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Improved Heralded Single-Photon Source with a Photon-Number-Resolving Superconducting Nanowire Detector

Physical Review applied 2022年第6期18卷 064007-064007页

作者： Samantha I. Davis Andrew Mueller Raju Valivarthi Nikolai Lauk Lautaro Narvaez Boris Korzh Andrew D. Beyer Olmo Cerri Marco Colangelo Karl K. Berggren Matthew D. Shaw Si Xie Neil Sinclair Maria Spiropulu Division of Physics Mathematics and Astronomy California Institute of Technology 1200 E California Boulevard Pasadena California 91125 USA Alliance for Quantum Technologies (AQT) California Institute of Technology 1200 E California Boulevard Pasadena California 91125 USA Division of Engineering and Applied Science California Institute of Technology 1200 E California Boulevard Pasadena California 91125 USA Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive Pasadena California 91109 USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology 50 Vassar Street Cambridge Massachusetts 02139 USA Fermi National Accelerator Laboratory P.O. Box 500 Batavia Illinois 60510 USA John A. Paulson School of Engineering and Applied Sciences Harvard University 29 Oxford Street Cambridge Massachusetts 02138 USA

Deterministic generation of single photons is essential for many quantum information technologies. A bulk optical nonlinearity emitting a photon pair, where the measurement of one of the photons heralds the presence of the other, is commonly used with the caveat that the single-photon emission rate is constrained due to a trade-off between multiphoton events and pair emission rate. Using an efficient and low noise photon-number-resolving superconducting nanowire detector we herald, in real time, a single photon at telecommunication wavelength. We perform a second-order photon correlation g2(0) measurement of the signal mode conditioned on the measured photon number of the idler mode for various pump powers and demonstrate an improvement of a heralded single-photon source. We develop an analytical model using a phase-space formalism that encompasses all multiphoton effects and relevant imperfections, such as loss and multiple Schmidt modes. We perform a maximum-likelihood fit to test the agreement of the model to the data and extract the best-fit mean photon number μ of the pair source for each pump power. A maximum reduction of 0.118±0.012 in the photon g2(0) correlation function at μ=0.327±0.007 is obtained, indicating a strong suppression of multiphoton emissions. For a fixed g2(0)=7×10−3, we increase the single pair generation probability by 25%. Our experiment, built using fiber-coupled and off-the-shelf components, delineates a path to engineering ideal sources of single photons.

关键词： Optical quantum information processing Quantum coherence & coherence measures Quantum communication Quantum engineering Quantum networks Quantum protocols Quantum teleportation Single photon sources

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Heralding Single Photons from a Photon Pair Source using a Superconducting Nanowire Detector

Heralding Single Photons from a Photon Pair Source using a S...

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Quantum 2.0, QUANTUM 2022

作者： Davis, Samantha I. Mueller, Andrew Valivarthi, Raju Lauk, Nikolai Narvaez, Lautaro Korzh, Boris Beyer, Andrew D. Colangelo, Marco Berggren, Karl K. Shaw, Matthew D. Sinclair, Neil Spiropulu, Maria Division of Physics Mathematics and Astronomy California Institute of Technology 1200 E California Blvd. PasadenaCA91125 United States California Institute of Technology 1200 E California Blvd. PasadenaCA91125 United States Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Dr. PasadenaCA91109 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology 50 Vassar St. CambridgeMA02139 United States John A. Paulson School of Engineering and Applied Sciences Harvard University 29 Oxford St. CambridgeMA02138 United States

We experimentally demonstrate an improved heralded single photon source using a photon-number-resolving superconducting nanowire detector compared to that using a conventional bucket detector. This work delineates a p... 详细信息

ISBN: (纸本)9781957171111

关键词： Photons

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Heralding Single Photons using Photon-number-resolving Superconducting Nanowires

Heralding Single Photons using Photon-number-resolving Super...

