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28 June 2023 Teaching optics with LightFlow: an intuitive framework for light propagation simulations
M. Hossein Eybposh, Changjia Cai, Vincent R. Curtis, Nicolas C. Pegard
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Proceedings Volume 12723, Seventeenth Conference on Education and Training in Optics and Photonics: ETOP 2023; 1272325 (2023) https://doi.org/10.1117/12.2672562
Event: Seventeenth Conference on Education and Training in Optics and Photonics: ETOP 2023, 2023, Cocoa Beach, Florida, United States
Abstract
We introduce LightFlow, an open-source software package for simulating light wave propagation through custom optical components and systems. Built upon TensorFlow and Keras, it benefits from GPU acceleration and offers a user-friendly and modular architecture. Optical components are represented as layers, simplifying the design and modification of simulation models. Our approach also streamlines the addition of new custom components. LightFlow’s automatic gradient calculation is valuable for computational imaging applications involving optimization algorithms and inverse problems. With its intuitive interface, tested building blocks, and expandable design, LightFlow is well-suited for education and research, from undergraduate to advanced graduate levels. The GPU-accelerated processing enables efficient, real-time visualization of optical simulations, making LightFlow valuable across a broad range of user expertise and applications.
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M. Hossein Eybposh, Changjia Cai, Vincent R. Curtis, and Nicolas C. Pegard "Teaching optics with LightFlow: an intuitive framework for light propagation simulations", Proc. SPIE 12723, Seventeenth Conference on Education and Training in Optics and Photonics: ETOP 2023, 1272325 (28 June 2023); https://doi.org/10.1117/12.2672562
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KEYWORDS
Machine learning
Simulations
Design and modelling
Light wave propagation
Open source software
Optical components
Optics education
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