Scattering obscures information carried by waves by producing speckle patterns,posing a fundamental challenge across diverse fields,from microscopy to astronomy.Although machine learning has recently shown promise in ...Scattering obscures information carried by waves by producing speckle patterns,posing a fundamental challenge across diverse fields,from microscopy to astronomy.Although machine learning has recently shown promise in speckle analysis,existing approaches are hindered by their dependence on large,labeled datasets—a significant bottleneck in many real-world applications.Here,we introduce speckle unsupervised recognition and evaluation(SURE),a groundbreaking unsupervised learning strategy for speckle recognition that eliminates the need for labeled training data.SURE's distinctive feature lies in its ability to extract invariant features through advanced clustering algorithms to enable direct classification of high-level information from speckle patterns without prior knowledge.We demonstrate the transformative potential of this approach in two key applications:(1)a noninvasive glucose monitoring system that accurately tracks glucose concentrations over time without extensive calibration and(2)a high-throughput communication system using multimode fibers,achieving improved performance in dynamic environments.In addition,we showcase SURE's unprecedented capability to classify objects hidden behind obstacles using scattered light,further broadening its scope.This versatile approach opens new frontiers in biomedical diagnostics,quantum network decoupling,and remote sensing,unlocking a transformative new paradigm for extracting information from seemingly random optical patterns.展开更多
Nonreciprocal isolators enable unidirectional light propagation without back-reflection.Typical terahertz isolators require magnetic fields to break the time-reversal symmetry.Herein,we propose a nonmagnetic isolator ...Nonreciprocal isolators enable unidirectional light propagation without back-reflection.Typical terahertz isolators require magnetic fields to break the time-reversal symmetry.Herein,we propose a nonmagnetic isolator in the terahertz range based on nonreciprocal graphene plasmons operated in a reflection configuration.The bias voltage generates a drift current in graphene,which breaks the time-reversal symmetry and induces nonreciprocal reflection.The isolator device exhibited a high isolation exceeding 20 d B with an insertion loss of less than 3 d B.Moreover,the bandwidth wit isolation exceeding 20 d B can be broadened five times to 1.7 THz by tuning the carrier density.The indexes,including the isolation,insertion loss and bandwidth of the isolator,show a strong dependence on the drift velocity and mobility of graphene,as well as the air-gap thickness.Our study shows great potential in the burgeoning terahertz technology,where nonmagnetic and electrically tunable isolators are still lacking.展开更多
Holography is an essential technique of generating three-dimensional images.Recently,quantum holography with undetected photons(QHUP)has emerged as a groundbreaking method capable of capturing complex amplitude images...Holography is an essential technique of generating three-dimensional images.Recently,quantum holography with undetected photons(QHUP)has emerged as a groundbreaking method capable of capturing complex amplitude images.Despite its potential,the practical application of QHUP has been limited by susceptibility to phase disturbances,low interference visibility,and limited spatial resolution.Deep learning,recognized for its ability in processing complex data,holds significant promise in addressing these challenges.In this report,we present an ample advancement in QHUP achieved by harnessing the power of deep learning to extract images from single-shot holograms,resulting in vastly reduced noise and distortion,alongside a notable enhancement in spatial resolution.The proposed and demonstrated deep learning QHUP(DL-QHUP)methodology offers a transformative solution by delivering high-speed imaging,improved spatial resolution,and superior noise resilience,making it suitable for diverse applications across an array of research fields stretching from biomedical imaging to remote sensing.DL-QHUP signifies a crucial leap forward in the realm of holography,demonstrating its immense potential to revolutionize imaging capabilities and pave the way for advancements in various scientific disciplines.The integration of DL-QHUP promises to unlock new possibilities in imaging applications,transcending existing limitations and offering unparalleled performance in challenging environments.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.11934011,12074339,62075194,U21A6006,62202418,and U21B2004)the National Key Research and Development Program of China(Grant Nos.2019YFA0308100,2023YFB2806000,and 2022YFA1204700)+4 种基金the Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDB28000000)the Leading Innovation and Entrepreneurship Team in Zhejiang Province(Grant No.2020R01001)the Open Program of the State Key Laboratory of Advanced Optical Communication Systems and Networks at Shanghai Jiao Tong University(Grant No.2023GZKF024)the Fundamental Research Funds for the Central Universities,the Information Technology Center and State Key Lab of CAD&CG at the Zhejiang University,the Zhejiang Provincial Key Laboratory of Information Processing,Communication and Networking(IPCAN)the National Institutes of Health(NIH)(Grant Nos.R01GM127696,R01GM152633,R21GM142107,and R21CA269099)。
