices
(100.4996) Pattern recognition
neural networks
(000.1570) Chemistry
- Language
The intensive neural network architecture for molecules resulted in exponential growth in computation cost. Photonic chip technology offers an alternative platform with faster processing. We apply an optical neural chip to predict multiple quantum mechanical properties of molecules.