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Faster and More Acc...
Faster and More Accurate Geometrical-Optics Optical Force Calculation Using Neural Networks
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Bronte Ciriza, David (författare)
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Magazzù, Alessandro (författare)
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- Callegari, Agnese (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för fysik (GU),Department of Physics (GU)
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Barbosa, Gunther (författare)
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Neves, Antonio A.R. (författare)
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Iatì, Maria Antonia (författare)
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- Volpe, Giovanni, 1979 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för fysik (GU),Department of Physics (GU)
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Maragò, Onofrio M. (författare)
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(creator_code:org_t)
- 2022-12-19
- 2022
- Engelska.
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Ingår i: ACS Photonics. - : American Chemical Society (ACS). - 2330-4022. ; 10:1, s. 234-41
- Relaterad länk:
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https://gup.ub.gu.se...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Optical forces are often calculated by discretizing the trapping light beam into a set of rays and using geometrical optics to compute the exchange of momentum. However, the number of rays sets a trade-off between calculation speed and accuracy. Here, we show that using neural networks permits overcoming this limitation, obtaining not only faster but also more accurate simulations. We demonstrate this using an optically trapped spherical particle for which we obtain an analytical solution to use as ground truth. Then, we take advantage of the acceleration provided by neural networks to study the dynamics of ellipsoidal particles in a double trap, which would be computationally impossible otherwise.
Ämnesord
- NATURVETENSKAP -- Fysik (hsv//swe)
- NATURAL SCIENCES -- Physical Sciences (hsv//eng)
Nyckelord
- ellipsoids
- Kramer's rate
- machine learning
- optical forces
- optical tweezers
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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