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CLEO: QELS_Fundamental science, QELS 2022

ISBN: (纸本)9781557528209

We improve a single photon source based on spontaneous parametric down-conversion by heralding one of the output modes using a photon number resolving superconducting nanowire detector. We measure a reduced magnitude of the second order cross correlation of one of the output modes conditioned on detection of a single photon in the other mode. © Optica Publishing Group 2022, © 2022 The Author(s)

关键词： Photons

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Density currents and relative non-pluripolar products

arXiv

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arXiv 2020年

作者： Vu, Duc-Viet University of cologne Division of mathematics Department of mathematics and computer science Weyertal 86-90 KÖln50931 Germany Thang long institute of mathematics and applied sciences HANOI Viet Nam

Let X be a compact Kähler manifold of dimension n. For 1 ≤ j ≤ m, let Tj be a closed positive (1, 1)-current on X whose cohomology class is Kähler. Let T be a closed positive current of bi-degree (p, p) with m + p ≤ n. We prove that if T1, . . ., Tm are of T -relative full mass intersection, then the T -relative non-pluripolar product of T1, . . ., Tm is equal to the Dinh-Sibony product of T1, . . ., Tm, T . Copyright © 2020, The Authors. All rights reserved.

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Neuromodulated neural architectures with local error signals for memory-constrained online continual learning

arXiv

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arXiv 2020年

作者： Madireddy, Sandeep Yanguas-Gil, Angel Balaprakash, Prasanna Mathematics & Computer Science Division Argonne National Laboratory LemontIL United States Applied Materials Division Argonne National Laboratory LemontIL United States

The ability to learn continuously from an incoming data stream without catastrophic forgetting is critical for designing intelligent systems. Many existing approaches to continual learning rely on stochastic gradient descent and its variants. However, these algorithms have to implement various strategies, such as memory buffers or replay, to overcome well-known shortcomings of stochastic gradient descent methods in terms of stability, greed, and short-term memory. To that end, we develop a biologically-inspired light weight neural network architecture that incorporates local learning and neuromodulation to enable input processing over data streams and online learning. Next, we address the challenge of hyperparameter selection for tasks that are not known in advance by implementing transfer metalearning: using a Bayesian optimization to explore a design space spanning multiple local learning rules and their hyperparameters, we identify high performing configurations in classical single task online learning and we transfer them to continual learning tasks with task-similarity considerations. We demonstrate the efficacy of our approach on both single task and continual learning setting. For the single task learning setting, we demonstrate superior performance over other local learning approaches on the MNIST, Fashion MNIST, and CIFAR-10 datasets. Using high performing configurations metalearned in the single task learning setting, we achieve superior continual learning performance on Split-MNIST, and Split-CIFAR-10 data as compared with other memory-constrained learning approaches, and match that of the state-of-the-art memory-intensive replay-based approaches. Copyright © 2020, The Authors. All rights reserved.

关键词： Stochastic systems

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Brownian motion in a magneto Thermo-diffusion fluid flow over a semi-circular stretching surface

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Partial Differential Equations in applied mathematics 2024年 12卷

作者： Munjam, Shankar Rao Gopal, D. Kishan, N. Formanova, Shoira Karthik, K. Ahmad, Furqan Waqas, M. Gupta, Manish Khan, M. Ijaz School of Technology Woxsen University Telangana Hyderabad 502345 India Junior Lecturer in Mathematics Telangana Tribal Welfare Upgraded Residential Junior College for Boys Cheemanpally Telangana Nizamabad District 503165 India Department of Mathematics UCS Osmania University Telangana Hyderabad 500007 India Department of Chemistry and Its Teaching Methods Tashkent State Pedagogical University Tashkent Uzbekistan Department of Studies in Mathematics Davangere University Karnataka Davangere India Western Caspian University Baku Azerbaijan NUTECH School of Applied Sciences and Humanities National University of Technology Islamabad 44000 Pakistan Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon Division of Research and Development Lovely Professional University Phagwara India Department of Mechanical Engineering College of Engineering Prince Mohammad Bin Fahd University Al-Khobar Saudi Arabia

