Elina I. Battalova, Aidar I. Minibaev, Indira G. Mustafina, Sergey S. Kharintsev
Photothermal therapy of oncological diseases, based on the targeted delivery of light‐harvesting agents such as dyes, nanoshells, and photosensitizers, remains a major focus of the scientific community. However, light can be effectively captured by optically transparent media through a scattering mechanism rather than absorption. This is achieved in spatially confined media, e.g., foams, colloids, gels, and tumors, which can impart extra momentum to electrons under light illumination, thereby enhancing the optical oscillator strength through indirect optical transitions. Spatial confinement induces additional electronic states, boosting the cross section of electronic light scattering (ELS), a phenomenon that manifests as a featureless broadband background in Raman spectra. This work studies thermo‐optical behaviors of percolating colloidal systems using ELS. We theoretically and experimentally demonstrate that a water‐in‐decane system stabilized by sodium bis(2‐ethylhexyl) sulfosuccinate () under continuous‐wave laser illumination with the moderate intensity of 1 kW/cm 2 can be heated by several tens of degrees at the percolation point. This effect is shown to originate from energy band bending in the optically transparent system. These findings hold unprecedented promise for the development of targeted thermo‐optical detection and treatment of specific cancers.
{"title":"Optically Transparent Percolating Colloids Heated by Electronic Light Scattering","authors":"Elina I. Battalova, Aidar I. Minibaev, Indira G. Mustafina, Sergey S. Kharintsev","doi":"10.1002/lpor.202502239","DOIUrl":"https://doi.org/10.1002/lpor.202502239","url":null,"abstract":"Photothermal therapy of oncological diseases, based on the targeted delivery of light‐harvesting agents such as dyes, nanoshells, and photosensitizers, remains a major focus of the scientific community. However, light can be effectively captured by optically transparent media through a scattering mechanism rather than absorption. This is achieved in spatially confined media, e.g., foams, colloids, gels, and tumors, which can impart extra momentum to electrons under light illumination, thereby enhancing the optical oscillator strength through indirect optical transitions. Spatial confinement induces additional electronic states, boosting the cross section of electronic light scattering (ELS), a phenomenon that manifests as a featureless broadband background in Raman spectra. This work studies thermo‐optical behaviors of percolating colloidal systems using ELS. We theoretically and experimentally demonstrate that a water‐in‐decane system stabilized by sodium bis(2‐ethylhexyl) sulfosuccinate () under continuous‐wave laser illumination with the moderate intensity of 1 kW/cm <jats:sup>2</jats:sup> can be heated by several tens of degrees at the percolation point. This effect is shown to originate from energy band bending in the optically transparent system. These findings hold unprecedented promise for the development of targeted thermo‐optical detection and treatment of specific cancers.","PeriodicalId":204,"journal":{"name":"Laser & Photonics Reviews","volume":"20 1","pages":""},"PeriodicalIF":11.0,"publicationDate":"2026-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147447738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tian Shuo Bai, Wen Yu Lu, Wen Jun Dai, Jia Rui Liu, Zi Xiang Xia, Jing Yuan Wang, Zhi Lin Gao, Tie Jun Cui, Xuanru Zhang
Non‐imaging target recognition by analyzing scattered waves is of vital application importance in various scenarios such as radar detection, automated systems, and life activity monitoring. Vortex wave features a helical phase structure which can be decomposed into infinite plane waves, thereby enabling information‐rich detection. Here, we develop a non‐imaging target recognition platform based on microwave vortex beams, which includes modules for target feature extraction and machine learning algorithms. A complex representation is proposed to fully characterize the amplitude and phase information of the scattered vortex waves, and a neural network (NN)‐based machine learning algorithm is used to extract the embedded information. The recognition performance is verified by experiments in distinguishing 12 different gestures from five individuals. The recognition accuracy can reach 100% for the single‐individual case and 99.1% for the cross‐individual case, completed in 0.48 and 0.117 ms, respectively. These findings offer a convenient, fast, and reliable approach for target detection and may promote broad applications in radar systems.