文摘Scattering obscures information carried by waves by producing speckle patterns,posing a fundamental challenge across diverse fields,from microscopy to astronomy.Although machine learning has recently shown promise in speckle analysis,existing approaches are hindered by their dependence on large,labeled datasets—a significant bottleneck in many real-world applications.Here,we introduce speckle unsupervised recognition and evaluation(SURE),a groundbreaking unsupervised learning strategy for speckle recognition that eliminates the need for labeled training data.SURE's distinctive feature lies in its ability to extract invariant features through advanced clustering algorithms to enable direct classification of high-level information from speckle patterns without prior knowledge.We demonstrate the transformative potential of this approach in two key applications:(1)a noninvasive glucose monitoring system that accurately tracks glucose concentrations over time without extensive calibration and(2)a high-throughput communication system using multimode fibers,achieving improved performance in dynamic environments.In addition,we showcase SURE's unprecedented capability to classify objects hidden behind obstacles using scattered light,further broadening its scope.This versatile approach opens new frontiers in biomedical diagnostics,quantum network decoupling,and remote sensing,unlocking a transformative new paradigm for extracting information from seemingly random optical patterns.
基金Supported by the National Natural Science Foundation of China(Grant Nos.11934011 and 12274365)National Key R&D Program of China(Grant Nos.2022YFA1402400 and 2022YFA1400043)+1 种基金Zhejiang Provincial Natural Science Foundation of China(Grant No.LR24A040001)Open project of Key Laboratory of Artificial Structures and Quantum Control(Ministry of Education)of Shanghai Jiao Tong University。
文摘Nonreciprocal isolators enable unidirectional light propagation without back-reflection.Typical terahertz isolators require magnetic fields to break the time-reversal symmetry.Herein,we propose a nonmagnetic isolator in the terahertz range based on nonreciprocal graphene plasmons operated in a reflection configuration.The bias voltage generates a drift current in graphene,which breaks the time-reversal symmetry and induces nonreciprocal reflection.The isolator device exhibited a high isolation exceeding 20 d B with an insertion loss of less than 3 d B.Moreover,the bandwidth wit isolation exceeding 20 d B can be broadened five times to 1.7 THz by tuning the carrier density.The indexes,including the isolation,insertion loss and bandwidth of the isolator,show a strong dependence on the drift velocity and mobility of graphene,as well as the air-gap thickness.Our study shows great potential in the burgeoning terahertz technology,where nonmagnetic and electrically tunable isolators are still lacking.
基金The National Natural Science Foundation of China(Grant No.11934011,62075194,U21A6006)The National Key Research and Development Program of China(Grant No.2019YFA0308100,2023YFB2806000,2022YFA1204700)+2 种基金The Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDB28000000)The Open Program of the State Key Laboratory of Advanced Optical Communication Systems and Networks at Shanghai Jiao Tong University(Grant No.2023GZKF024)The Fundamental Research Funds for the Central Universities.The Information Technology Center and State Key Lab of CAD&CG.
文摘Holography is an essential technique of generating three-dimensional images.Recently,quantum holography with undetected photons(QHUP)has emerged as a groundbreaking method capable of capturing complex amplitude images.Despite its potential,the practical application of QHUP has been limited by susceptibility to phase disturbances,low interference visibility,and limited spatial resolution.Deep learning,recognized for its ability in processing complex data,holds significant promise in addressing these challenges.In this report,we present an ample advancement in QHUP achieved by harnessing the power of deep learning to extract images from single-shot holograms,resulting in vastly reduced noise and distortion,alongside a notable enhancement in spatial resolution.The proposed and demonstrated deep learning QHUP(DL-QHUP)methodology offers a transformative solution by delivering high-speed imaging,improved spatial resolution,and superior noise resilience,making it suitable for diverse applications across an array of research fields stretching from biomedical imaging to remote sensing.DL-QHUP signifies a crucial leap forward in the realm of holography,demonstrating its immense potential to revolutionize imaging capabilities and pave the way for advancements in various scientific disciplines.The integration of DL-QHUP promises to unlock new possibilities in imaging applications,transcending existing limitations and offering unparalleled performance in challenging environments.
