Conjugate symmetric extension Fourier computer-generated holography with controllable reconstruction focus

Li, Chunyu; Huang, Sujuan; Liu, Xianpeng

doi:10.1007/s00340-023-07990-4

Cited by 2 publications

(1 citation statement)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Autoencoders were also used for compressing the dimension of the metamaterials design space. [ 81,225 ] Compared to DGMs like VAEs and GANs, autoencoders only minimize the reconstruction errors of training samples without considering the continuity of the latent space, which may reduce the efficiency of design optimization and latent space analysis.…”

Section: Data‐driven Unit Cell Design Of Metamaterialsmentioning

confidence: 99%

Data‐Driven Design for Metamaterials and Multiscale Systems: A Review

Lee,

Chen,

Wang

et al. 2023

Advanced Materials

View full text Add to dashboard Cite

Metamaterials are artificial materials designed to exhibit effective material parameters that go beyond those found in nature. Composed of unit cells with rich designability that are assembled into multiscale systems, they hold great promise for realizing next‐generation devices with exceptional, often exotic, functionalities. However, the vast design space and intricate structure–property relationships pose significant challenges in their design. A compelling paradigm that could bring the full potential of metamaterials to fruition is emerging: data‐driven design. This review provides a holistic overview of this rapidly evolving field, emphasizing the general methodology instead of specific domains and deployment contexts. Existing research is organized into data‐driven modules, encompassing data acquisition, machine learning‐based unit cell design, and data‐driven multiscale optimization. The approaches are further categorized within each module based on shared principles, analyze and compare strengths and applicability, explore connections between different modules, and identify open research questions and opportunities.

show abstract

Section: Data‐driven Unit Cell Design Of Metamaterialsmentioning

confidence: 99%

Data‐Driven Design for Metamaterials and Multiscale Systems: A Review

Lee,

Chen,

Wang

et al. 2023

Advanced Materials

View full text Add to dashboard Cite

show abstract

Color image information transmission based on elliptic optical vortex array encoding/decoding

Liu¹,

Huang²,

Li³

2023

Opt. Express

View full text Add to dashboard Cite

A multichannel high-dimensional data encoding/decoding scheme based on composite elliptic optical vortex (EOV) arrays is proposed. By exploiting the rotation angle of the EOV, a 4 × 4 composite EOV array is used for high-dimensional data encoding. The conjugate symmetric extension Fourier computer-generated holography algorithm with controllable reconstruction focus is used to assign different reconstruction focus to the data of the three channels (R, G, and B) of the color image. Then, the data of the three channels is transmitted simultaneously by a single hologram to further improve the transmission efficiency. At the receiver, the initial information sequence is decoded by directly identifying the captured intensity patterns with a deep learning-based convolutional neural network. In the experiment, a 128 × 128-pixel color image is successfully transmitted, which confirms the feasibility of our proposed encoding/decoding scheme. This method has great potential for future high-capacity optical communications.

show abstract

Conjugate symmetric extension Fourier computer-generated holography with controllable reconstruction focus

Cited by 2 publications

References 34 publications

Data‐Driven Design for Metamaterials and Multiscale Systems: A Review

Data‐Driven Design for Metamaterials and Multiscale Systems: A Review

Color image information transmission based on elliptic optical vortex array encoding/decoding

Contact Info

Product

Resources

About