{"title":"Non‐Imaging Gesture Recognition Based on Complex Representation of Vortex Waves Empowered by Machine Learning","authors":"Tian Shuo Bai, Wen Yu Lu, Wen Jun Dai, Jia Rui Liu, Zi Xiang Xia, Jing Yuan Wang, Zhi Lin Gao, Tie Jun Cui, Xuanru Zhang","doi":"10.1002/lpor.202503222","DOIUrl":"https://doi.org/10.1002/lpor.202503222","url":null,"abstract":"Non‐imaging target recognition by analyzing scattered waves is of vital application importance in various scenarios such as radar detection, automated systems, and life activity monitoring. Vortex wave features a helical phase structure which can be decomposed into infinite plane waves, thereby enabling information‐rich detection. Here, we develop a non‐imaging target recognition platform based on microwave vortex beams, which includes modules for target feature extraction and machine learning algorithms. A complex representation is proposed to fully characterize the amplitude and phase information of the scattered vortex waves, and a neural network (NN)‐based machine learning algorithm is used to extract the embedded information. The recognition performance is verified by experiments in distinguishing 12 different gestures from five individuals. The recognition accuracy can reach 100% for the single‐individual case and 99.1% for the cross‐individual case, completed in 0.48 and 0.117 ms, respectively. These findings offer a convenient, fast, and reliable approach for target detection and may promote broad applications in radar systems.","PeriodicalId":204,"journal":{"name":"Laser & Photonics Reviews","volume":"10 1","pages":""},"PeriodicalIF":11.0,"publicationDate":"2026-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147454698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jilun Zhao, Jiaqi Zhang, Zhiyuan Ye, Hong‐Chao Liu, Hai‐Bo Wang, Jun Xiong
Diffractive neural networks, as a representative approach to free‐space optical diffractive information processing, exploit the intrinsic advantages of light, including low power consumption and parallelism, to efficiently perform various visual tasks. For a specific visual task, such as optical classification, a physical decoder composed of cascaded diffractive surfaces must be carefully trained and subsequently fabricated with high precision. However, the precision manufacturing of diffractive processors typically involves substantial cost and produces devices that are not reprogrammable, thereby limiting the achievable parallelism for handling multiple targets. In this work, linear optical decoders in diffractive computing are virtualized as meta‐decoders without a physical embodiment. This approach enables a hybrid optical‐electronic classification framework that exploits correlations between optically inferred fields and computer‐generated virtual reference fields. The proposed scheme integrates computational ghost diffraction with diffractive computing, referred to as ghost classification. It provides several advantages, including single‐point detection, a lens‐free configuration, pattern‐independent flexibility, reprogrammability, and the ability to classify multi‐class targets in parallel. This work leverages the complementary strengths of hybrid optical‐electronic inference while incorporating lightweight electrical computations through multiplication‐only correlation operations. The resulting framework serves as a transitional architecture in which each processing unit remains physically interpretable rather than a black box.
