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arXiv 2024年

作者： Arora, Arnav Midha, Siddhant Zyuzin, Alexander Hakonen, Pertti Muralidharan, Bhaskaran Department of Physics Indian Institute of Technology Roorkee India Department of Electrical Engineering Indian Institute of Technology Bombay Powai Mumbai400076 India Low Temperature Laboratory Department of Applied Physics Aalto University PO Box 15100 EspooFI-00076 Finland QTF Centre of Excellence Department of Applied Physics Aalto University PO Box 15100 EspooFI-00076 Finland Center of Excellence in Quantum Information Computing Science and Technology Indian Institute of Technology Bombay Powai Mumbai400076 India

Recent experiments on Cooper pair splitters using superconductor-quantum dot hybrids have embarked on creating entanglement in the solid-state, by engineering the sub-gap processes in the superconducting region. Using the thermoelectric Cooper pair splitter setup [Nat. Comm., 12, 21, (2021)] as a prototype, we present a comprehensive analysis of the fundamental components of the observed transport signal, aiming to critically clarify the operating regimes and confirm the nonlocal and nonclassical nature of correlations arising from crossed Andreev processes. By making a nexus with quantum discord, we identify operating points of nonlocal quantum correlations in the CPS device—information that cannot be extracted from the transport signal alone. A notable consequence of our analysis is the finding that contact-induced level broadening of the quantum dot’s discrete energy spectrum, along with its hybridization with the superconducting segment, can lead to shifted resonances in the crossed Andreev process as well as a parity reversal in the thermoelectric current. Our work thereby provides detailed insights into the gate voltage control of the quantum correlations in superconducting-hybrid Cooper pair splitters, revealing new avenues for harnessing quantum correlations in solid-state systems. © 2024, CC BY.

关键词： Semiconductor quantum dots

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Adaptive time-stepping and maximum-principle preserving Lagrangian schemes for gradient flows

arXiv

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arXiv 2025年

作者： Liu, Qianqian Chen, Wenbin Shen, Jie Cheng, Qing School of Mathematical Sciences Fudan University Shanghai200433 China Shanghai Key Laboratory for Contemporary Applied Mathematics School of Mathematical Sciences Fudan University Shanghai200433 China Eastern Institute of Technology Zhejiang Ningbo315200 China Key Laboratory of Intelligent Computing and Application Tongji University Ministry of Education Department of Mathematics Tongji University Shanghai200092 China

We develop in this paper an adaptive time-stepping approach for gradient flows with distinct treatments for conservative and non-conservative dynamics. For the non-conservative gradient flows in Lagrangian coordinates, we propose a modified formulation augmented by auxiliary terms to guarantee positivity of the determinant, and prove that the corresponding adaptive second-order Backward Difference Formulas (BDF2) scheme preserves energy stability and the maximum principle under the time-step ratio constraint 0 n ≤ rmax ≤ 32. On the other hand, for the conservative Wasserstein gradient flows in Lagrangian coordinates, we propose an adaptive BDF2 scheme which is shown to be energy dissipative, and positivity preserving under the time-step ratio constraint 0 n ≤ rmax ≤ 3+√217 in 1D and 0 n ≤ rmax ≤ 54 in 2D, respectively. We also present ample numerical simulations in 1D and 2D to validate the efficiency and accuracy of the proposed *** Codes 35K55, 35K65, 65M06, 65M12 Copyright © 2025, The Authors. All rights reserved.

关键词： Lagrange multipliers

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Intrinsic Dynamic Generation of Spin Polarization by Time-Varying Electric Field

arXiv

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arXiv 2024年

作者： Feng, Xukun Cao, Jin Zhang, Zhi-Fan Ang, Lay Kee Lai, Shen Jiang, Hua Xiao, Cong Yang, Shengyuan A. Singapore University of Technology and Design Singapore487372 Singapore Institute of Applied Physics and Materials Engineering University of Macau China Fudan University Shanghai200433 China Institute for Nanoelectronic Devices and Quantum Computing State Key Laboratory of Surface Physics Fudan University Shanghai200433 China

Electric control of spin in insulators is desired for low-consumption and ultrafast spintronics, but the underlying mechanism remains largely unexplored. Here, we propose an intrinsic effect of dynamic spin generation driven by time-varying electric field. In the intraband response regime, it can be nicely formulated as a Berry curvature effect and leads to two phenomena that are forbidden in the dc limit: linear spin generation in nonmagnetic insulators and intrinsic Néel spin-orbit torque in PT -symmetric antiferromagnetic insulators. These phenomena are driven by the time derivative of field rather than the field itself, and have a quantum origin in the first-order dynamic anomalous spin polarizability. Combined with first-principles calculations, we predict sizable effects driven by terahertz field in nonmagnetic monolayer Bi and in antiferromagnetic even-layer MnBi2Te4, which can be detected in experiment. Copyright © 2024, The Authors. All rights reserved.

