Reviews|69 Article(s)
Reviews
Synthesis and applications of fluorescent cationic polyelectrolytes for light-triggered antimicrobial therapy
Xiang Su, Dong Wang, Ting Han, and Ben Zhong Tang
Microbial infections, particularly those caused by emerging and antibiotic-resistant pathogens pose grave threats to human health. As a powerful antibiotic-free strategy, light-triggered therapy offers non-invasive treatment with low side effects, broad antimicrobial spectra, and reduced resistance potency. Among various light-responsive antimicrobial agents, fluorescent cationic polyelectrolytes (FCPs) have attracted great attention due to their intrinsic dark toxicity to microbes together with efficient generation capabilities of reactive oxygen species and heat under light irradiation, enabling multifaceted antimicrobial treatment via photodynamic and/or photothermal therapies. This review summarizes the recent advances in the synthesis and light-triggered antimicrobial applications of different types of FCPs, including side-chain fluorescent cationic polyelectrolytes (SFCPs) and main-chain fluorescent cationic polyelectrolytes (MFCPs). The commonly used synthetic routes and structures of SFCPs and MFCPs are discussed in detail. In view of the critical role of positively charged moieties, we further classify FCPs into different groups based on their embedded cationic structures and provide a detailed description of the light-triggered antimicrobial scenarios of SFCPs and MFCPs bearing different cations. Finally, the existing challenges and future perspectives of FCP-based antimicrobial phototherapy are outlined to provide insights into the development of FCP bactericides with more diversified structures and advanced functionalities. Microbial infections, particularly those caused by emerging and antibiotic-resistant pathogens pose grave threats to human health. As a powerful antibiotic-free strategy, light-triggered therapy offers non-invasive treatment with low side effects, broad antimicrobial spectra, and reduced resistance potency. Among various light-responsive antimicrobial agents, fluorescent cationic polyelectrolytes (FCPs) have attracted great attention due to their intrinsic dark toxicity to microbes together with efficient generation capabilities of reactive oxygen species and heat under light irradiation, enabling multifaceted antimicrobial treatment via photodynamic and/or photothermal therapies. This review summarizes the recent advances in the synthesis and light-triggered antimicrobial applications of different types of FCPs, including side-chain fluorescent cationic polyelectrolytes (SFCPs) and main-chain fluorescent cationic polyelectrolytes (MFCPs). The commonly used synthetic routes and structures of SFCPs and MFCPs are discussed in detail. In view of the critical role of positively charged moieties, we further classify FCPs into different groups based on their embedded cationic structures and provide a detailed description of the light-triggered antimicrobial scenarios of SFCPs and MFCPs bearing different cations. Finally, the existing challenges and future perspectives of FCP-based antimicrobial phototherapy are outlined to provide insights into the development of FCP bactericides with more diversified structures and advanced functionalities.
Advanced Photonics
- Publication Date: Dec. 02, 2025
- Vol. 8, Issue 1, 014002 (2026)
Statistical physics and nonlinear dynamics in random fiber lasers: from theory to multidisciplinary applications
Yifei Qi, Wangyouyou Li, Jing Zhang, Weili Zhang, Han Wu, Ernesto P. Raposo, Anderson S. L. Gomes, and Zinan Wang
As a novel optical platform, random fiber laser (RFL) exhibits multiple metastable energy landscapes due to its disordered feedback mechanism and nonlinear effects, which make it an ideal platform for the study of nonequilibrium statistical physics and multiple nonlinear optical effects. We systematically explores the progress of cutting-edge research on RFL from three key perspectives: complex physical properties, time-domain dynamics, and frequency-domain dynamics in conjunction with theoretical models. In particular, the refinement of the modeling of Rayleigh scattering promotes the study of the replica symmetry breaking phenomenon of RFL. On the basis of this theoretical study, the article elucidates the innovative applications of RFL in several fields, especially providing new possibilities in the field of laser-driven inertial confinement fusion. Finally, the article explores the challenges and possibilities of RFL integration with cutting-edge fields, such as neural networks, and provides an outlook on its prospects for multidisciplinary fusion applications. As a novel optical platform, random fiber laser (RFL) exhibits multiple metastable energy landscapes due to its disordered feedback mechanism and nonlinear effects, which make it an ideal platform for the study of nonequilibrium statistical physics and multiple nonlinear optical effects. We systematically explores the progress of cutting-edge research on RFL from three key perspectives: complex physical properties, time-domain dynamics, and frequency-domain dynamics in conjunction with theoretical models. In particular, the refinement of the modeling of Rayleigh scattering promotes the study of the replica symmetry breaking phenomenon of RFL. On the basis of this theoretical study, the article elucidates the innovative applications of RFL in several fields, especially providing new possibilities in the field of laser-driven inertial confinement fusion. Finally, the article explores the challenges and possibilities of RFL integration with cutting-edge fields, such as neural networks, and provides an outlook on its prospects for multidisciplinary fusion applications.