{"title":"Ghost Classification Using Meta‐Decoders and Optical‐Electronic Correlations","authors":"Jilun Zhao, Jiaqi Zhang, Zhiyuan Ye, Hong‐Chao Liu, Hai‐Bo Wang, Jun Xiong","doi":"10.1002/lpor.202502943","DOIUrl":"https://doi.org/10.1002/lpor.202502943","url":null,"abstract":"Diffractive neural networks, as a representative approach to free‐space optical diffractive information processing, exploit the intrinsic advantages of light, including low power consumption and parallelism, to efficiently perform various visual tasks. For a specific visual task, such as optical classification, a physical decoder composed of cascaded diffractive surfaces must be carefully trained and subsequently fabricated with high precision. However, the precision manufacturing of diffractive processors typically involves substantial cost and produces devices that are not reprogrammable, thereby limiting the achievable parallelism for handling multiple targets. In this work, linear optical decoders in diffractive computing are virtualized as meta‐decoders without a physical embodiment. This approach enables a hybrid optical‐electronic classification framework that exploits correlations between optically inferred fields and computer‐generated virtual reference fields. The proposed scheme integrates computational ghost diffraction with diffractive computing, referred to as ghost classification. It provides several advantages, including single‐point detection, a lens‐free configuration, pattern‐independent flexibility, reprogrammability, and the ability to classify multi‐class targets in parallel. This work leverages the complementary strengths of hybrid optical‐electronic inference while incorporating lightweight electrical computations through multiplication‐only correlation operations. The resulting framework serves as a transitional architecture in which each processing unit remains physically interpretable rather than a black box.","PeriodicalId":204,"journal":{"name":"Laser & Photonics Reviews","volume":"16 1","pages":""},"PeriodicalIF":11.0,"publicationDate":"2026-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147454699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We present a portable liquid crystal (LC)-based optoelectronic hybrid neural network system for high-precision formaldehyde sensing. Central to the platform is an electrically tunable LC-on-Chip module, optimized via a progressive inverse design strategy that co-optimizes optical and neural network parameters. We introduce LC-chromatic aberration coding, a novel optical computing mechanism that efficiently captures rich spatial-spectral features, which are subsequently decoded by the integrated neural network to quantify formaldehyde with high selectivity. The compact device achieves approximately triple that of commercial kits and matches laboratory-grade spectrophotometers, despite occupying less than 1% of their volume. It further exhibits robust interference rejection against acetaldehyde and other VOCs in complex mixtures. By synergizing optical coding with co-optimized hardware and algorithm, this work bridges the gap between portability and lab-scale performance, enabling scalable, intelligent indoor air quality monitoring.
{"title":"Reconfigurable Optical Computing via Electrically Tunable Liquid Crystals: A Framework for Intelligent Miniaturized Spectroscopy","authors":"Zikang Li, Hui Li, Xiaoyue Song, Xianhui Zhu, Zhiwei Wang, Weixing Yu, Hongfei Liu, Yuntao Wu","doi":"10.1002/lpor.202502925","DOIUrl":"https://doi.org/10.1002/lpor.202502925","url":null,"abstract":"We present a portable liquid crystal (LC)-based optoelectronic hybrid neural network system for high-precision formaldehyde sensing. Central to the platform is an electrically tunable LC-on-Chip module, optimized via a progressive inverse design strategy that co-optimizes optical and neural network parameters. We introduce LC-chromatic aberration coding, a novel optical computing mechanism that efficiently captures rich spatial-spectral features, which are subsequently decoded by the integrated neural network to quantify formaldehyde with high selectivity. The compact device achieves approximately triple that of commercial kits and matches laboratory-grade spectrophotometers, despite occupying less than 1% of their volume. It further exhibits robust interference rejection against acetaldehyde and other VOCs in complex mixtures. By synergizing optical coding with co-optimized hardware and algorithm, this work bridges the gap between portability and lab-scale performance, enabling scalable, intelligent indoor air quality monitoring.","PeriodicalId":204,"journal":{"name":"Laser & Photonics Reviews","volume":"20 1","pages":""},"PeriodicalIF":11.0,"publicationDate":"2026-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147447735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Optical manipulation enables controlled assembly of colloidal particles, facilitating light-mediated interactions relevant to optically driven technologies. Most studies focus on isotropic plasmonic nanospheres, whereas controlled optical actuation of anisotropic nanoparticles such as gold nanorods (GNRs) remains underexplored. We demonstrate that GNRs confined in custom-designed dynamic optical traps exhibit cooperative behavior driven by optical binding, propulsion forces, torques, and near surface hydrodynamic interactions. These mechanisms enable the reversible formation of mobile optically bound (OB) GNR dimers in end-to-end configurations, with interparticle separations close to the trapping wavelength in the medium. The assemblies display strong anisotropic dynamics, including orientation-dependent propulsion and transport velocities up to four times higher than isolated GNRs. Dimer velocity varies by a factor of two depending on its alignment with the propulsion force. We investigate these dynamics using polygonal laser traps with tailored phase-gradient propulsion forces and fast orientation resolved optical tracking that enables studying in situ creation and optically guided motion of OB dimers. Combined experimental and theoretical analysis reveals how propulsion, confinement, and hydrodynamic conditions determine binding distance and transport behavior. The developed approach disentangles optical, thermal, and fluidic contributions, providing quantitative insight into light-driven anisotropic assemblies for nanoscale transport and adaptive colloidal systems.
