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Measuring kinetic inductance and superfluid stiffness of two-dimensional superconductors using high-quality transmission-line resonators

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Physical Review Research 2024年第4期6卷 043245-043245页

作者： Mary Kreidel Xuanjing Chu Jesse Balgley Abhinandan Antony Nishchhal Verma Julian Ingham Leonardo Ranzani Raquel Queiroz Robert M. Westervelt School of Engineering and Applied Sciences Harvard University Cambridge Massachusetts 02138 USA Department of Applied Physics and Applied Mathematics Columbia University New York New York 10027 USA Department of Mechanical Engineering Columbia University New York New York 10027 USA Department of Physics Columbia University New York New York 10027 USA RTX BBN Technologies Quantum Engineering and Computing Group Cambridge Massachusetts 02138 USA Center for Computational Quantum Physics Flatiron Institute New York New York 10010 USA Department of Physics Harvard University Cambridge Massachusetts 02138 USA

The discovery of van der Waals superconductors in recent years has generated a lot of excitement for their potentially novel pairing mechanisms. However, their typical atomic-scale thickness and micrometer-scale lateral dimensions impose severe challenges to investigations of pairing symmetry by conventional methods. We demonstrate an improved technique that employs high-quality-factor superconducting resonators to measure the kinetic inductance—up to one part per million—and loss of a van der Waals superconductor. We analyze the equivalent circuit model to extract the kinetic inductance, superfluid stiffness, penetration depth, and ratio of imaginary and real parts of the complex conductivity. We validate the technique by measuring aluminum and finding excellent agreement in both the zero-temperature superconducting gap as well as the complex conductivity data when compared with BCS theory. We then demonstrate the utility of the technique by measuring the kinetic inductance of multilayered niobium diselenide and discuss the limits to the accuracy of our technique when the transition temperature of the sample, NbSe2 at 7.06 K, approaches our Nb probe resonator at 8.59 K. Our method will be useful for practitioners in the growing fields of superconducting physics, materials science, and quantum sensing, as a means of characterizing superconducting circuit components and studying pairing mechanisms of the novel superconducting states which arise in layered two-dimensional materials and heterostructures.

关键词： Quantum circuits Superconducting order parameter Superconductivity 2-dimensional systems Van der Waals systems Methods in superconductivity Microwave techniques

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Covariance-Based Joint Device Activity and Delay Detection in Asynchronous mMTC

arXiv

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arXiv 2021年

作者： Wang, Zhaorui Liu, Ya-Feng Liu, Liang The Department of Information Engineering The Chinese University of Hong Kong Hong Kong The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The Department of Electronic and Information Engineering The Hong Kong Polytechnic University Hong Kong

In this letter, we study the joint device activity and delay detection problem in asynchronous massive machine-type communications (mMTC), where all active devices asynchronously transmit their preassigned preamble sequences to the base station (BS) for device identification and delay detection. We first formulate this joint detection problem as a maximum likelihood estimation problem, which depends on the received signal only through its sample covariance, and then propose efficient coordinate descent type of algorithms to solve the formulated problem. Our proposed covariance-based approach is sharply different from the existing compressed sensing (CS) approach for the same problem. Numerical results show that our proposed covariance-based approach significantly outperforms the CS approach in terms of the detection performance since our proposed approach can make better use of the BS antennas than the CS approach. © 2021, CC BY.

关键词： Compressed sensing

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On the Power of Gradual Network Alignment Using Dual-Perception Similarities

arXiv

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arXiv 2022年

作者： Park, Jin-Duk Tran, Cong Shin, Won-Yong Cao, Xin The School of Mathematics and Computing Computational Science and Engineering Yonsei University Seoul03722 Korea Republic of The Faculty of Information Technology Posts and Telecommunications Institute of Technology Hanoi100000 Viet Nam Pohang37673 Korea Republic of The School of Computer Science and Engineering The University of New South Wales Sydney2052 Australia

Network alignment (NA) is the task of finding the correspondence of nodes between two networks based on the network structure and node attributes. Our study is motivated by the fact that, since most of existing NA methods have attempted to discover all node pairs at once, they do not harness information enriched through interim discovery of node correspondences to more accurately find the next correspondences during the node matching. To tackle this challenge, we propose Grad-Align, a new NA method that gradually discovers node pairs by making full use of node pairs exhibiting strong consistency, which are easy to be discovered in the early stage of gradual matching. Specifically, Grad-Align first generates node embeddings of the two networks based on graph neural networks along with our layer-wise reconstruction loss, a loss built upon capturing the first-order and higher-order neighborhood structures. Then, nodes are gradually aligned by computing dual-perception similarity measures including the multi-layer embedding similarity as well as the Tversky similarity, an asymmetric set similarity using the Tversky index applicable to networks with different scales. Additionally, we incorporate an edge augmentation module into Grad-Align to reinforce the structural consistency. Through comprehensive experiments using real-world and synthetic datasets, we empirically demonstrate that Grad-Align consistently outperforms state-of-the-art NA methods. © 2022, CC BY.

