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28 September 2023 Faster and more accurate geometrical-optics optical force calculation using neural networks
Agnese Callegari, David Bronte Ciriza, Alessandro Magazzù, Gunther Barbosa, Antonio A. R. Neves, Maria Antonia Iatì, Giovanni Volpe, Onofrio M. Maragò
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Proceedings Volume PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023; PC126550C (2023) https://doi.org/10.1117/12.2677267
Event: SPIE Nanoscience + Engineering, 2023, San Diego, California, United States
Abstract
Optical forces are often calculated by using geometrical optics to compute the exchange of momentum between particle and light beam. In geometrical optics, the light beam is represented by a certain number of rays. This sets a trade-off between calculation speed and accuracy. Here, we show that using neural networks allows overcoming this limitation, obtaining not only faster but also more accurate simulations. Then, we exploit our neural networks method to study the dynamics of ellipsoidal particles in a double trap, a system that would be computationally impossible otherwise.
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Agnese Callegari, David Bronte Ciriza, Alessandro Magazzù, Gunther Barbosa, Antonio A. R. Neves, Maria Antonia Iatì, Giovanni Volpe, and Onofrio M. Maragò "Faster and more accurate geometrical-optics optical force calculation using neural networks", Proc. SPIE PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023, PC126550C (28 September 2023); https://doi.org/10.1117/12.2677267
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KEYWORDS
Particles
Geometrical optics
Neural networks
Modeling
Optical tweezers
Laser scattering
Light scattering
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