New Perspectives on Observing Newton's Rings

• Main Authors: Lu, Ming-Feng, Wu, Jin-Min, Yang, Wenming, Zhang, Feng, Luo, Jihao, Tao, Ran
• Format: Conference Proceeding
• Language: English
• Subjects: Artificial intelligence; course design; Data analysis; Education; Fourier transforms; Interference; Newton's Rings; Optical variables measurement; Signal processing
• ISSN: 2377-634X
• DOI: 10.1109/FIE58773.2023.10343510

Newton's rings experiment is a fundamental experiment. The rings counting method has been used to reveal the phenomenon of equal-thickness interference in physics for over 100 years. This paper proposes two perspectives on observing Newton's rings. From the perspective of signal processing, fractional Fourier transform are introduced into the Newton's rings experiment to reveal the mathematical nature of the fringe. From the perspective of data analysis, the deep neural network is trained so that it can intelligently analyze Newton's rings. High precision measurement of physical parameters such as the radius of curvature of a lens can be completed directly without counting rings. These two new perspectives provide good extensions to university physics experiments, which can be followed by additional theoretical and experimental sessions to further understand Newton's rings. The new session can be added to the current physics, signal processing and artificial intelligence courses. A brand-new course is designed to help students understand recent Newton's rings processing methods and know the pros and cons of them. which broaden their horizons and stimulate their creative thinking.