The advent of deep integration and development in the domains of information technology and computational science has precipitated a paradigm shift in modern imaging technology, transitioning it from a device-driven model to one that is increasingly led by information transmission. Consequently, computational imaging has emerged as a paradigm shift, transcending the limitations of conventional technological approaches by establishing an interdisciplinary research framework that integrates multi-dimensional physical information perception and computational information interpretation. Prof. Fei Liu of Xidian University was recently invited by the editor-in-chief of Photonics Insights to co-author a paper entitled "Revolutionizing Optical Imaging: Computational imaging via deep learning". The project is being led by Prof. Chao Zuo of Nanjing University of Science and Technology, Prof. Zihan Geng of Tsinghua University, and Postdoc Yi Wei of MIT.

At the invitation from the founding Editor-in-Chief of Photonics Insights, Prof. Xingjun Wang and Prof. Haowen Shu from Peking University jointly authored a review article titled "Microcomb technology: from principles to applications". The article was published in Issue 4, Volume 3 of Photonics Insights in 2024. (Haowen Shu, Bitao Shen, Huajin Chang, Junhao Han, Jiong Xiao, Xingjun Wang. Microcomb technology: from principles to applications [J]. Photonics Insights, 2024, 3(4): R09)

In most photon systems, losses usually affect the performance of the photon system and increase energy consumption. When we mention "losses", it seems that we cannot think of anything else to use them for besides being used as absorbers. Therefore, in experiments, everyone is thinking about how to eliminate this "trouble". However, in experiments and practical applications, even with advanced processes and materials, not all losses can be completely eliminated. Is loss really just about being a loser? Through research, some scientists have taken a different approach and found ways to turn loss into treasure: by utilizing the exceptional points (EPs) in optical non-Hermitian systems, appropriate control of losses can bring better performance to the system or novel functions that are difficult to achieve with traditional optical systems.

Fluorescence microscopy, as a pivotal tool in the life sciences, grapples with the challenges of background fluorescence interference and the optical diffraction limit. Structured Illumination Microscopy (SIM), a significant branch of super-resolution techniques, can enhance resolution up to twice the diffraction limit. It boasts the advantages of being "gentle" (lower excitation intensity, minimizing sample damage) and "inclusive" (no need for special labeling or complex processing), making it a recent focus of research.