Ernst Wittmann;Claudia Buerhop-Lutz;Savannah Bennett;Vincent Christlein;Jens Hauch;Christoph J. Brabec;Ian Marius Peters
{"title":"PV Polaris – Automated PV System Orientation Prediction","authors":"Ernst Wittmann;Claudia Buerhop-Lutz;Savannah Bennett;Vincent Christlein;Jens Hauch;Christoph J. Brabec;Ian Marius Peters","doi":"10.1109/JPHOT.2025.3568887","DOIUrl":"https://doi.org/10.1109/JPHOT.2025.3568887","url":null,"abstract":"The orientation of a photovoltaic system is an important parameter for power generation and yield predictions. Yet often, the real orientation is unknown. Measuring the orientation manually is time-consuming. This study introduces an automated Monte Carlo Search based algorithm called PV Polaris which is capable of predicting the systems orientation within 18 s, with uncertainties of less than 2° in tilt and 4° in azimuth. In terms of accuracy, PV Polaris outperforms other methods such as measurements with a tilt compensated compass or predictions from satellite images. Applicable at module, string and inverter levels, the algorithm only requires power monitoring data as well as an approximate coordinate as input. Additionally, the algorithm can operate inversely to estimate the system's coordinates based on a given orientation. By using this orientation prediction, it was possible to calculate the yearly yield loss due to non-ideal orientation. For photovoltaic systems we investigated, we found that yearly yield increases between 2.3% to 10.3% could be achieved if the PV systems orientation would be optimized.","PeriodicalId":13204,"journal":{"name":"IEEE Photonics Journal","volume":"17 3","pages":"1-7"},"PeriodicalIF":2.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10999083","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144255649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qi Xi;Binghe Ma;Zhiyong Tian;Ruofei Li;Yinan Wang;Zhibo Ma
{"title":"Micro-Fabricated Compact Extrinsic Fabry-Perot Sensor for In-Situ Harsh Environment Acoustic Measurement","authors":"Qi Xi;Binghe Ma;Zhiyong Tian;Ruofei Li;Yinan Wang;Zhibo Ma","doi":"10.1109/JPHOT.2025.3569540","DOIUrl":"https://doi.org/10.1109/JPHOT.2025.3569540","url":null,"abstract":"This paper presents a compact extrinsic Fabry-Perot acoustic sensor. The key component of this sensor is a SOI chip with acoustic sensing Si diaphragm of 5 mm diameter and <inline-formula><tex-math>$2,{rm{mu m}}$</tex-math></inline-formula> thickness, which is obtained by micro fabrication process. Acoustic calibration experiment indicates that the sensor exhibits a frequency response range over 100 Hz-20 kHz, and a sensitivity of <inline-formula><tex-math>${95},{rm{.73mV/Pa}}$</tex-math></inline-formula>. High temperature plane wave tube is established for experiment that simulates the acoustic field in harsh environment, indicating that the sensor is able to realize acoustic sensing with ambient temperature up to <inline-formula><tex-math>${589},^circ mathrm{C}$</tex-math></inline-formula>. The prospect of our proposed sensor is realizing multi-point, in-situ acoustic measurement in harsh environment of aerospace engine internal flow field, enabled by its batch fabrication process and high compactness as well as sensitivity, which we believe will shows great potential in significant industrial domains.","PeriodicalId":13204,"journal":{"name":"IEEE Photonics Journal","volume":"17 3","pages":"1-7"},"PeriodicalIF":2.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11002598","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Experimental Demonstration of Superimposed Data Transmission in Rolling Shutter Based Visible Light Communication","authors":"Masayuki Kinoshita;Ryuto Maeda;Koji Kamakura;Takaya Yamazato","doi":"10.1109/JPHOT.2025.3568891","DOIUrl":"https://doi.org/10.1109/JPHOT.2025.3568891","url":null,"abstract":"This study aims to provide adaptability to changes in the communication distance of rolling shutter based visible light communication (RS-VLC). A key issue in RS-VLC is the trade-off between the data rate and communication distance. To resolve this issue, we propose a superimposed data transmission method in which two sets of data, namely short- and long-range data, are superimposed and transmitted simultaneously. Short-range data are transmitted in long-bit sequences with a small number of iterations, whereas long-range data are transmitted in short-bit sequences with a large number of iterations. These two datasets can be separately decoded at the receiver by superimposing and transmitting them at different amplitudes. The proposed method can decode all the superimposed data at short ranges, thus suppressing data rate degradation. As the communication distance increases, the proposed method decodes only the available data, allowing for data reception over longer ranges, albeit at a lower data rate. We further extend the proposed method by adding a third set of data, namely mid-range data, for further flexibility in communication distance and data rate. The experimental results show that the proposed method achieves data reception over a longer distance (up to 150 cm) while suppressing throughput degradation at short-ranges, that is, it mitigates the trade-off between the data rate and communication distances compared to conventional <inline-formula><tex-math>$M$</tex-math></inline-formula>-ary pulse amplitude modulation systems.","PeriodicalId":13204,"journal":{"name":"IEEE Photonics Journal","volume":"17 3","pages":"1-11"},"PeriodicalIF":2.