{"title":"Optically Bound Rapid Plasmonic Nanorod Dimers: Anisotropic Dynamics Driven by Light-Fluidic Cooperation","authors":"José A. Rodrigo, Tatiana Alieva","doi":"10.1002/lpor.202502652","DOIUrl":"https://doi.org/10.1002/lpor.202502652","url":null,"abstract":"Optical manipulation enables controlled assembly of colloidal particles, facilitating light-mediated interactions relevant to optically driven technologies. Most studies focus on isotropic plasmonic nanospheres, whereas controlled optical actuation of anisotropic nanoparticles such as gold nanorods (GNRs) remains underexplored. We demonstrate that GNRs confined in custom-designed dynamic optical traps exhibit cooperative behavior driven by optical binding, propulsion forces, torques, and near surface hydrodynamic interactions. These mechanisms enable the reversible formation of mobile optically bound (OB) GNR dimers in end-to-end configurations, with interparticle separations close to the trapping wavelength in the medium. The assemblies display strong anisotropic dynamics, including orientation-dependent propulsion and transport velocities up to four times higher than isolated GNRs. Dimer velocity varies by a factor of two depending on its alignment with the propulsion force. We investigate these dynamics using polygonal laser traps with tailored phase-gradient propulsion forces and fast orientation resolved optical tracking that enables studying in situ creation and optically guided motion of OB dimers. Combined experimental and theoretical analysis reveals how propulsion, confinement, and hydrodynamic conditions determine binding distance and transport behavior. The developed approach disentangles optical, thermal, and fluidic contributions, providing quantitative insight into light-driven anisotropic assemblies for nanoscale transport and adaptive colloidal systems.","PeriodicalId":204,"journal":{"name":"Laser & Photonics Reviews","volume":"36 1","pages":""},"PeriodicalIF":11.0,"publicationDate":"2026-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147447751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Atmospheric turbulence‐induced wavefront aberrations significantly degrade performance in optical imaging and laser transmission systems. While adaptive optics (AO) offers compensation, conventional systems rely on wavefront sensors and guide stars, limiting their applicability in complex scenarios. Deep learning‐based approaches have emerged as promising alternatives but remain constrained by ill‐posedness and limited nonlinear representation capabilities. To overcome these challenges, we propose a novel dual‐plane nonlinear wavefront sensing method WaveKAN (WKAN) that operates without wavefront sensors or guide stars during inference and deployment. By capturing on‐focus and defocused images to constrain the solution space effectively, WKAN incorporates learnable activation functions and multi‐head self‐attention to enhance its ability to approximate the complex nonlinear mapping and model cross‐scale aberration features, respectively. Validated under various turbulence conditions using both spots under laser and extended objects under LED, WKAN demonstrates superior wavefront reconstruction accuracy (∼0.3 rad on average) and generalization capability compared to existing methods. In wavefront correction experiments, it significantly increased the Strehl ratio for point sources and restored distorted images to be clear for extended objects. These results confirm the potential of WKAN as a robust, guideless solution for broadening AO applications.
