@inproceedings{5a58c06e099848c1a98321b7868c59cc,
title = "New Perspectives on Observing Newton's Rings",
abstract = "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.",
keywords = "Newton's Rings, artificial intelligence, course design, data analysis, signal processing",
author = "Lu, {Ming Feng} and Wu, {Jin Min} and Wenming Yang and Feng Zhang and Jihao Luo and Ran Tao",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023 ; Conference date: 18-10-2023 Through 21-10-2023",
year = "2023",
doi = "10.1109/FIE58773.2023.10343510",
language = "English",
series = "Proceedings - Frontiers in Education Conference, FIE",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 IEEE Frontiers in Education Conference, FIE 2023 - Proceedings",
address = "United States",
}