Advanced Photonics
- Publication Date: Nov. 12, 2025
- Vol. 8, Issue 1, 014001 (2026)
Integrated continuous-variable quantum light sources for quantum computing
Xuezhi Zhu, Siyu Ren, Yunyun Cao, and Xiaolong Su
Continuous-variable (CV) quantum light sources are the essential resource for quantum computation. Integrated CV quantum light sources offer a scalable pathway by harnessing low-loss nonlinear materials, versatile device architectures, and CMOS-compatible fabrication processes enabled by integrated photonics platforms. In this review, we briefly introduce recent progress on integrated CV quantum light sources, including single-mode squeezed states, two-mode squeezed states, and multimode entangled states. The key performance metrics of CV quantum light sources, such as the squeezing level, bandwidth, purity, and mode multiplexing, are analyzed. We highlight representative implementations of lithium niobate, silicon nitride, and silica platforms for CV quantum light sources and discuss major challenges for realizing integrated large-scale and fault-tolerant CV quantum computation. Continuous-variable (CV) quantum light sources are the essential resource for quantum computation. Integrated CV quantum light sources offer a scalable pathway by harnessing low-loss nonlinear materials, versatile device architectures, and CMOS-compatible fabrication processes enabled by integrated photonics platforms. In this review, we briefly introduce recent progress on integrated CV quantum light sources, including single-mode squeezed states, two-mode squeezed states, and multimode entangled states. The key performance metrics of CV quantum light sources, such as the squeezing level, bandwidth, purity, and mode multiplexing, are analyzed. We highlight representative implementations of lithium niobate, silicon nitride, and silica platforms for CV quantum light sources and discuss major challenges for realizing integrated large-scale and fault-tolerant CV quantum computation.
Advanced Photonics
- Publication Date: Nov. 13, 2025
- Vol. 7, Issue 6, 064005 (2025)
Review of nonlinear activation functions in optical neural networks
Wanxin Shi, Zheng Huang, Tingzhao Fu, and Hongwei Chen
Recently, the rapid development of electronic neural networks (ENNs) has enabled the widespread application of artificial intelligence in fields such as computer vision, natural language processing, and autonomous systems. As an emerging computing paradigm, optical neural networks (ONNs) have become a promising alternative to their electronic counterparts, offering advantages such as ultrahigh speed, low latency, and inherent parallelism. Nonlinear activation functions in ENNs are known to accelerate network convergence and improve accuracy across various tasks. Similarly, incorporating optical nonlinear activation functions into ONNs is crucial for achieving fully optical-domain neural network computing, which is an essential step toward leveraging the high-speed and high-capacity computing potential of ONNs. In this work, we first introduced several methods for implementing optical nonlinear activation functions. We then propose approaches for measuring their activation curves and exploring their interactions within network architectures. Finally, we demonstrated their roles in ONNs and discussed future development prospects and remaining challenges. Recently, the rapid development of electronic neural networks (ENNs) has enabled the widespread application of artificial intelligence in fields such as computer vision, natural language processing, and autonomous systems. As an emerging computing paradigm, optical neural networks (ONNs) have become a promising alternative to their electronic counterparts, offering advantages such as ultrahigh speed, low latency, and inherent parallelism. Nonlinear activation functions in ENNs are known to accelerate network convergence and improve accuracy across various tasks. Similarly, incorporating optical nonlinear activation functions into ONNs is crucial for achieving fully optical-domain neural network computing, which is an essential step toward leveraging the high-speed and high-capacity computing potential of ONNs. In this work, we first introduced several methods for implementing optical nonlinear activation functions. We then propose approaches for measuring their activation curves and exploring their interactions within network architectures. Finally, we demonstrated their roles in ONNs and discussed future development prospects and remaining challenges.