{"title":"Dual‐plane Intensity Nonlinear Wavefront Sensing via a Kolmogorov‐Arnold Network in Adaptive Optics","authors":"Haocheng Feng, Mengmeng Zhang, Zhenbo Ren, Ju Tang, Siqing Dai, Jiazhen Dou, Jianglei Di, Yuwen Qin","doi":"10.1002/lpor.202502441","DOIUrl":"https://doi.org/10.1002/lpor.202502441","url":null,"abstract":"Atmospheric turbulence‐induced wavefront aberrations significantly degrade performance in optical imaging and laser transmission systems. While adaptive optics (AO) offers compensation, conventional systems rely on wavefront sensors and guide stars, limiting their applicability in complex scenarios. Deep learning‐based approaches have emerged as promising alternatives but remain constrained by ill‐posedness and limited nonlinear representation capabilities. To overcome these challenges, we propose a novel dual‐plane nonlinear wavefront sensing method WaveKAN (WKAN) that operates without wavefront sensors or guide stars during inference and deployment. By capturing on‐focus and defocused images to constrain the solution space effectively, WKAN incorporates learnable activation functions and multi‐head self‐attention to enhance its ability to approximate the complex nonlinear mapping and model cross‐scale aberration features, respectively. Validated under various turbulence conditions using both spots under laser and extended objects under LED, WKAN demonstrates superior wavefront reconstruction accuracy (∼0.3 rad on average) and generalization capability compared to existing methods. In wavefront correction experiments, it significantly increased the Strehl ratio for point sources and restored distorted images to be clear for extended objects. These results confirm the potential of WKAN as a robust, guideless solution for broadening AO applications.","PeriodicalId":204,"journal":{"name":"Laser & Photonics Reviews","volume":"188 1","pages":""},"PeriodicalIF":11.0,"publicationDate":"2026-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147447753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emerging as essential tools for interrogating ultrafast nonequilibrium processes in quantum materials, ultrashort long-wavelength infrared (LWIR) pulses demand both high performance and fine characterization. In this letter, we present a high-repetition-rate (50 kHz) LWIR source with peak fields exceeding 14.8 MV cm−1 and spectral tunability (8–12.5 µm), generated via difference frequency generation scheme between a Yb:YAG pump laser and its parametrically amplified signal. Spatio-temporal coupling pulse characterization is realized through nonlinear optical imaging of time-resolved four-wave mixing between LWIR and near-infrared pulses in a 1-µm-thick silicon film. The multi-dimensional pulse characterization confirms the excellent temporal characteristics and high beam quality of the generated LWIR characterization pulses, providing a reliable foundation for applications in nonlinear spectroscopy, high-harmonic generation, and related fields.
作为研究量子材料中超快非平衡过程的重要工具，超短波长红外（LWIR）脉冲要求高性能和精细表征。在这封信中，我们提出了一个高重复率（50 kHz）的LWIR源，其峰值场超过14.8 MV cm - 1，光谱可调性（8-12.5µm），通过Yb:YAG泵浦激光器与其参数放大信号之间的差频产生方案产生。通过在1µm厚的硅薄膜中对LWIR和近红外脉冲进行时间分辨四波混频的非线性光学成像，实现了时空耦合脉冲表征。多维脉冲表征证实了生成的LWIR表征脉冲具有优良的时间特性和高光束质量，为非线性光谱、高谐波产生等领域的应用提供了可靠的基础。
{"title":"Generation and Spatio-Temporal Characterization of High-Repetition-Rate High-Peak-Power Long-Wave Infrared Laser Pulses","authors":"Hongyang Li, Liwei Song, Ye Tian, Ruxin Li","doi":"10.1002/lpor.202502847","DOIUrl":"https://doi.org/10.1002/lpor.202502847","url":null,"abstract":"Emerging as essential tools for interrogating ultrafast nonequilibrium processes in quantum materials, ultrashort long-wavelength infrared (LWIR) pulses demand both high performance and fine characterization. In this letter, we present a high-repetition-rate (50 kHz) LWIR source with peak fields exceeding 14.8 MV cm<sup>−1</sup> and spectral tunability (8–12.5 µm), generated via difference frequency generation scheme between a Yb:YAG pump laser and its parametrically amplified signal. Spatio-temporal coupling pulse characterization is realized through nonlinear optical imaging of time-resolved four-wave mixing between LWIR and near-infrared pulses in a 1-µm-thick silicon film. The multi-dimensional pulse characterization confirms the excellent temporal characteristics and high beam quality of the generated LWIR characterization pulses, providing a reliable foundation for applications in nonlinear spectroscopy, high-harmonic generation, and related fields.","PeriodicalId":204,"journal":{"name":"Laser & Photonics Reviews","volume":"15 1","pages":""},"PeriodicalIF":11.0,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147439927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jingtan Li, Shuyan Zhang, Hongxin Cai, Minjun Lee, Qunxi Dong, Naidi Sun, Bin Hu