关键词： Spin polarization

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CTGDiff: A Conditional Diffusion Model for Cardiotocography Signal Synthesis

CTGDiff: A Conditional Diffusion Model for Cardiotocography ...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Xiaoqing Li Pufan Cai Yu Lu Shijie Shi Liangkun Ma Xianghua Fu College of Big Data and Internet Shenzhen Technology University Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China Department of Surgery Yong Loo Lin School of Medicine National University of Singapore Singapore School of Applied Technology Shenzhen University Shenzhen China Department of Obstetrics and Gynecology Peking Union Medical College Hospital Beijing China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The analysis of Cardiotocography (CTG) signals is often hindered by challenges such as limited data availability and label imbalance, which can undermine the performance of deep learning models. To address these issues, we present CTGDiff, a novel conditional diffusion model designed for generating synthetic Fetal Heart Rate (FHR) and Uterine Contraction (UC) signals. CTGDiff leverages both Phase-Rectified Signal Averaging (PRSA) spectrograms and UC as conditioning inputs for FHR, and integrates time encoding, condition generation from PRSA features, and residual blocks with dilated convolutions to capture both temporal dynamics and long-range dependencies. Extensive experiments, both qualitative and quantitative, demonstrate the model’s ability to synthesize high-quality CTG signals. In comparison with GANs and image-based diffusion models, CTGDiff achieves superior signal fidelity and distribution similarity for FHR, as indicated by metrics such as a 0.004 maximum mean deviation (MMD), 0.646 percent root mean square difference (PRD), 3.951 relative entropy (RE), and 0.291 Frechet distance (FD). Expert evaluations confirm that the model can generate both normal and abnormal CTG signals with high accuracy, conditioned on specific input data. These results underscore the potential of diffusion models for a wide range of applications in biomedical time series analysis, including signal synthesis, imputation, and noise reduction.

关键词： Measurement Fetal heart rate Biological system modeling Time series analysis Diffusion models Data models Signal synthesis Cardiography Speech processing Spectrogram

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Multi-Photon Subtraction from Squeezed Light toward Full Quantum State Engineering

Multi-Photon Subtraction from Squeezed Light toward Full Qua...

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Quantum 2.0, QUANTUM 2024 in Quantum 2.0 Conference and Exhibition

作者： Endo, Mamoru Nomura, Takefumi Sonoyama, Tatsuki Takahashi, Kazuma Fukui, Kosuke Kashiwazaki, Takahiro Inoue, Asuka Umeki, Takeshi Takasu, Sachiko Hattori, Kaori Fukuda, Daiji Nehra, Rajveer Marek, Petr Filip, Radim Takase, Kan Asavanant, Warit Furusawa, Akira Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-8656 Japan Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Saitama Wako351-0198 Japan NTT Device Technology Labs. NTT Corporation 3-1 Morinosato Wakamiya Kanagawa Atsugi243-0198 Japan National Institute of Advanced Industrial Science and Technology Ibaraki Tsukuba305-8563 Japan AIST-UTokyo Advanced Operando-Measurement Technology Open Innovation Laboratory Ibaraki Tsukuba305-8563 Japan Department of Electrical and Computer Engineering University of Massachusetts-Amherst AmherstMA01003 United States Department of Physics University of Massachusetts-Amherst AmherstMA01003 United States Department of Optics Palacky University 17. listopadu 1192/12 Olomouc77146 Czech Republic

We have applied up to four annihilation operations to squeezed light by photon subtraction. The presence of negative values in the Wigner function for all states indicates the successful implementation of quantum mani... 详细信息

ISBN: (纸本)9781557525185

关键词： Squeezed light

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ExpliCareNEXT: Human-Centered Explainable AI Solutions for Nursing Care

ExpliCareNEXT: Human-Centered Explainable AI Solutions for N...

