Three-dimensional vectorial holography based on machine learning inverse design-Reference-Cited by-同舟云学术

Three-dimensional vectorial holography based on machine learning inverse design

Published:2020-04-17 Issue:16 Volume:6 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Ren Haoran¹²^ORCID,Shao Wei³^ORCID,Li Yi²^ORCID,Salim Flora³^ORCID,Gu Min¹⁴^ORCID

Affiliation:

1. Laboratory of Artificial-Intelligence Nanophotonics, School of Science, RMIT University, Melbourne, Victoria 3001, Australia.

2. Chair in Hybrid Nanosystems, Nanoinstitute Munich, Faculty of Physics, Ludwig-Maximilians-University Munich, 80539 Munich, Germany.

3. Computer Science, School of Science, RMIT University, Melbourne, Victoria 3001, Australia.

4. Centre for Artificial-Intelligence Nanophotonics, School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.

Abstract

3D vectorial holography reconstructs an arbitrary 3D vectorial field–carrying wavefront using machine learning inverse design.

Funder

American Friends of the Alexander von Humboldt Foundation

Australian Research Council

Victoria Government in Australia

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference40 articles.

1. A New Microscopic Principle

2. A Three-Color, Solid-State, Three-Dimensional Display

3. An updatable holographic three-dimensional display

4. Holographic three-dimensional telepresence using large-area photorefractive polymer

5. A photophoretic-trap volumetric display

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