The current study explores the mass and heat transport analysis of a Casson liquid stream past a curved surface. The current model considers the effect of magnetic strength brought on by the strength of the applied uniform magnetic field. The significance of thermophoresis and Brownian motion are also taken into account using the Buongiorno nano-liquid model. The study of liquid flow over stretching sheets frequently addresses practical issues that have garnered significant attention from researchers due to their importance in various domains, including microfluidics, fibreglass production, manufacturing, transportation, metal extrusion, thermal insulation, glass production, paper manufacturing, and acoustic blasting. The governing partial differential equations (PDEs) are converted into ordinary differential equations (ODEs) using the similarity variables. These equations are numerically solved using the finite difference method (FDM). The concentration, temperature, and velocity graphs were produced by varying the different physical parameters. The upsurge in the magnetic parameter reduces the velocity profile. As the magnetic parameter increases, thermal and concentration profiles upsurge. The decrease in velocity profile can be seen as the Casson parameter rises. The intensification in values of thermophoretic parameter enhances the thermal and concentration profiles. The concentration and thermal profiles reduce as the curvature parameter upsurges. © 2024 The Author(s)

关键词： Casson fluid Curved stretching sheet Nanofluid Thermophoresis and Brownian motion

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Neuromorphic architecture optimization for task-specific dynamic learning 19

Neuromorphic architecture optimization for task-specific dyn...

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2019 International Conference on Neuromorphic Systems, ICONS 2019

作者： Madireddy, Sandeep Yanguas-Gil, Angel Balaprakash, Prasanna Mathematics and Computer Science Division Argonne National Laboratory LemontIL United States Applied Materials Division Argonne National Laboratory LemontIL United States

ISBN: (纸本)9781450376808

The ability to learn and adapt in real time is a central feature of biological systems. Neuromorphic architectures demonstrating such versatility can greatly enhance our ability to efficiently process information at the edge. A key challenge, however, is to understand which learning rules are best suited for specific tasks and how the relevant hyperparameters can be fine-tuned. In this work, we introduce a conceptual framework in which the learning process is integrated into the network itself. This allows us to cast meta-learning as a mathematical optimization problem. We employ DeepHyper, a scalable, asynchronous model-based search, to simultaneously optimize the choice of meta-learning rules and their hyperparameters. We demonstrate our approach with two different datasets, MNIST and FashionMNIST, using a network architecture inspired by the learning center of the insect brain. Our results show that optimal learning rules can be dataset-dependent even within similar tasks. This dependency demonstrates the importance of introducing versatility and flexibility in the learning algorithms. It also illuminates experimental findings in insect neuroscience that have shown a heterogeneity of learning rules within the insect mushroom body. © 2019 Association for Computing Machinery.

关键词： Optimization

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Pass-Efficient randomized lu algorithms for computing low-rank matrix approximation

arXiv

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arXiv 2020年

作者： Zhang, Bolong Mascagniy, Michael Department of Computer Science Florida State University FL United States Applied and Computational Mathematics Division NIST GaithersburgMD United States

Low-rank matrix approximation is extremely useful in the analysis of data that arises in scientific computing, engineering applications, and data science. However, as data sizes grow, traditional low-rank matrix approximation methods, such as singular value decomposition (SVD) and column pivoting QR decomposition (CPQR), are either prohibitively expensive or cannot provide sufficiently accurate results. A solution is to use randomized low-rank matrix approximation methods such as randomized SVD , and randomized LU decomposition on extremely large data sets. In this paper, we focus on the randomized LU decomposition method. First, we employ a reorthogonalization procedure to perform the power iteration of the existing randomized LU algorithm to compensate for the rounding errors caused by the power method. Then we propose a novel randomized LU algorithm, called PowerLU, for the fixed low-rank approximation problem. PowerLU allows for an arbitrary number of passes of the input matrix, v = 2. Recall that the existing randomized LU decomposition only allows an even number of passes. We prove the theoretical relationship between PowerLU and the existing randomized LU. Numerical experiments show that our proposed PowerLU is generally faster than the existing randomized LU decomposition, while remaining accurate. We also propose a version of PowerLU, called PowerLU FP, for the fixed precision low-rank matrix approximation problem. PowerLU FP is based on an efficient blocked adaptive rank determination Algorithm 4.1 proposed in this paper. We present numerical experiments that show that PowerLU FP can achieve almost the same accuracy and is faster than the randomized blocked QB algorithm by Martinsson and Voronin. We finally propose a single-pass algorithm based on LU factorization. Tests show that the accuracy of our single-pass algorithm is comparable with the existing single-pass *** Codes 65F99, 65C99 Copyright © 2020, The Authors. All rights reserved.

