Open AccessInverse design of optical needles with central zero-intensity points by artificial neural networks
Author(s) -
Xin Wei,
Qiming Zhang,
Miṅ Gu
Publication year - 2020
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.410073
Subject(s) - optics , inverse , intensity (physics) , artificial neural network , light intensity , optical phenomena , point spread function , optical axis , inverse problem , physics , materials science , computer science , mathematics , geometry , lens (geology) , mathematical analysis , artificial intelligence
Optical needles with central zero-intensity points have attracted much attention in the field of 3D super-resolution microscopy, optical lithography, optical storage and Raman spectroscopy. Nevertheless, most of the studies create few types of optical needles with central zero-intensity points based on the theory and intuition with time-consuming parameter sweeping and complex pre-select of parameters. Here, we report on the inverse design of optical needles with central zero-intensity points by dipole-based artificial neural networks (DANNs), permitting the creation of needles which are close to specific length and amplitude. The resolution of these optical needles with central zero-intensity points is close to axial diffraction limit (∼1λ). Additionally, the DANNs can realize the inverse design of several types on-axis distributions, such as optical needles and multifocal distributions.