Advanced Photonics最新文献

{"title":"Deep reinforcement learning for quantum multiparameter estimation","authors":"V. Cimini, M. Valeri, E. Polino, S. Piacentini, F. Ceccarelli, G. Corrielli, N. Spagnolo, R. Osellame, F. Sciarrino","doi":"10.1117/1.AP.5.1.016005","DOIUrl":"https://doi.org/10.1117/1.AP.5.1.016005","url":null,"abstract":"Abstract. Estimation of physical quantities is at the core of most scientific research, and the use of quantum devices promises to enhance its performances. In real scenarios, it is fundamental to consider that resources are limited, and Bayesian adaptive estimation represents a powerful approach to efficiently allocate, during the estimation process, all the available resources. However, this framework relies on the precise knowledge of the system model, retrieved with a fine calibration, with results that are often computationally and experimentally demanding. We introduce a model-free and deep-learning-based approach to efficiently implement realistic Bayesian quantum metrology tasks accomplishing all the relevant challenges, without relying on any a priori knowledge of the system. To overcome this need, a neural network is trained directly on experimental data to learn the multiparameter Bayesian update. Then the system is set at its optimal working point through feedback provided by a reinforcement learning algorithm trained to reconstruct and enhance experiment heuristics of the investigated quantum sensor. Notably, we prove experimentally the achievement of higher estimation performances than standard methods, demonstrating the strength of the combination of these two black-box algorithms on an integrated photonic circuit. Our work represents an important step toward fully artificial intelligence-based quantum metrology.","PeriodicalId":33241,"journal":{"name":"Advanced Photonics","volume":"5 1","pages":"016005 - 016005"},"PeriodicalIF":17.3,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48962531","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}

{"title":"About the cover: Advanced Photonics Volume 4, Issue 5","authors":"Chang‐Ling Zou, C. Dong, Xiankai Sun","doi":"10.1117/1.AP.4.5.059901","DOIUrl":"https://doi.org/10.1117/1.AP.4.5.059901","url":null,"abstract":"Abstract. The article provides information about the image on the cover of Advanced Photonics, Volume 4, Issue 5.","PeriodicalId":33241,"journal":{"name":"Advanced Photonics","volume":"4 1","pages":"059901 - 059901"},"PeriodicalIF":17.3,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43560708","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}

{"title":"Hybrid brightfield and darkfield transport of intensity approach for high-throughput quantitative phase microscopy","authors":"Linpeng Lu, Jiaji Li, Ye Shu, Jiasong Sun, Jie Zhou, E. Lam, Qian Chen, C. Zuo","doi":"10.1117/1.AP.4.5.056002","DOIUrl":"https://doi.org/10.1117/1.AP.4.5.056002","url":null,"abstract":"Abstract. Transport of intensity equation (TIE) is a well-established non-interferometric phase retrieval approach that enables quantitative phase imaging (QPI) by simply measuring intensity images at multiple axially displaced planes. The advantage of a TIE-based QPI system is its compatibility with partially coherent illumination, which provides speckle-free imaging with resolution beyond the coherent diffraction limit. However, TIE is generally implemented with a brightfield (BF) configuration, and the maximum achievable imaging resolution is still limited to the incoherent diffraction limit (twice the coherent diffraction limit). It is desirable that TIE-related approaches can surpass this limit and achieve high-throughput [high-resolution and wide field of view (FOV)] QPI. We propose a hybrid BF and darkfield transport of intensity (HBDTI) approach for high-throughput quantitative phase microscopy. Two through-focus intensity stacks corresponding to BF and darkfield illuminations are acquired through a low-numerical-aperture (NA) objective lens. The high-resolution and large-FOV complex amplitude (both quantitative absorption and phase distributions) can then be synthesized based on an iterative phase retrieval algorithm taking the coherence model decomposition into account. The effectiveness of the proposed method is experimentally verified by the retrieval of the USAF resolution target and different types of biological cells. The experimental results demonstrate that the half-width imaging resolution can be improved from 1230 nm to 488 nm with 2.5  ×   expansion across a 4  ×   FOV of 7.19  mm2, corresponding to a 6.25  ×   increase in space-bandwidth product from ∼5 to ∼30.2  megapixels. In contrast to conventional TIE-based QPI methods where only BF illumination is used, the synthetic aperture process of HBDTI further incorporates darkfield illuminations to expand the accessible object frequency, thereby significantly extending the maximum available resolution from 2NA to ∼5NA with a ∼5  ×   promotion of the coherent diffraction limit. Given its capability for high-throughput QPI, the proposed HBDTI approach is expected to be adopted in biomedical fields, such as personalized genomics and cancer diagnostics.","PeriodicalId":33241,"journal":{"name":"Advanced Photonics","volume":"4 1","pages":"056002 - 056002"},"PeriodicalIF":17.3,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46313885","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}