Photoacoustic microscopy (PAM) enables structural and functional imaging at a microscopic level, playing a vital role in biomedical imaging. However, due to the limitations imposed by its scanning mechanism, PAM faces a trade-off between spatial resolution and imaging speed. While deep learning has improved PAM imaging speed, the image reconstruction performance of existing methods under high downsampling ratios still needs improvement. To address these limitations, we propose UPAM-KAN for undersampled PAM image reconstruction. This model is based on U-Net and integrates dedicated Kolmogorov–Arnold Network layers into the tokenized intermediate representations to construct its backbone network. Furthermore, three feature fusion extraction modules are proposed to enhance details, extract multi-scale features, and fuse shallow and deep features, respectively. Compared with the leading methods in undersampled PAM image reconstruction, UPAM-KAN achieves significant SSIM improvements of 8.322% and 2.692% on the Leaf Vein and Mouse Cerebrovascular datasets with only 1.4% of fully sampled pixels, respectively. Moreover, for functional reconstruction, the model pre-trained on public datasets achieves a 3.275% SSIM improvement in oxygen saturation at the 1/4 undersampling ratio. These results demonstrate that UPAM-KAN efficiently reconstructs both structural and functional information, offering insights for high-speed PAM imaging, dynamic vascular imaging and tissue functional monitoring.
{"title":"UPAM-KAN: A Method for Highly Undersampled Photoacoustic Microscopy Image Reconstruction","authors":"Jingtan Li, Shuyan Zhang, Hongxin Cai, Minjun Lee, Qunxi Dong, Naidi Sun, Bin Hu","doi":"10.1002/lpor.202500870","DOIUrl":"https://doi.org/10.1002/lpor.202500870","url":null,"abstract":"Photoacoustic microscopy (PAM) enables structural and functional imaging at a microscopic level, playing a vital role in biomedical imaging. However, due to the limitations imposed by its scanning mechanism, PAM faces a trade-off between spatial resolution and imaging speed. While deep learning has improved PAM imaging speed, the image reconstruction performance of existing methods under high downsampling ratios still needs improvement. To address these limitations, we propose UPAM-KAN for undersampled PAM image reconstruction. This model is based on U-Net and integrates dedicated Kolmogorov–Arnold Network layers into the tokenized intermediate representations to construct its backbone network. Furthermore, three feature fusion extraction modules are proposed to enhance details, extract multi-scale features, and fuse shallow and deep features, respectively. Compared with the leading methods in undersampled PAM image reconstruction, UPAM-KAN achieves significant SSIM improvements of 8.322% and 2.692% on the Leaf Vein and Mouse Cerebrovascular datasets with only 1.4% of fully sampled pixels, respectively. Moreover, for functional reconstruction, the model pre-trained on public datasets achieves a 3.275% SSIM improvement in oxygen saturation at the 1/4 undersampling ratio. These results demonstrate that UPAM-KAN efficiently reconstructs both structural and functional information, offering insights for high-speed PAM imaging, dynamic vascular imaging and tissue functional monitoring.","PeriodicalId":204,"journal":{"name":"Laser & Photonics Reviews","volume":"8 9-10 1","pages":""},"PeriodicalIF":11.0,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147439928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Full-wave numerical methods based on quasinormal modes (QNMs) offer valuable physical insights and computational efficiency for analyzing electromagnetic resonators. However, despite their advantages, many researchers in electromagnetism continue to favor real-frequency domain or time-domain approaches, often using finite element or finite-difference time-domain methods. This preference stems from various factors, including the perception that QNM theory is still developing or requires advanced mathematical tools from complex analysis. In this work, we combine numerical techniques with accurate approximations to simplify the computation of QNMs and enable ultrafast reconstructions using QNM expansions. The result is a new approach that is straightforwardly accessible to users familiar with real-frequency methods. We demonstrate the practicality of our approach through an open-source package [https://doi.org/10.5281/zenodo.18708748] implemented within a widely-used commercial photonics software.