关键词： Singular value decomposition

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Multiregion Multiscale Image Segmentation with Anisotropic Diffusion 25th

Multiregion Multiscale Image Segmentation with Anisotropic D...

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25th International Conference on Pattern Recognition Workshops, ICPR 2020

作者： Prasath, V. B. Surya Thanh, Dang Ngoc Hoang Hai, Nguyen Hoang Dvoenko, Sergey Department of Electrical Engineering and Computer Science University of Cincinnati CincinnatiOH45221 United States Division of Biomedical Informatics Cincinnati Children’s Hospital Medical Center CincinnatiOH45229 United States Department of Biomedical Informatics College of Medicine University of Cincinnati CincinnatiOH45267 United States Department of Pediatrics University of Cincinnati College of Medicine CincinnatiOH45257 United States Department of Information Technology School of Business Information Technology University of Economics Ho Chi Minh City Ho Chi Minh City Viet Nam Department of Computer Science Vietnam-Korea University of Information and Communication Technology – The University of Danang Danang Viet Nam Department of Information Security Institute of Applied Mathematics and Computer Science Tula State University Tula city Russia

ISBN: (纸本)9783030688202

We present a multiregion image segmentation approach which utilizes multiscale anisotropic diffusion based scale spaces. By combining powerful edge preserving anisotropic diffusion smoothing with isolevel set linking and merging, we obtain coherent segments which are tracked across multiple scales. A hierarchical tree representation of the given input image with progressively simplified regions is used with intra-scale splitting and inter-scale merging for obtaining multiregion segmentations. Experimental results on natural and medical images indicate that multiregion, multiscale image segmentation (MMIS) approach obtains coherent segmentation results. © 2021, Springer Nature Switzerland AG.

关键词： Diffusion

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A Hybrid Statistical-Dynamical Downscaling of Air Temperature over Scandinavia Using the WRF Model

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Advances in Atmospheric sciences 2020年第1期37卷 57-74页

作者： Jianfeng WANG Ricardo M.FONSECA Kendall RUTLEDGE Javier MARTÍN-TORRES Jun YU Department of Mathematics and Mathematical Statistics UmeåUniversitySE 90187UmeåSweden Group of Atmospheric Science Division of Space TechnologyDepartment of Computer ScienceElectrical and Space EngineeringLuleåUniversity of TechnologySE 97187 LuleåSweden Novia University of Applied Sciences PO BOX 6FI-65201 VaasaFinland Instituto Andaluz de Ciencias de la Tierra 18100 GranadaSpain The Pheasant Memorial Laboratory for Geochemistry and Cosmochemistry Institute for Planetary MaterialsOkayama University at MisasaTottori 682-0193Japan

An accurate simulation of air temperature at local scales is crucial for the vast majority of weather and climate *** this work,a hybrid statistical–dynamical downscaling method and a high-resolution dynamical-only downscaling method are applied to daily mean,minimum and maximum air temperatures to investigate the quality of localscale estimates produced by *** two downscaling approaches are evaluated using station observation data obtained from the Finnish Meteorological Institute over a near-coastal region of western *** dynamical downscaling is performed with the Weather Research and Forecasting(WRF)model,and the statistical downscaling method implemented is the Cumulative Distribution Function-transform(CDF-t).The CDF-t is trained using 20 years of WRF-downscaled Climate Forecast System Reanalysis data over the region at a 3-km spatial resolution for the central month of each *** performance of the two methods is assessed qualitatively,by inspection of quantile-quantile plots,and quantitatively,through the Cramer-von Mises,mean absolute error,and root-mean-square error *** hybrid approach is found to provide significantly more skillful forecasts of the observed daily mean and maximum air temperatures than those of the dynamical-only downscaling(for all seasons).The hybrid method proves to be less computationally expensive,and also to give more skillful temperature forecasts(at least for the Finnish near-coastal region).

关键词： WRF air temperature Cumulative Distribution Function-transform hybrid statistical–dynamical downscaling,model evaluation Scandinavian Peninsula

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