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10999103","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144123354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Songsheng Lin;Huanting Chen;Yin Zheng;Quanji Xie;Xuehua Shen;Huichuan Lin;Shuo Lin;Yan Li
{"title":"Forward Predicting Chromatic-Optical Parameters of the Mixed Light of White-Red Light-Emitting Diode Configurations Based on Deep Learning Algorithms","authors":"Songsheng Lin;Huanting Chen;Yin Zheng;Quanji Xie;Xuehua Shen;Huichuan Lin;Shuo Lin;Yan Li","doi":"10.1109/JPHOT.2025.3569079","DOIUrl":"https://doi.org/10.1109/JPHOT.2025.3569079","url":null,"abstract":"This paper presents a novel deep learning framework that integrates experimental measurements with advanced modeling techniques to predict key optical parameters, including luminous flux, correlated color temperature (CCT), and chromaticity coordinates of white-red light-emitting diodes (LED) configurations under diverse operating conditions. The heatsink temperature, white LED driving current, and red LED driving current were each varied systematically to generate a comprehensive set of 5,166 spectral power distribution (SPD) measurements. This dataset, partitioned into training (4,182 data sets) and testing (984 data sets) sets, encapsulates the complex physical mechanisms influencing LED performance, such as temperature-induced spectral shifts and current-dependent optical behavior. Four deep learning algorithms were evaluated. Each model was trained to reconstruct the SPD curves and predict the corresponding optical and chromatic parameters. Our results indicate that Long Short-Term Memory Network (LSTM), Convolutional Neural Network (CNN), and Autoencoder (AE) outperform Backpropagation Neural Network (BP-NN), with CNN achieving the highest accuracy in predicting SPD curves and LSTM achieving the highest accuracy in predicting the optical and chromatic parameters. Furthermore, By mimicking the effects of varying red phosphor ratios through independent control of red LED output, our approach can provide deeper insights into the underlying physical phenomena governing LED spectral behavior. This integrated methodology not only enhances our understanding of the interplay between operating conditions and LED performance but also offers a robust predictive tool for the design and optimization of next-generation LED lighting technologies.","PeriodicalId":13204,"journal":{"name":"IEEE Photonics Journal","volume":"17 3","pages":"1-7"},"PeriodicalIF":2.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10999086","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144125635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Reservoir Computing for Few-Mode Fiber Channel OSNR Monitoring in Deep Learning Frameworks","authors":"Jianjun Li;Tianfeng Zhao;Baojian Wu;Kun Qiu;Feng Wen","doi":"10.1109/JPHOT.2025.3550505","DOIUrl":"https://doi.org/10.1109/JPHOT.2025.3550505","url":null,"abstract":"This paper presents a novel optical performance monitoring (OPM) scheme based on reservoir computing (RC) and Resnet network for monitoring the optical signal-to-noise ratio (OSNR) of few-mode transmission channels, without the need for any demodulation process. By using 300 RC nodes, the number of floating-point operations (FLOPs) is reduced by 75%, with almost no change in prediction accuracy compared to a network without RC. In a system ranging from 0 to 30 dB, 40 simulation runs yield an OSNR prediction accuracy band around 0.9900. We also investigate the prediction accuracy when using different spectral information, with results showing that frequency-domain information effectively captures the characteristics of both signal and noise. Additionally, we examine the impact of different mode combinations on OSNR prediction accuracy and find that the prediction performance is nearly unaffected by the mode combination.","PeriodicalId":13204,"journal":{"name":"IEEE Photonics Journal","volume":"17 2","pages":"1-7"},"PeriodicalIF":2.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10923712","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143698239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ziting Pan;Yuting Li;Yijie Shen;Ziqiang Li;Guan Huang;Chao Geng;Xinyang Li
