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Machine learning is attracting surging interest across nearly all scientific areas by enabling the analysis of large datasets and the extraction of scientific information from incomplete data. Data-driven science is rapidly growing,…

Applied Physics · Physics 2025-03-17 Sung Yun Lee , Do Hyung Cho , Chulho Jung , Daeho Sung , Daewoong Nam , Sangsoo Kim , Changyong Song

In powder diffraction data analysis, phase identification is the process of determining the crystalline phases in a sample using its characteristic Bragg peaks. For multiphasic spectra, we must also determine the relative weight fraction of…

Machine Learning · Computer Science 2022-10-21 Patrick Hosein , Jaimie Greasley

Coherent optical fibre networks are extremely sensitive to thermal, mechanical and acoustic noise, which requires elaborate schemes of phase stabilization with dedicated auxiliary lasers, multiplexers and photodetectors. This is…

We introduce deep learning technique to perform complete mode decomposition for few-mode optical fiber for the first time. Our goal is to learn a fast and accurate mapping from near-field beam profiles to the complete mode coefficients,…

Signal Processing · Electrical Eng. & Systems 2019-04-19 Yi An , Liangjin Huang , Jun Li , Jinyong Leng , Lijia Yang , Pu Zhou

{We report on an intensity-only and deep-learning based method for laser beam characterization that allows to predict the underlying optical field within milliseconds. A simple near-field / far-field camera setup enables online control of…

An innovative scheme is proposed for the dynamic control of phase in two-dimensional laser beam array. It is based on a simple neural network that predicts the complex field array from the intensity of the induced scattered pattern through…

Autonomous synthesis and characterization of inorganic materials requires the automatic and accurate analysis of X-ray diffraction spectra. For this task, we designed a probabilistic deep learning algorithm to identify complex multi-phase…

Materials Science · Physics 2021-05-27 Nathan J. Szymanski , Christopher J. Bartel , Yan Zeng , Qingsong Tu , Gerbrand Ceder

With the success of deep learning methods in many image processing tasks, deep learning approaches have also been introduced to the phase retrieval problem recently. These approaches are different from the traditional iterative optimization…

Computer Vision and Pattern Recognition · Computer Science 2022-07-29 Qiuliang Ye , Li-Wen Wang , Daniel P. K. Lun

We incorporate deep learning (DL) into coherent beam combining (CBC) systems for the first time, to the best of our knowledge. Using a well-trained convolutional neural network DL model, the phase error in CBC systems could be accurately…

Precise sensing and control of spatial mode content is essential for the performance of precision optical systems, particularly interferometric gravitational-wave detectors, where misalignment and mode mismatch can lead to significant…

Instrumentation and Methods for Astrophysics · Physics 2026-03-31 Liu Tao , Eleonora Capocasa , Yuhang Zhao , Jacques Ding , Isander Ahrend , Matteo Barsuglia

The performance of fiber laser systems has drastically increased over recent decades, which has opened up new industrial and scientific applications for this technology. However, currently a number of physical effects prevents further power…

Ultrafast lasers ($< 500$ fs) have enabled laser-matter interactions at intensities exceeding $10^{18} \rm{Wcm}^{-2}$ with only millijoules of laser energy. However, as pulse durations become shorter, larger spectral bandwidths are…

Deep neural networks have emerged as effective tools for computational imaging including quantitative phase microscopy of transparent samples. To reconstruct phase from intensity, current approaches rely on supervised learning with training…

Image and Video Processing · Electrical Eng. & Systems 2020-01-28 Emrah Bostan , Reinhard Heckel , Michael Chen , Michael Kellman , Laura Waller

Millimeter-wave communication has the potential to deliver orders of magnitude increases in mobile data rates. A key design challenge is to enable rapid beam alignment with phased arrays. Traditional millimeter-wave systems require a high…

Signal Processing · Electrical Eng. & Systems 2020-10-06 Han Yan , Benjamin W. Domae , Danijela Cabric

Phase retrieval, the problem of recovering lost phase information from measured intensity alone, is an inverse problem that is widely faced in various imaging modalities ranging from astronomy to nanoscale imaging. The current process of…

Image and Video Processing · Electrical Eng. & Systems 2024-06-12 Henry Chan , Youssef S. G. Nashed , Saugat Kandel , Stephan Hruszkewycz , Subramanian Sankaranarayanan , Ross J. Harder , Mathew J. Cherukara

Coherent beam combination is one promising way to overcome the power limit of one single laser. In this paper, we use a Multi-Plane Light Converter to combine 12 fibers at 1.03 micron with a phase locking setup. The overall loss measurement…

The multi-dithering method has been well verified in phase locking of polarization coherent combination experiment. However, it is hard to apply to low repetition frequency pulsed lasers, since there exists an overlap frequency domain…

Signal Processing · Electrical Eng. & Systems 2022-03-10 Jiali Zhang , Jie Cao , Qun Hao , Yang Cheng , Liquan Dong , Bin Han , Xuesheng Liu

Coherent optics has demonstrated significant potential as a viable solution for achieving 100 Gb/s and higher speeds in single-wavelength passive optical networks (PON). However, upstream burst-mode coherent detection is a major challenge…

Signal Processing · Electrical Eng. & Systems 2024-09-24 Yongxin Sun , Hexun Jiang , Yicheng Xu , Mengfan Fu , Yixiao Zhu , Lilin Yi , Weisheng Hu , Qunbi Zhuge

Huge overhead of beam training imposes a significant challenge in millimeter-wave (mmWave) wireless communications. To address this issue, in this paper, we propose a wide beam based training approach to calibrate the narrow beam direction…

Signal Processing · Electrical Eng. & Systems 2021-07-21 Ke Ma , Dongxuan He , Hancun Sun , Zhaocheng Wang , Sheng Chen

21-cm intensity mapping (IM) is a powerful technique to probe the large-scale distribution of neutral hydrogen (HI) and extract cosmological information such as the baryon acoustic oscillation feature. A key challenge lies in recovering the…

Cosmology and Nongalactic Astrophysics · Physics 2025-11-24 Zitong Wang , Feng Shi , Le Zhang , Yanming Liu , Xiaoping Li , Shulei Ni , Ming Jiang , Xiaofan Ma
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