关键词： Embeddings

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Energy-preserving fully-discrete schemes for nonlinear stochastic wave equations with multiplicative noise

arXiv

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arXiv 2021年

作者： Hong, Jialin Hou, Baohui Sun, Liying Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China

In this paper, we focus on constructing numerical schemes preserving the averaged energy evolution law for nonlinear stochastic wave equations driven by multiplicative noise. We first apply the compact finite difference method and the interior penalty discontinuous Galerkin finite element method to discretize space variable and present two semi-discrete schemes, respectively. Then we make use of the discrete gradient method and the Pad'e approximation to propose efficient fully-discrete schemes. These semi-discrete and fully-discrete schemes are proved to preserve the discrete averaged energy evolution law. In particular, we also prove that the proposed fully-discrete schemes exactly inherit the averaged energy evolution law almost surely if the considered model is driven by additive noise. Numerical experiments are given to confirm theoretical findings. © 2021, CC BY.

关键词： Finite difference method

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Characterizing Faculty Online Learning Community Interactions Using Social Network Analysis

arXiv

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arXiv 2024年

作者： Bolger, Emily Nwobi, Marius Caballero, Marcos D. Department of Computational Mathematics Science and Engineering Michigan State University East LansingMI48824 United States Department of Biochemistry and Molecular Biology Michigan State University East LansingMI48824 United States Department of Physics and Astronomy CREATE for STEM Institute Michigan State University East LansingMI48824 United States Department of Physics Center for Computing in Science Education University of Oslo Oslo0315 Norway

Expanding on other work in the Physics Education Community, we apply Social Network Analysis to a Faculty Online Learning Community focused on facilitating the integration of computation into physics courses. The Partnership for Integration of Computation into Undergraduate Physics (PICUP) uses Slack as a mechanism for continued communication beyond face-to-face meetings. Through our analysis, we use networks to represent the Slack channels, identify lurkers, and use metrics to quantify pariticipation. Additionally, we use randomization techniques to understand how similar our metric values are to networks of similar size and distribution. We highlight the need for using the appropriate randomization model and assumption checking. We characterize participation amongst users in the network and provide potential reasonings for their actions. Copyright © 2024, The Authors. All rights reserved.

关键词： Social networking (online)

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Cross-Platform Multimodal Frogeye Leaf Spot Recognition and Classification: Advancing with Cutting-Edge CNN Technologies and Transfer Learning in Diverse Plant Species

Cross-Platform Multimodal Frogeye Leaf Spot Recognition and ...

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International Conference on Circuit, Power and computing Technologies (ICCPCT)

作者： G. Mohan R Usharani Vatsala Tomar Arthi A Suniti Kumar Kuriyal K.P. Yuvaraj Department of Mathematics K.S.Rangasamy College of Technology Tamil Nadu India Department of Computational Intelligence School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Chennai India Department of Botany School of Life Science & Technology IIMT University Meerut UP India Department of Information Technology Karpagam College of Engineering Coimbatore India Department of Botany Pt.L.M.S.Sridev Suman Uttarakhand University Campus Rishikesh India Department of Mechanical Engineering Sri Krishna College of Engineering and Technology Coimbatore India

ISBN: (数字)9798350372816

ISBN: (纸本)9798350372823

Frogeye Leaf Spot, a common agricultural disease, poses a significant threat to crop yields. Using multimodal data from different platforms successfully has been a hurdle for existing research in leaf spot detection. Using cutting-edge convolutional neural network (CNN) and transfer learning techniques, this research presents a Cross-Platform Multimodal Recognition system to solve this issue. With a recall of 0.88, F1-score of 0.90, accuracy of 0.91, and precision of 0.92, the suggested method demonstrates exceptional performance. Our accuracy is 6% higher, F1-score is 8% higher, and recall is 9% higher than the preceding state-of-the-art, according to comparisons with previous studies. Improved Frogeye Leaf Spot detection on many platforms is a direct result of our method's success in combining picture and sensor data. This study improves farmers' ability to identify diseases and provides a solid answer for precision agriculture. Our Cross-Platform Multimodal Recognition system has shown to be effective in enhancing agricultural disease recognition, and the shown advances highlight its potential influence on crop management tactics.

关键词： Precision agriculture Accuracy Plants (biology) Transfer learning Neural networks Solids Stability analysis

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On the relevance of lift force modelling in turbulent wall flows with small inertial particles

arXiv

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arXiv 2024年

作者： Gao, Wei Shi, Pengyu Parsani, Matteo Costa, Pedro Mechanical Engineering Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Applied Mathematics and Computational Science Computer Electrical and Mathematical Science and Engineering Division Extreme Computing Research Center King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Université de Toulouse CNRS Toulouse France Helmholtz-Zentrum Dresden – Rossendorf Institute of Fluid Dynamics Dresden01328 Germany Process & Energy Department TU Delft Leeghwaterstraat 39 Delft2628 CB Netherlands