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Joint of the ACM Workshops at the International Conference on Intelligent User Interfaces 2025, IUI-WS 2025

作者： Hermann, Julia van Ledden, Sebastian Meske, Christian Löhrke, Enrico Naroska, Edwin Dimitrov, Todor Ölcer, Sabahat Dogangün, Aysegül Institute Positive Computing Ruhr West University of Applied Sciences Lützowstraße 5 Bottrop46236 Germany Institute of Work Science Ruhr University Bochum Wasserstraße 221 Bochum44799 Germany inhaus GmbH Grabenstraße 5 Duisburg47057 Germany Ambient Intelligence Laboratory Niederrhein University of Applied Sciences Reinarzstr. 49 Krefeld47805 Germany Anasoft Technology AG Querenburger Str. 38 Bochum44789 Germany Institute of Computer Science Ruhr West University of Applied Sciences Lützowstraße 5 Bottrop46236 Germany Department of Palliative Medicine University Medical Center Göttingen University of Göttingen Von-Siebold-Straße 3 Göttingen37075 Germany

The increasing demand for nursing care services, coupled with a persistent shortage of skilled caregivers, underscores the urgent need for innovative technological solutions. ExpliCareNEXT addresses this challenge by integrating explainable artificial intelligence (XAI) into caregiving workflows to enhance efficiency, transparency, and trust. The project applies participatory design methods to develop adaptive, human-centered AI systems that support caregivers in their daily tasks while ensuring interpretability and ease of use. Initial findings from field studies in institutional care settings reveal barriers to technology adoption, including high documentation burdens, language barriers, and data privacy concerns. These insights inform the system design, ensuring that AI-driven recommendations align with caregivers' workflows and information needs. Our paper presents the project's objectives and methodological approach, emphasizing interdisciplinary collaboration as key strategies for bridging the gap between technical innovation and practical application. Challenges are explored, highlighting the importance of participatory approaches in fostering trust and usability in safety-critical domains. © 2025 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Ambient intelligence

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Phase-field based lattice Boltzmann method for containerless freezing

arXiv

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arXiv 2024年

作者： Huang, Jiangxu Wang, Lei Chai, Zhenhua Shi, Baochang School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan430074 China School of Mathematics and Physics China University of Geosciences Wuhan430074 China Institute of Interdisciplinary Research for Mathematics and Applied Science Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan430074 China

In this paper, a phase-field based lattice Boltzmann (LB) method is proposed to simulate solid-liquid phase change phenomena in multiphase systems. The method couples the thermal properties of the solidification front with the dynamics of the droplet interface, which enables the description of the complex interfacial changes during solid-liquid phase change process. The volume expansion or shrinkage of the droplet caused by the change of density during phase change is represented by adding a mass source term to the continuum equation. We first test the developed LB method by the three-phase Stefan problem and the droplet solidification on a cold surface, and the numerical results are in good agreement with the analytical and experimental solutions. Then the LB method is used to study the solidification problem with bubbles. The results show that the model can accurately capture the effect of bubbles on the solidification process, which is in good agreement with the previous work. Finally, a parametric study is carried out to examine the influences of some physical parameters on the sessile droplet solidification, and it is found that the time of droplet solidification increases with the increase of droplet volume and contact angle. Copyright © 2024, The Authors. All rights reserved.

关键词： Freezing

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A Consistent and Conservative Axisymmetric Lattice Boltzmann Method for Multiphase Electro-Hydrodynamic Flows

SSRN

引用

SSRN 2024年

作者： Liu, Xi Chai, Zhenhua Shi, Baochang Yuan, Xiaolei School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan430074 China Institute of Interdisciplinary Research for Mathematics and Applied Science Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan430074 China College of Mathematics and Information Science Hebei University Baoding071002 China

In this paper, a consistent and conservative mathematical model is first developed for multiphase electro-hydrodynamic (EHD) flows, which has some distinct features in the volume conservation, the consistency of reduction, and the consistency of mass-momentum transport. Then a two-relaxation-time axisymmetric lattice Boltzmann (LB) method is proposed for multiphase EHD flows, and the present LB method consists of three LB models, which are used to solve the axisymmetric reduction-consistent and conservative Allen-Cahn equation for the multiphase field, the axisymmetric Poisson equation for the electric potential, and the axisymmetric consistent and conservative Navier-Stokes equations for the flow field. Owing to the reduction-consistent property, the present LB method can be used to handle a set of M (1≤M≤N) EHD fluids in N-phase system. To test the capacity of the LB method, the deformations of a single two-phase droplet and a ternary-phase compound droplet under a uniform electric field are considered. It is found that different from a single droplet with two deformation modes, the compound droplet has four deformation modes, and additionally, the effects of the electric strength, the conductivity ratio and the permittivity ratio on the compound droplet are also investigated. Finally, the compound droplet in the quaternary-phase system is also explored, and there are eight deformation modes that have not been reported in the available literature. © 2024, The Authors. All rights reserved.

