Supercharge Your Innovation With Domain-Expert AI Agents!

Diffractive optical element based on neural network and design method thereof

A diffractive optical element and neural network technology, applied in the field of diffractive optical element and its design, can solve problems such as local optimal solution and dependent optimization starting point, and achieve the effect of great flexibility

Pending Publication Date: 2022-06-21
爱思菲尔光学科技(苏州)有限公司
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, existing algorithms such as Geigerberg-Thaxton (GS) are difficult to take into account both at the same time, and rely on the optimization starting point, which is easy to fall into a local optimal solution

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Diffractive optical element based on neural network and design method thereof
  • Diffractive optical element based on neural network and design method thereof
  • Diffractive optical element based on neural network and design method thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0037] In order to make the objectives, technical solutions and advantages of the present disclosure clearer, the present disclosure will be further described in detail below with reference to the specific embodiments and the accompanying drawings.

[0038] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of the present disclosure should have the usual meanings understood by those with ordinary skill in the art to which the present disclosure belongs. "First", "second" and similar words used in the embodiments of the present disclosure do not denote any order, quantity or importance, but are only used to distinguish different components. "Comprising" or "comprising" and similar words mean that the elements or things appearing before the word encompass the elements or things recited after the word and their equivalents, but do not exclude other elements or things. Words like "connected" or "connected" are not limited t...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a diffractive optical element based on a neural network and a design method thereof. The design method of the diffractive optical element based on the neural network comprises the following steps: calculating intensity distribution of a light field passing through the diffractive optical element through a field propagation physical model; by establishing a neural network, the phase distribution of the required intensity distribution is optimized. According to the design method of the diffractive optical element based on the neural network, the iterative recurrent neural network is provided, the precision and the imaging quality in the design of the diffractive optical element can be effectively ensured, the flexibility is high, and the speed is high.

Description

technical field [0001] The present disclosure relates to the field of optoelectronic technology, and relates to a neural network-based diffractive optical element and a design method thereof. Background technique [0002] In the prior art, the realization of a specially tailored laser beam intensity distribution is of particular importance in various applications. For example, in laser-based material processing, improving the quality of the workpiece is closely related to the intensity distribution of the laser light in the focal region. Alternatively, for optical tweezers and atomic traps, the light intensity distribution defines the trap potential. Furthermore, structured illumination enables 3D object reconstruction in fringe projection profilometry or facial recognition in modern mobile phone applications. These field distributions are usually achieved by changing the phase of the initial laser beam through specially designed phase masks, such as diffractive optical el...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G02B27/00G02B27/42G06N3/04G06N3/08
CPCG02B27/0012G02B27/4205G06N3/08G06N3/045
Inventor 詹耀辉
Owner 爱思菲尔光学科技(苏州)有限公司
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com