{"title":"Multi-Aperture Adaptive Fiber-Coupled Free-Space Optical Communication System: Scintillation Mitigation and Turbulence Compensation Experiment Based on Gamma-Gamma Channel Modeling","authors":"Ziting Pan;Yuting Li;Yijie Shen;Ziqiang Li;Guan Huang;Chao Geng;Xinyang Li","doi":"10.1109/JPHOT.2025.3550789","DOIUrl":"https://doi.org/10.1109/JPHOT.2025.3550789","url":null,"abstract":"Free-space optical communication is an effective alternative solution to address the “last mile” bottleneck in fiber-optic communication systems. However, its practical performance is significantly affected by phase perturbations and intensity scintillation induced by atmospheric turbulence effects. This paper proposes a multi-aperture adaptive fiber-coupled communication architecture, systematically investigating the optical transmission characteristics in turbulent channels through a combined approach of theoretical modeling and experimental validation. Utilizing the Gamma-Gamma turbulence channel model, quantitative analyses are conducted to elucidate the relationships between the scintillation index, the number of transmitting apertures, and the bit error rate. By establishing an outdoor 2.1 km experimental platform, we demonstrate that multi-aperture diversity transmission combined with closed-loop control reduces the scintillation index by 60% while achieving 10 Gbit/s error-free communication under weak turbulence conditions. Experimental results indicate that the proposed architecture enhances coupling power while maintaining high communication quality. Its modular design ensures high compatibility with mature fiber-optic communication components, providing a solution for constructing low-complexity, high-reliability hybrid optical communication systems in urban environments.","PeriodicalId":13204,"journal":{"name":"IEEE Photonics Journal","volume":"17 2","pages":"1-7"},"PeriodicalIF":2.1,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10923635","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Musa N. Hamza;Mohammad Tariqul Islam;Sunil Lavadiya;Iftikhar ud Din;Bruno Sanches;Slawomir Koziel;Syeda Iffat Naqvi;Abinash Panda;Mohammad Alibakhshikenari;B. Virdee;Md. Shabiul Islam
{"title":"Polarization-Insensitive Nano-Metamaterial Sensor With Near-Infrared μ and ϵ Negative Properties for Early Cancer Detection via Exosome Analysis (70 THz to 3 PHz)","authors":"Musa N. Hamza;Mohammad Tariqul Islam;Sunil Lavadiya;Iftikhar ud Din;Bruno Sanches;Slawomir Koziel;Syeda Iffat Naqvi;Abinash Panda;Mohammad Alibakhshikenari;B. Virdee;Md. Shabiul Islam","doi":"10.1109/JPHOT.2025.3549946","DOIUrl":"https://doi.org/10.1109/JPHOT.2025.3549946","url":null,"abstract":"Metamaterials (MTMs) have emerged as essential components in high-performance electromagnetic devices, including sensors and absorbers. This study presents a polarization-insensitive nano-metamaterial sensor with exceptional angular stability and a wide operating range of 70 THz to 3 PHz. The sensor achieves an average absorption rate of 97% across this range, making it highly suitable for applications in biomedical engineering. By integrating microwave imaging (MWI) techniques, the sensor can detect circulating cancer exosomes (CCEs) with high sensitivity, effectively distinguishing them from normal exosomes. Exhibiting double-negative MTM properties (negative permittivity and permeability) in the near-infrared (NIR) range (70 THz to 400 THz), the sensor enhances sensitivity for early cancer detection. A detailed analysis of its properties, including impedance (Z), phase, and S<sub>11</sub> parameters (real and imaginary components), demonstrates its superior performance. This non-invasive, label-free approach to detecting cancer biomarkers represents a significant step forward in advancing personalized healthcare.","PeriodicalId":13204,"journal":{"name":"IEEE Photonics Journal","volume":"17 2","pages":"1-15"},"PeriodicalIF":2.1,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10919043","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yi Feng;Ruiyuan Liu;Xinyue Chang;Xiangzhen Huang;Yuan He;Ning Li;Tiantian Zhou;Chujun Zhao
{"title":"Predicting the Evolution of the Supercontinuum Generation With CNN-LSTM Model","authors":"Yi Feng;Ruiyuan Liu;Xinyue Chang;Xiangzhen Huang;Yuan He;Ning Li;Tiantian Zhou;Chujun Zhao","doi":"10.1109/JPHOT.2025.3549825","DOIUrl":"https://doi.org/10.1109/JPHOT.2025.3549825","url":null,"abstract":"We propose a hybrid deep learning model, namely convolutional neural network–long short-term memory (CNN-LSTM) approach to investigate the evolution of the supercontinuum (SC) generation numerically. The hybrid model can use the CNN model to extract and map the local features of the sequence, followed by the LSTM to predict the overall trend of the SC generation. With the trained model by learning the propagation dynamics of the generalized nonlinear Schrödinger equation, the consistent outcome for the neural network predictions and numerical solutions