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Cited by 320

The DOI matches its Crossref record; 172 of the 172 references it cites were found in a registry or an index.

Highlighting photonics: looking into the next decade

Open access
Chen, Zhigang, Segev, Mordechai·2021·eLight

Abstract

Let there be light–to change the world we want to be! Over the past several decades, and ever since the birth of the first laser, mankind has witnessed the development of the science of light, as light-based technologies have revolutionarily changed our lives. Needless to say, photonics has now penetrated into many aspects of science and technology, turning into an important and dynamically changing field of increasing interdisciplinary interest. In this inaugural issue of eLight, we highlight a few emerging trends in photonics that we think are likely to have major impact at least in the upcoming decade, spanning from integrated quantum photonics and quantum computing, through topological/non-Hermitian photonics and topological insulator lasers, to AI-empowered nanophotonics and photonic machine learning. This Perspective is by no means an attempt to summarize all the latest advances in photonics, yet we wish our subjective vision could fuel inspiration and foster excitement in scientific research especially for young researchers who love the science of light.

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Metadata

Authors
Chen, Z., & Segev, M.
Venue
eLight
Published
2021-06-08
Volume
1
Issue
1
ISSN
  • 2097-1710 (ISSN-L)
  • 2662-8643
OpenAlex
W3171489384
Cited by
320
References
172
FWCI
19.59
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: Highlighting photonics: looking into the next decade. https://app.cochat.ai/papers/10.1186/s43593-021-00002-y
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Chen, Z., & Segev, M. (2021). Highlighting photonics: looking into the next decade. eLight. https://doi.org/10.1186/s43593-021-00002-y

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.