BELLINGHAM, Washington, USA — The highly selective and high-impact journal Advanced Photonics has selected the Editor-in-Chief Choice Awards for the best papers published in the journal in 2024.
Established in 2019, Advanced Photonics publishes innovative research in all areas of optics and photonics, including fundamental and applied research. The Gold Open Access journal is co-published by SPIE, the international society for optics and photonics, and Chinese Laser Press (CLP). Available online in the SPIE Digital Library and at CLP’s Researching site, the journal has an Impact Factor of 20.6 and a CiteScore of 22.7, among the highest for the optics and photonics discipline.
Xiao-Cong (Larry) Yuan, of Shenzhen University and Zhejiang Lab, and Anatoly Zayats, of King's College London, jointly serve as the founding co-editors-in-chief for the journal. The Advanced Photonics Editor-in-Chief Choice Awards, established in 2020, recognize exceptional papers — typically, an original research article and a review article — based on the importance of the work to the optics and photonics field. Articles published between December 2023 and December 2024 were eligible for the honor.
The winning research article “Programming nonlinear propagation for efficient optical learning machines” was published in January of 2024 and authored by Ilker Oguz, Jih-Liang Hsieh, Niyazi Ulas Dinc, Mustafa Yildirim, Carlo Gigli, Christophe Moser, and Demetri Psaltis, all from École Polytechnique Fédérale de Lausanne in Switzerland, and Uğur Teğin of École Polytechnique Fédérale de Lausanne and Koç University in Turkey.
“The paper explores innovative methods for enhancing machine-learning efficiency using optical neural networks in an integrable manner,” Zayats said. “Programming nonlinear propagation inside multimode fibers with wavefront-shaping techniques allows exploitation of complex optical interactions for computation purposes, and achieves results on par with multilayer neural networks while consuming orders of magnitude less energy for performing the equivalent number of computations. This paves the way for more sustainable and efficient machine-learning solutions.”
The winning review article “Metasurface-based computational imaging: a review” was published in February 2024 and authored by Xuemei Hu, Weizhu Xu, Qingbin Fan, Tao Yue, Feng Yan, Yanqing Lu, and Ting Xu, all from Nanjing University in China.
“This review article presents a timely analysis and comprehensive summary of recent scientific advancements and innovations in metasurfaces for computational imaging,” noted Yuan. “In addition to summarizing the existing literature, concerning the intricate technical challenges confronting metasurface-based computational imaging systems, the authors provide valuable insights into potential research directions and technical solutions.”
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