{"title":"Rigorous Electromagnetic Quasinormal-Mode Method Made Easy for Users","authors":"Tong Wu, Philippe Lalanne","doi":"10.1002/lpor.202503045","DOIUrl":"https://doi.org/10.1002/lpor.202503045","url":null,"abstract":"Full-wave numerical methods based on quasinormal modes (QNMs) offer valuable physical insights and computational efficiency for analyzing electromagnetic resonators. However, despite their advantages, many researchers in electromagnetism continue to favor real-frequency domain or time-domain approaches, often using finite element or finite-difference time-domain methods. This preference stems from various factors, including the perception that QNM theory is still developing or requires advanced mathematical tools from complex analysis. In this work, we combine numerical techniques with accurate approximations to simplify the computation of QNMs and enable ultrafast reconstructions using QNM expansions. The result is a new approach that is straightforwardly accessible to users familiar with real-frequency methods. We demonstrate the practicality of our approach through an open-source package [https://doi.org/10.5281/zenodo.18708748] implemented within a widely-used commercial photonics software.","PeriodicalId":204,"journal":{"name":"Laser & Photonics Reviews","volume":"16 1","pages":""},"PeriodicalIF":11.0,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147439938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yuyu Zhang, Minghao An, Lixiong Lin, Jingyi Tian, Xiaorui Zheng
All-dielectric chiral metasurfaces, exploiting broken in-plane or out-of-plane symmetry to manipulate circular polarized light, offer immense potential applications for chiral emission, sensing, and nonlinear optics. While their low loss and multipolar resonances surpass metallic counterparts in efficiency and design freedom, realizing flexible design and full capabilities has been constrained by suitable high-precision 3D nanofabrication approaches. Here, we overcome this critical barrier by developing dielectric-compatible thermal scanning probe lithography (t-SPL) for high-index dielectric metasurfaces with grayscale topography and exceptional vertical resolution (<10 nm). Therefore, grayscale-engineered 3D chiral metasurfaces can be designed and precisely fabricated, showcasing the chiral quasi-bound states in the continuum with high quality factors (Q-factor>100) and giant intrinsic chirality. In addition, the resulting 3D geometries provide independent control over both chirality and Q-factor through tailored asymmetric parameters. By developing the dielectric-compatible t-SPL as a promising pathway for complex high-index all-dielectric 3D architectures, this work enables the practical realization of high-efficiency chiral optical devices—accelerating progress in integrated quantum photonics, ultrasensitive biosensing, and compact polarization-engineered systems.
{"title":"Dielectric-Compatible Thermal Scanning Probe Lithography for Grayscale Chiral Metasurfaces","authors":"Yuyu Zhang, Minghao An, Lixiong Lin, Jingyi Tian, Xiaorui Zheng","doi":"10.1002/lpor.202502717","DOIUrl":"https://doi.org/10.1002/lpor.202502717","url":null,"abstract":"All-dielectric chiral metasurfaces, exploiting broken in-plane or out-of-plane symmetry to manipulate circular polarized light, offer immense potential applications for chiral emission, sensing, and nonlinear optics. While their low loss and multipolar resonances surpass metallic counterparts in efficiency and design freedom, realizing flexible design and full capabilities has been constrained by suitable high-precision 3D nanofabrication approaches. Here, we overcome this critical barrier by developing dielectric-compatible thermal scanning probe lithography (t-SPL) for high-index dielectric metasurfaces with grayscale topography and exceptional vertical resolution (<10 nm). Therefore, grayscale-engineered 3D chiral metasurfaces can be designed and precisely fabricated, showcasing the chiral quasi-bound states in the continuum with high quality factors (Q-factor>100) and giant intrinsic chirality. In addition, the resulting 3D geometries provide independent control over both chirality and Q-factor through tailored asymmetric parameters. By developing the dielectric-compatible t-SPL as a promising pathway for complex high-index all-dielectric 3D architectures, this work enables the practical realization of high-efficiency chiral optical devices—accelerating progress in integrated quantum photonics, ultrasensitive biosensing, and compact polarization-engineered systems.","PeriodicalId":204,"journal":{"name":"Laser & Photonics Reviews","volume":"31 1","pages":""},"PeriodicalIF":11.0,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147439934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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