{"title":"3.6 W compact all-fiber Pr3+-doped green laser at 521 nm","authors":"Jinhai Zou, Jinfen Hong, Zhuang Zhao, Qingyuan Li, Qiujun Ruan, Hang Wang, Yikun Bu, X. Guan, Min Zhou, Zhiyong Feng, Zhengqian Luo","doi":"10.1117/1.AP.4.5.056001","DOIUrl":"https://doi.org/10.1117/1.AP.4.5.056001","url":null,"abstract":"Abstract. Green semiconductor lasers are still undeveloped, so high-power green lasers have heavily relied on nonlinear frequency conversion of near-infrared lasers, precluding compact and low-cost green laser systems. Here, we report the first Watt-level all-fiber CW Pr3  +  -doped laser operating directly in the green spectral region, addressing the aforementioned difficulties. The compact all-fiber laser consists of a double-clad Pr3  +  -doped fluoride fiber, two homemade fiber dichroic mirrors at visible wavelengths, and a 443-nm fiber-pigtailed pump source. Benefitting from   >  10  MW  /  cm2 high damage intensity of our designed fiber dielectric mirror, the green laser can stably deliver 3.62-W of continuous-wave power at   ∼  521  nm with a slope efficiency of 20.9%. To the best of our knowledge, this is the largest output power directly from green fiber lasers, which is one order higher than previously reported. Moreover, these green all-fiber laser designs are optimized by using experiments and numerical simulations. Numerical results are in excellent agreement with our experimental results and show that the optimal gain fiber length, output mirror reflectivity, and doping level should be considered to obtain higher power and efficiency. This work may pave a path toward compact high-power green all-fiber lasers for applications in biomedicine, laser display, underwater detection, and spectroscopy.","PeriodicalId":33241,"journal":{"name":"Advanced Photonics","volume":"4 1","pages":"056001 - 056001"},"PeriodicalIF":17.3,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48049182","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}

{"title":"Massively parallel universal linear transformations using a wavelength-multiplexed diffractive optical network","authors":"Jingxi Li, Bijie Bai, Yilin Luo, Aydogan Ozcan","doi":"10.1117/1.AP.5.1.016003","DOIUrl":"https://doi.org/10.1117/1.AP.5.1.016003","url":null,"abstract":"Abstract. Large-scale linear operations are the cornerstone for performing complex computational tasks. Using optical computing to perform linear transformations offers potential advantages in terms of speed, parallelism, and scalability. Previously, the design of successive spatially engineered diffractive surfaces forming an optical network was demonstrated to perform statistical inference and compute an arbitrary complex-valued linear transformation using narrowband illumination. We report deep-learning-based design of a massively parallel broadband diffractive neural network for all-optically performing a large group of arbitrarily selected, complex-valued linear transformations between an input and output field of view, each with Ni and No pixels, respectively. This broadband diffractive processor is composed of Nw wavelength channels, each of which is uniquely assigned to a distinct target transformation; a large set of arbitrarily selected linear transformations can be individually performed through the same diffractive network at different illumination wavelengths, either simultaneously or sequentially (wavelength scanning). We demonstrate that such a broadband diffractive network, regardless of its material dispersion, can successfully approximate Nw unique complex-valued linear transforms with a negligible error when the number of diffractive neurons (N) in its design is ≥2NwNiNo. We further report that the spectral multiplexing capability can be increased by increasing N; our numerical analyses confirm these conclusions for Nw  >  180 and indicate that it can further increase to Nw  ∼  2000, depending on the upper bound of the approximation error. Massively parallel, wavelength-multiplexed diffractive networks will be useful for designing high-throughput intelligent machine-vision systems and hyperspectral processors that can perform statistical inference and analyze objects/scenes with unique spectral properties.","PeriodicalId":33241,"journal":{"name":"Advanced Photonics","volume":"5 1","pages":"016003 - 016003"},"PeriodicalIF":17.3,"publicationDate":"2022-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47952815","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}

{"title":"Physics-informed neural networks for diffraction tomography","authors":"Amirhossein Saba, C. Gigli, Ahmed B. Ayoub, D. Psaltis","doi":"10.1117/1.AP.4.6.066001","DOIUrl":"https://doi.org/10.1117/1.AP.4.6.066001","url":null,"abstract":"Abstract. We propose a physics-informed neural network (PINN) as the forward model for tomographic reconstructions of biological samples. We demonstrate that by training this network with the Helmholtz equation as a physical loss, we can predict the scattered field accurately. It will be shown that a pretrained network can be fine-tuned for different samples and used for solving the scattering problem much faster than other numerical solutions. We evaluate our methodology with numerical and experimental results. Our PINNs can be generalized for any forward and inverse scattering problem.","PeriodicalId":33241,"journal":{"name":"Advanced Photonics","volume":"4 1","pages":"066001 - 066001"},"PeriodicalIF":17.3,"publicationDate":"2022-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43779952","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}

