CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 11804 > Article
Presentation
1 August 2021 Machine learning to improve the calculation of optical forces in the geometrical optics approximation
David Bronte Ciriza, Alessandro Magazzù, Agnese Callegari, Maria A. Iatì, Giovanni Volpe, Onofrio M. Maragò
Author Affiliations +
Proceedings Volume 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021; 1180415 (2021) https://doi.org/10.1117/12.2593836
Event: SPIE Nanoscience + Engineering, 2021, San Diego, California, United States
Abstract
Even though in most cases optical forces can be calculated semi-analytically, the computation becomes prohibitively slow in problems where the calculation needs to be repeated several times. Starting from a spherical particle in an optical trap, we show how machine learning can be used to improve not only the speed but also the accuracy of the optical force calculations in the geometrical optics approach. This is demonstrated to work efficiently at least up to 9 degrees of freedom, constituting a tool for exploring problems that were out of the scope of the traditional geometrical optics calculation.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
David Bronte Ciriza, Alessandro Magazzù, Agnese Callegari, Maria A. Iatì, Giovanni Volpe, and Onofrio M. Maragò "Machine learning to improve the calculation of optical forces in the geometrical optics approximation", Proc. SPIE 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021, 1180415 (1 August 2021); https://doi.org/10.1117/12.2593836
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 PRESENTATION
WATCH
PRESENTATION SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
KEYWORDS
Geometrical optics
Machine learning
Particles
Computing systems
Neural networks
Numerical simulations
Objectives
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top