Abstract
Flat lenses with focal length tunability can enable the development of
highly integrated imaging systems. This work explores machine learning
to inverse design a multifocal multilevel diffractive lens (MMDL) by
wavelength multiplexing. The MMDL output is multiplexed in three color
channels, red (650 nm), green (550 nm), and blue
(450 nm), to achieve varied focal lengths of 4 mm,
20 mm, and 40 mm at these three color channels,
respectively. The focal lengths of the MMDL scale significantly with
the wavelength in contrast to conventional diffractive lenses. The
MMDL consists of concentric rings with equal widths and varied
heights. The machine learning method is utilized to optimize the
height of each concentric ring to obtain the desired phase
distribution so as to achieve varied focal lengths multiplexed by
wavelengths. The designed MMDL is fabricated through a direct-write
laser lithography system with gray-scale exposure. The demonstrated
singlet lens is miniature and polarization insensitive, and thus can
potentially be applied in integrated optical imaging systems to
achieve zooming functions.
Funder
National Science Foundation
Office of Naval Research
Subject
Atomic and Molecular Physics, and Optics,Engineering (miscellaneous),Electrical and Electronic Engineering