has been obtained. The combined neural network can effectively solve the complex nonlinear propagation problems and maintain high accuracy compared with the LSTM, GRU neural networks for different incident power. The hybrid approach can facilitate the design and optimization of the spectral or temporal intensity distribution of SC generation, and may offer guidance for designing SC source for specific applications.","PeriodicalId":13204,"journal":{"name":"IEEE Photonics Journal","volume":"17 2","pages":"1-5"},"PeriodicalIF":2.1,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10919035","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143688090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Neutens;E. Mafakheri;X. Zheng;P. Helin;Z. Jafari;C. Lin;G. Jeevanandam;Nga P. Pham;S. Fan;C. Su;R. Jansen;P. Van Dorpe;N. Le Thomas;C. Haffner
{"title":"A 200 mm Wafer-Scale Al2O3 Photonics Waveguide Technology for UV and Visible Applications","authors":"P. Neutens;E. Mafakheri;X. Zheng;P. Helin;Z. Jafari;C. Lin;G. Jeevanandam;Nga P. Pham;S. Fan;C. Su;R. Jansen;P. Van Dorpe;N. Le Thomas;C. Haffner","doi":"10.1109/JPHOT.2025.3568162","DOIUrl":"https://doi.org/10.1109/JPHOT.2025.3568162","url":null,"abstract":"Low-loss, UV wavelength compatible Al<sub>2</sub>O<sub>3</sub> photonic waveguides have been fabricated in a 200 mm CMOS pilot line. The Al<sub>2</sub>O<sub>3</sub> waveguide layer optical properties and roughness were characterized by ellipsometry and AFM, respectively. Optical losses of the slab mode in the waveguide layer were studied by prism coupling. SiO<sub>2</sub>-cladded Al<sub>2</sub>O<sub>3</sub> waveguides were patterned on 200 mm wafers and propagation losses were measured at 266, 360, 450, 532 and 638 nm wavelengths. Wafer-level measurements for 360–638 nm show an average propagation loss below 0.6 dB/cm, while die-level measurements for 266 nm yield average propagation losses between 4.3 and 14.7 dB/cm. To study the dependence of the wave propagation on processing variations, large sets of Mach-Zehnder interferometers with varying arm lengths were measured at a wavelength of 360 nm, and the coherence length of the standard 450 nm wide and 110 nm high Al<sub>2</sub>O<sub>3</sub> waveguide was calculated to be longer than 2.2 mm.","PeriodicalId":13204,"journal":{"name":"IEEE Photonics Journal","volume":"17 3","pages":"1-6"},"PeriodicalIF":2.1,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10993371","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Foreground-Driven Contrastive Learning for Unsupervised Human Keypoint Detection","authors":"Shuxian Li;Hui Luo;Zhengwei Miao;Zhixing Wang;Qiliang Bao;Jianlin Zhang","doi":"10.1109/JPHOT.2025.3567754","DOIUrl":"https://doi.org/10.1109/JPHOT.2025.3567754","url":null,"abstract":"Human keypoint detection has significant value in computer vision tasks such as human-machine interaction. Recently, unsupervised human keypoint detection has become prevalent due to concerns about data privacy. Most existing methods are based on a reconstruction process that extracts appearance and pose information from transformed image pairs and spatially aligns them to obtain a reconstructed image for detection. However, these methods suffer from an issue because they reconstruct the entire image, which can easily lead to some keypoints being assigned to the background region. In this work, we believe that focusing on independent reconstruction and detection of the foreground region can mitigate the above issue. To this end, we propose a novel unsupervised human keypoint detection scheme to achieve reliable detection, which focuses on reconstructing and detecting keypoints in the foreground. Specifically, we first use a segmentor to separate the foreground and background of the image, for reconstruction and detection to be done only on the foreground region. Considering that keypoints vary due to changes in appearance and pose, we then introduce the contrastive loss to expand the feature space and enhance the network's robustness. Depending on the insertion position of the segmentor, we differentiate the proposed scheme into two versions: the effective version and the efficient version. Experimental results on popular datasets show that the proposed method exhibits superior performance. Specifically, on the BBC Pose dataset, the effective version achieves a <inline-formula><tex-math>$mathbf{7.0%}$</tex-math></inline-formula> performance improvement. The efficient version leads to a <inline-formula><tex-math>$mathbf{5.7%}$</tex-math></inline-formula> performance enhancement without sacrificing the inference speed.","PeriodicalId":13204,"journal":{"name":"IEEE Photonics Journal","volume":"17 3","pages":"1-14"},"PeriodicalIF":2.1,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10989733","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144125650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}