In particle-laden turbulent wall flows, lift forces can influence the near-wall turbulence. This has been recently observed in particle-resolved simulations, which, however, are too expensive to be used in upscaled models. Instead, point-particle simulations have been the method of choice to simulate the dynamics of these flows during the last decades. While this approach is simpler, cheaper, and physically sound for small inertial particles in turbulence, some issues remain. In the present work, we address challenges associated with lift force modelling in turbulent wall flows and the impact of lift forces in the near-wall flow. We performed direct numerical simulations (DNS) of small inertial point particles in turbulent channel flow for fixed Stokes number and mass loading while varying the particle size. Our results show that the particle dynamics in the buffer region, causing the apparent particle-to-fluid slip velocity to vanish, raises major challenges for accurately modelling lift forces. While our results confirm that lift forces have little influence on particle dynamics for sufficiently small particle sizes, for inner-scaled diameters of order one and beyond, lift forces become quite important near the wall. The different particle dynamics under lift forces results in the modulation of streamwise momentum transport in the near-wall region. We analyze this lift-induced turbulence modulation for different lift force models, and the results indicate that realistic models are critical for particle-modelled simulations to correctly predict turbulence modulation by particles in the near-wall region. © 2024, CC BY.

关键词： Wall flow

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TAYLOR-HOOD LIKE FINITE ELEMENTS FOR NEARLY INCOMPRESSIBLE STRAIN GRADIENT ELASTICITY PROBLEMS

arXiv

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arXiv 2021年

作者： Liao, Yulei Ming, Pingbing Xu, Yun LSEC Institute of Computational Mathematics and Scientific/Engineering Computing AMSS Chinese Academy of Sciences No. 55 East Road Zhong-Guan-Cun Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing100088 China

We propose a family of mixed finite elements that are robust for the nearly incompressible strain gradient model, which is a fourth-order singular perturbed elliptic system. The element is similar to [C. Taylor and P. Hood, Comput. & Fluids, 1(1973), 73-100] in the Stokes flow. Using a uniform discrete B-B inequality for the mixed finite element pairs, we show the optimal rate of convergence that is robust in the incompressible limit. By a new regularity result that is uniform in both the materials parameter and the incompressibility, we prove the method converges with 1/2 order to the solution with strong boundary layer effects. Moreover, we estimate the convergence rate of the numerical solution to the unperturbed second-order elliptic system. Numerical results for both smooth solutions and the solutions with sharp layers confirm the theoretical *** Codes 65N15, 65N30 (Primary), 74K20 (Secondary) Copyright © 2021, The Authors. All rights reserved.

关键词： Elasticity

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Novel H (sym Curl)-conforming finite elements for the relaxed micromorphic sequence

arXiv

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arXiv 2023年

作者： Sky, Adam Neunteufel, Michael Lewintan, Peter Zilian, Andreas Neff, Patrizio Institute of Computational Engineering and Sciences Department of Engineering Faculty of Science Technology and Medicine University of Luxembourg 6 Avenue de la Fonte Esch-sur-AlzetteL-4362 Luxembourg Institute of Analysis and Scientific Computing Technische Universität Wien Wiedner Hauptstr. 8-10 Wien1040 Austria Nonlinear Analysis and Modelling Faculty of Mathematics Universität Duisburg-Essen Thea-Leymann Str. 9 Essen45127 Germany

In this work we construct novel H (sym Curl)-conforming finite elements for the recently introduced relaxed micromorphic sequence, which can be considered as the completion of the div Div-sequence with respect to the H (sym Curl)-space. The elements respect H (Curl)-regularity and their lowest order versions converge optimally for [H (sym Curl) \ H (Curl)]-fields. This work introduces a detailed construction, proofs of linear independence and conformity of the basis, and numerical examples. Further, we demonstrate an application to the computation of metamaterials with the relaxed micromorphic model. © 2023, CC BY-NC-ND.

关键词： Metamaterials

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Fast Algorithms for Monotone Lower Subsets of Kronecker Least Squares Problems

arXiv

引用

arXiv 2022年

作者： Malik, Osman Asif Xu, Yiming Cheng, Nuojin Becker, Stephen Doostan, Alireza Narayan, Akil Applied Mathematics & Computational Research Division Lawrence Berkeley National Laboratory United States Corporate Model Risk Wells Fargo United States Department of Applied Mathematics University of Colorado Boulder United States Smead Aerospace Engineering Sciences Department University of Colorado Boulder United States Scientific Computing and Imaging Institute Department of Mathematics University of Utah United States

Approximate solutions to large least squares problems can be computed efficiently using leverage score-based row-sketches, but directly computing the leverage scores, or sampling according to them with naive methods, still requires an expensive manipulation and processing of the design matrix. In this paper we develop efficient leverage score-based sampling methods for matrices with certain Kronecker product-type structure;in particular we consider matrices that are monotone lower column subsets of Kronecker product matrices. Our discussion is general, encompassing least squares problems on infinite domains, in which case matrices formally have infinitely many rows. We briefly survey leverage score-based sampling guarantees from the numerical linear algebra and approximation theory communities, and follow this with efficient algorithms for sampling when the design matrix has Kronecker-type structure. Our numerical examples confirm that sketches based on exact leverage score sampling for our class of structured matrices achieve superior residual compared to approximate leverage score sampling methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Least squares approximations

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