Advanced Photonics
- Publication Date: Nov. 06, 2025
- Vol. 7, Issue 6, 064004 (2025)
Optical computing and optical signal processing for recovery of spatiotemporally coupled optical communications channels
Jie Liu, Zhenhua Li, Yibin Wan, Jiaqing Li, and Siyuan Yu
We explore an emerging frontier in optical communications—leveraging optical computing and optical signal processing to restore degraded signals in space or mode-division multiplexing (SDM/MDM) systems. As SDM/MDM pushes toward ever-higher channel densities within a single fiber, inter-channel optical coupling leads to significant crosstalk. Due to group velocity mismatches, this crosstalk spatiotemporally entangles optical signal streams, significantly complicating multi-input multi-output digital signal processing (MIMO DSP) for signal recovery across both spatial and temporal domains. Free-space optical systems face similar challenges from multipath interference. We systematically appraise two strategic pathways of optically addressing the spatiotemporal interference: (1) optoelectronic computing that either accelerates conventional linear MIMO DSP or maps the problem onto physics-inspired models solvable by analog or hybrid optoelectronic systems and (2) all-optical processing that seeks to untangle the coupled optical signals directly within the optical domain. For both pathways, we evaluate architectural effectiveness and scalability based on rigorous mathematical analysis, aiming to offer insights into promising approaches for future research. We explore an emerging frontier in optical communications—leveraging optical computing and optical signal processing to restore degraded signals in space or mode-division multiplexing (SDM/MDM) systems. As SDM/MDM pushes toward ever-higher channel densities within a single fiber, inter-channel optical coupling leads to significant crosstalk. Due to group velocity mismatches, this crosstalk spatiotemporally entangles optical signal streams, significantly complicating multi-input multi-output digital signal processing (MIMO DSP) for signal recovery across both spatial and temporal domains. Free-space optical systems face similar challenges from multipath interference. We systematically appraise two strategic pathways of optically addressing the spatiotemporal interference: (1) optoelectronic computing that either accelerates conventional linear MIMO DSP or maps the problem onto physics-inspired models solvable by analog or hybrid optoelectronic systems and (2) all-optical processing that seeks to untangle the coupled optical signals directly within the optical domain. For both pathways, we evaluate architectural effectiveness and scalability based on rigorous mathematical analysis, aiming to offer insights into promising approaches for future research.
Advanced Photonics
- Publication Date: Oct. 06, 2025
- Vol. 7, Issue 6, 064003 (2025)
Quantum sensing with spin defects: principles, progress, and prospects for use cases
Kihwan Kim, Jong Sung Moon, Dongkwon Lee, Jin Hee Lee, Yuhan Lee, Chanhu Park, Jugyeong Chung, Donghun Lee, and Je-Hyung Kim
Quantum sensing aims to detect signals with unparalleled sensitivity, potentially surpassing classical limitations. Solid-state spin defects, particularly nitrogen-vacancy centers in diamond, have emerged as promising platforms due to their long coherence time, optical addressability, high field sensitivity, and spatial and spectral resolution, making them ideal for sensing and imaging applications. Their compact size and robust performance under room temperature and ambient conditions further enhance their suitability for real-world applications. We provide an overview of quantum sensing principles and explore efforts to improve sensor functionality, including advanced sensing protocols, spatial imaging techniques, and integration with optical systems to enhance detection efficiency. We also highlight recent progress in the applications of these sensors across various use cases, including biomedical diagnostics, semiconductor device inspection, and industrial and military applications. Quantum sensing aims to detect signals with unparalleled sensitivity, potentially surpassing classical limitations. Solid-state spin defects, particularly nitrogen-vacancy centers in diamond, have emerged as promising platforms due to their long coherence time, optical addressability, high field sensitivity, and spatial and spectral resolution, making them ideal for sensing and imaging applications. Their compact size and robust performance under room temperature and ambient conditions further enhance their suitability for real-world applications. We provide an overview of quantum sensing principles and explore efforts to improve sensor functionality, including advanced sensing protocols, spatial imaging techniques, and integration with optical systems to enhance detection efficiency. We also highlight recent progress in the applications of these sensors across various use cases, including biomedical diagnostics, semiconductor device inspection, and industrial and military applications.