{"title":"Topological transformation and free-space transport of photonic hopfions","authors":"Yijie Shen, Bing-qiang Yu, Hai-Jung Wu, Chun-Yu Li, Zhi-Han Zhu, A. Zayats","doi":"10.1117/1.ap.5.1.015001","DOIUrl":"https://doi.org/10.1117/1.ap.5.1.015001","url":null,"abstract":"Structured light fields embody strong spatial variations of polarisation, phase and amplitude. Understanding, characterization and exploitation of such fields can be achieved through their topological properties. Three-dimensional (3D) topological solitons, such as hopfions, are 3D localized continuous field configurations with nontrivial particle-like structures, that exhibit a host of important topologically protected properties. Here, we propose and demonstrate photonic counterparts of hopfions with exact characteristics of Hopf fibration, Hopf index, and Hopf mapping from real-space vector beams to homotopic hyperspheres representing polarisation states. We experimentally generate photonic hopfions with on-demand high-order Hopf indices and independently controlled topological textures, including N'eel-, Bloch-, and anti-skyrmionic types. We also demonstrate a robust free-space transport of photonic hopfions, thus, showing potential of hopfions for developing optical topological informatics and communications.","PeriodicalId":33241,"journal":{"name":"Advanced Photonics","volume":" ","pages":""},"PeriodicalIF":17.3,"publicationDate":"2022-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48067760","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}

{"title":"Nonlinear thermal emission and visible thermometry","authors":"Zhihao Zhou, Wei Liu, Hengzhe Yan, Xianfeng Chen, W. Wan","doi":"10.1117/1.ap.4.4.045001","DOIUrl":"https://doi.org/10.1117/1.ap.4.4.045001","url":null,"abstract":". The control of thermal emission is of great importance for emerging applications in energy conversion and thermometric sensing. Usually, thermal emission at ambient temperature is limited to the mid-to far-infrared, according to the linear theory of Planck ’ s law. We experimentally demonstrate a broadband nonlinear thermal emission in the visible-NIR spectrum within a quadradic nonlinear medium, which emits visible thermal radiation through a pump-driven nonlinear upconversion from its mid-IR components even at room temperature, unlike its linear counterpart which requires ultrahigh temperature. The broadband emission is enabled by the crucial random quasi-phase-matching condition in our nonlinear nanocrystal powders. Moreover, nonlinear thermal emission also permits visible thermometry using traditional optical cameras instead of thermal ones. This scheme paves the way to understand thermal radiation dynamics with nonlinearity in many fields, such as nonlinear heat transfer and nonlinear thermodynamics.","PeriodicalId":33241,"journal":{"name":"Advanced Photonics","volume":" ","pages":""},"PeriodicalIF":17.3,"publicationDate":"2022-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42441367","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}

{"title":"Silicon-based optoelectronics for general-purpose matrix computation: a review","authors":"Pengfei Xu, Zhiping Zhou","doi":"10.1117/1.AP.4.4.044001","DOIUrl":"https://doi.org/10.1117/1.AP.4.4.044001","url":null,"abstract":"Abstract. Conventional electronic processors, which are the mainstream and almost invincible hardware for computation, are approaching their limits in both computational power and energy efficiency, especially in large-scale matrix computation. By combining electronic, photonic, and optoelectronic devices and circuits together, silicon-based optoelectronic matrix computation has been demonstrating great capabilities and feasibilities. Matrix computation is one of the few general-purpose computations that have the potential to exceed the computation performance of digital logic circuits in energy efficiency, computational power, and latency. Moreover, electronic processors also suffer from the tremendous energy consumption of the digital transceiver circuits during high-capacity data interconnections. We review the recent progress in photonic matrix computation, including matrix-vector multiplication, convolution, and multiply–accumulate operations in artificial neural networks, quantum information processing, combinatorial optimization, and compressed sensing, with particular attention paid to energy consumption. We also summarize the advantages of silicon-based optoelectronic matrix computation in data interconnections and photonic-electronic integration over conventional optical computing processors. Looking toward the future of silicon-based optoelectronic matrix computations, we believe that silicon-based optoelectronics is a promising and comprehensive platform for disruptively improving general-purpose matrix computation performance in the post-Moore’s law era.","PeriodicalId":33241,"journal":{"name":"Advanced Photonics","volume":"4 1","pages":"044001 - 044001"},"PeriodicalIF":17.3,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49146798","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}

{"title":"Topology-empowered membrane devices for terahertz photonics","authors":"Quanlong Yang, Dongyang Wang, S. Kruk, Mingkai Liu, I. Kravchenko, Jiaguang Han, Y. Kivshar, I. Shadrivov","doi":"10.1117/1.AP.4.4.046002","DOIUrl":"https://doi.org/10.1117/1.AP.4.4.046002","url":null,"abstract":"Abstract. Control of terahertz waves offers a profound platform for next-generation sensing, imaging, and information communications. However, all conventional terahertz components and systems suffer from bulky design, sensitivity to imperfections, and transmission loss. We propose and experimentally demonstrate on-chip integration and miniaturization of topological devices, which may address many existing drawbacks of the terahertz technology. We design and fabricate topological devices based on valley-Hall photonic structures that can be employed for various integrated components of on-chip terahertz systems. We demonstrate valley-locked asymmetric energy flow and mode conversion with topological waveguide, multiport couplers, wave division, and whispering gallery mode resonators. Our devices are based on topological membrane metasurfaces, which are of great importance for developing on-chip photonics and bring many features into terahertz technology.","PeriodicalId":33241,"journal":{"name":"Advanced Photonics","volume":"4 1","pages":"046002 - 046002"},"PeriodicalIF":17.3,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44309293","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}