关键词： Navier Stokes equations

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A Survey of Fault Tolerance in Cloud computing

A Survey of Fault Tolerance in Cloud Computing

引用

Systems, Advanced Technologies and Knowledge (ISSATK), International Symposium of

作者： Om Kolthoum Elhajjej Nouha Alyaoui Samia Dardouri Karim Chabir Research Laboratory Modeling Aanalysis Control of System (MACS) LR16ES22 National engineering school of Gabes (ENIG) University of Gabes Tunisia Computer Science and Telecommunications Department Laboratory of Modeling Analysis and Control of Systems (MACS) Higher Institute of Applied Sciences and Technology Zarroug Gafsa Gafsa University Tunisia Department of Computer Science College of Computing and Information Technology Shaqra University Saudi Arabia InnoV’COM Laboratory-Sup’Com University of Carthage Tunisia

ISBN: (数字)9798331540173

ISBN: (纸本)9798331540180

This paper is designed to provide a comprehensive overview of the latest developments in fault tolerance methods for cloud computing. Maintaining high availability and reliability of cloud environments requires fault tolerance. This paper explores fault tolerance in the context of cloud computing and discusses recent challenges and innovations in the field. Moreover, it examines the ongoing research efforts to improve fault-tolerance architectures. At the end of the paper, the paper presents system-level metrics that are relevant to fault tolerance.

关键词： Measurement Surveys Cloud computing Fault tolerance Technological innovation Scalability Fault tolerant systems Computer architecture Software Software reliability

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A Novel Explainable CNN Model for Screening COVID-19 on X-ray Images

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Computer Systems Science & Engineering 2023年第8期46卷 1789-1809页

作者： Hicham Moujahid Bouchaib Cherradi Oussama El Gannour Wamda Nagmeldin Abdelzahir Abdelmaboud Mohammed Al-Sarem Lhoussain Bahatti Faisal Saeed Mohammed Hadwan EEIS Laboratory ENSET of MohammediaHassan II University of CasablancaMohammedia28820Morocco STIE Team CRMEF Casablanca-SettatThe Provincial Section of El JadidaEl Jadida24000Morocco Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Information Systems King Khalid UniversityMuhayel Aseer61913Saudi Arabia College of Computer Science and Engineering Taibah UniversityMedina42353Saudi Arabia Department of Computer Science University of Sheba RegionMarib14400Yemen DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City UniversityBirminghamB47XGUK Department of Information Technology College of ComputerQassim UniversityBuraydah 51452Saudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaiz6803Yemen

Due to the rapid propagation characteristic of the Coronavirus(COVID-19)disease,manual diagnostic methods cannot handle the large number of infected individuals to prevent the spread of ***,new automated diagnostic methods have been brought on board,particularly methods based on artificial intelligence using different medical data such as X-ray *** imaging,for example,produces several image types that can be processed and analyzed by machine and deep learning methods.X-ray imaging materials widely exist in most hospitals and health institutes since they are affordable compared to other imaging *** this paper,we propose a novel Convolutional Neural Network(CNN)model(COV2Net)that can detect COVID-19 virus by analyzing the X-ray images of suspected *** model is trained on a dataset containing thousands of X-ray images collected from different *** model was tested and evaluated on an independent *** order to approve the performance of the proposed model,three CNN models namely Mobile-Net,Residential Energy Services Network(Res-Net),and Visual Geometry Group 16(VGG-16)have been implemented using transfer learning *** experiment consists of a multi-label classification task based on X-ray images for normal patients,patients infected by COVID-19 virus and other patients infected with *** proposed model is empowered with Gradient-weighted Class Activation Mapping(Grad-CAM)and Grad-Cam++techniques for a visual explanation and methodology debugging *** finding results show that the proposed model COV2Net outperforms the state-of-the-art methods.

关键词： Artificial intelligence intelligent diagnostic systems decisionmaking COVID-19 convolutional neural network

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