Advanced Photonics
- Publication Date: Sep. 24, 2025
- Vol. 7, Issue 6, 064002 (2025)
Erbium-doped/erbium-ytterbium co-doped waveguide amplifiers in silicon-based optoelectronics: recent progress
Xiwen He, Zheng Zhang, Deyue Ma, Chen Zhou, Huihuang Hou, Youqiang Shuai, Jiqiao Liu, Rongping Wang, Zhiping Zhou, and Weibiao Chen
Erbium-doped/erbium-ytterbium co-doped waveguide amplifiers (EDWAs/EYCDWAs) have received much attention as essential components within large-scale functionalized silicon-based optoelectronic (SBO) chips for their remarkable ability to amplify optical signals on-chip at the communication band combined with their potential application across diverse fields. We reviewed the research progress of EDWAs/EYCDWAs comprehensively. In particular, the research advancements concerning amplifiers constructed with diverse host materials are introduced in detail, and the gain limitations of the waveguide amplifiers are thoroughly analyzed from multiple perspectives, such as host materials and innovative structural designs. Subsequently, the preparation processes of the gain medium and waveguide structure in EDWAs/EYCDWAs are discussed, and their common application scenarios and commercial applications are summarized. In addition, an assessment is carried out on the challenges encountered by EDWAs/EYCDWAs. Finally, a discussion is held on their potential applications and development prospects in the field of SBO chips, with the aspiration of providing valuable references for the development of EDWAs/EYCDWAs. Erbium-doped/erbium-ytterbium co-doped waveguide amplifiers (EDWAs/EYCDWAs) have received much attention as essential components within large-scale functionalized silicon-based optoelectronic (SBO) chips for their remarkable ability to amplify optical signals on-chip at the communication band combined with their potential application across diverse fields. We reviewed the research progress of EDWAs/EYCDWAs comprehensively. In particular, the research advancements concerning amplifiers constructed with diverse host materials are introduced in detail, and the gain limitations of the waveguide amplifiers are thoroughly analyzed from multiple perspectives, such as host materials and innovative structural designs. Subsequently, the preparation processes of the gain medium and waveguide structure in EDWAs/EYCDWAs are discussed, and their common application scenarios and commercial applications are summarized. In addition, an assessment is carried out on the challenges encountered by EDWAs/EYCDWAs. Finally, a discussion is held on their potential applications and development prospects in the field of SBO chips, with the aspiration of providing valuable references for the development of EDWAs/EYCDWAs.
Advanced Photonics
- Publication Date: Sep. 24, 2025
- Vol. 7, Issue 6, 064001 (2025)
Nanophotonic phenomena driven by vector beams
Uttam Manna, Maya Chauhan and Mahua Biswas
Cylindrical vector beams (CVBs), characterized by their spatially varying polarization and axial symmetry, have emerged as powerful tools for engineering light–matter interactions at the nanoscale. Unlike conventional linearly polarized beams, tightly focused CVBs can generate strong longitudinal electric or magnetic field components, enabling the selective excitation of specific multipolar modes and various resulting modes in optical nanostructures. This unique field configuration facilitates the excitation of various optical phenomena such as anapole states, dark modes, Fano resonances, optical magnetism, and enhanced nonlinear optical responses, which are challenging to achieve with traditional illumination. We summarize recent advancements in nanophotonic phenomena/effects driven by CVB excitation, illustrated through seminal studies in plasmonic, dielectric, or hybrid nanostructures, offering promising opportunities for applications in imaging, sensing, optical trapping, quantum information processing, etc. We discuss how enhanced electromagnetic field confinement, increased coupling efficiency, and precise control over resonant scattering can lead to advanced nanophotonic phenomena/effects under CVB illumination. The insights presented here aim to guide future developments in structured light–matter interaction and inspire the design of advanced nanophotonic systems. Cylindrical vector beams (CVBs), characterized by their spatially varying polarization and axial symmetry, have emerged as powerful tools for engineering light–matter interactions at the nanoscale. Unlike conventional linearly polarized beams, tightly focused CVBs can generate strong longitudinal electric or magnetic field components, enabling the selective excitation of specific multipolar modes and various resulting modes in optical nanostructures. This unique field configuration facilitates the excitation of various optical phenomena such as anapole states, dark modes, Fano resonances, optical magnetism, and enhanced nonlinear optical responses, which are challenging to achieve with traditional illumination. We summarize recent advancements in nanophotonic phenomena/effects driven by CVB excitation, illustrated through seminal studies in plasmonic, dielectric, or hybrid nanostructures, offering promising opportunities for applications in imaging, sensing, optical trapping, quantum information processing, etc. We discuss how enhanced electromagnetic field confinement, increased coupling efficiency, and precise control over resonant scattering can lead to advanced nanophotonic phenomena/effects under CVB illumination. The insights presented here aim to guide future developments in structured light–matter interaction and inspire the design of advanced nanophotonic systems.
