Multifocal multilevel diffractive lens by wavelength multiplexing

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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Sep 05, 2023
Source ID
10.1364/ao.497775

Entities

People

  • Berardi Sensale-Rodriguez
  • Dajun Lin
  • Rajesh Menon
  • Wei Jia

Organizations

  • National Science Foundation
  • Office of Naval Research
  • University of Utah

Tags

Fields of Study

  • Physics

Readers

  • Image Processing and Computer Vision.
  • Nanofabrication and Microfabrication.
  • Vision Science/Vision Psychology/Cognitive Neuroscience.

Technology Areas

  • AI & ML
  • Directed Energy