Advanced Photonics
- Publication Date: Oct. 16, 2025
- Vol. 7, Issue 5, 054004 (2025)
Integrated photonic recurrent processors
Yizhi Wang, Lingzhi Luo, Sizhe Xing, Chunhui Yao, Richard Penty, and Qixiang Cheng
Photonic accelerators have emerged as promising alternatives to conventional electronic processors because they offer unique advantages such as high parallelism, low propagation loss, and in-propagation computation, making them well-suited for modern machine learning tasks that benefit from scalable parallelism. Fundamental mathematical operations including matrix-vector multiplication, convolution, and nonlinear activation functions are readily achieved with all-optical components. Due to the fixed hardware sizes, most kernel reutilization with photonics is based on the intermediate optical–electrical–optical conversion and storage. Yet, for a class of algorithms where signal recurrence is intrinsic, such truncation is suboptimal. The advancement in photonic material platforms with low loss and high integration density makes direct optical signal feedback with on-chip waveguides feasible. This development enables a specialized class of devices that we term integrated photonic recurrent processors (IPRPs). IPRPs uniquely accelerate computation by incorporating optical delay memory and bypassing the conventional single-pass photonic computing overheads. We explore algorithms with inherent recurrence and their implementation using integrated photonics. We also highlight potential applications for IPRPs and discuss how emerging material technologies may drive their advancement. With ongoing improvements in fabrication, integration, and control, IPRPs hold strong promise as compact, energy-efficient platforms for advancing optical computing. Photonic accelerators have emerged as promising alternatives to conventional electronic processors because they offer unique advantages such as high parallelism, low propagation loss, and in-propagation computation, making them well-suited for modern machine learning tasks that benefit from scalable parallelism. Fundamental mathematical operations including matrix-vector multiplication, convolution, and nonlinear activation functions are readily achieved with all-optical components. Due to the fixed hardware sizes, most kernel reutilization with photonics is based on the intermediate optical–electrical–optical conversion and storage. Yet, for a class of algorithms where signal recurrence is intrinsic, such truncation is suboptimal. The advancement in photonic material platforms with low loss and high integration density makes direct optical signal feedback with on-chip waveguides feasible. This development enables a specialized class of devices that we term integrated photonic recurrent processors (IPRPs). IPRPs uniquely accelerate computation by incorporating optical delay memory and bypassing the conventional single-pass photonic computing overheads. We explore algorithms with inherent recurrence and their implementation using integrated photonics. We also highlight potential applications for IPRPs and discuss how emerging material technologies may drive their advancement. With ongoing improvements in fabrication, integration, and control, IPRPs hold strong promise as compact, energy-efficient platforms for advancing optical computing.
Advanced Photonics
- Publication Date: Oct. 03, 2025
- Vol. 7, Issue 5, 054003 (2025)
Deep learning for computational imaging: from data-driven to physics-enhanced approaches
Fei Wang, Juergen W. Czarske and Guohai Situ
Computational imaging (CI) leverages the joint optimization of optical system design and reconstruction algorithms, enabling superior performance in terms of dimensionality, resolution, efficiency, and hardware complexity. It has found widespread applications in medical diagnosis and astronomy, among others. Recently, deep learning (DL) has changed the paradigm of CI by harnessing learned priors from data through trained neural network models. However, widely used data-driven DL-based CI methods encounter difficulties related to training data acquisition, computation requirements, generalization, and interpretability. Recent studies have indicated that integrating the physics prior of the CI system into various components of DL pipelines (including training data, network design, and loss functions) holds promise for alleviating these challenges. To provide readers with a better understanding of the current research status and ideas, we present an overview of the state-of-the-art in DL-based CI. We begin by briefly introducing the concepts of CI and DL, followed by a comprehensive review of how DL addresses inverse problems in CI. Particularly, we focus on the emerging physics-enhanced approaches. We highlight the perspectives of future research directions and the transfer to real-world applications. Computational imaging (CI) leverages the joint optimization of optical system design and reconstruction algorithms, enabling superior performance in terms of dimensionality, resolution, efficiency, and hardware complexity. It has found widespread applications in medical diagnosis and astronomy, among others. Recently, deep learning (DL) has changed the paradigm of CI by harnessing learned priors from data through trained neural network models. However, widely used data-driven DL-based CI methods encounter difficulties related to training data acquisition, computation requirements, generalization, and interpretability. Recent studies have indicated that integrating the physics prior of the CI system into various components of DL pipelines (including training data, network design, and loss functions) holds promise for alleviating these challenges. To provide readers with a better understanding of the current research status and ideas, we present an overview of the state-of-the-art in DL-based CI. We begin by briefly introducing the concepts of CI and DL, followed by a comprehensive review of how DL addresses inverse problems in CI. Particularly, we focus on the emerging physics-enhanced approaches. We highlight the perspectives of future research directions and the transfer to real-world applications.
Advanced Photonics
- Publication Date: Sep. 03, 2025
- Vol. 7, Issue 5, 054002 (2025)
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