IEEE Journal on Multiscale and Multiphysics Computational Techniques最新文献_第2页

Computational Electromagnetics Meets Spin Qubits: Controlling Noise Effects in Quantum Sensing and Computing 计算电磁学遇上自旋微ubits：控制量子传感和计算中的噪声效应

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2024-08-06 DOI: 10.1109/JMMCT.2024.3439531

Wenbo Sun;Sathwik Bharadwaj;Runwei Zhou;Dan Jiao;Zubin Jacob

{"title":"Computational Electromagnetics Meets Spin Qubits: Controlling Noise Effects in Quantum Sensing and Computing","authors":"Wenbo Sun;Sathwik Bharadwaj;Runwei Zhou;Dan Jiao;Zubin Jacob","doi":"10.1109/JMMCT.2024.3439531","DOIUrl":"https://doi.org/10.1109/JMMCT.2024.3439531","url":null,"abstract":"Solid-state spin qubits have emerged as promising platforms for quantum information. Despite extensive efforts in controlling noise in spin qubit quantum applications, one important but less controlled noise source is near-field electromagnetic fluctuations. Low-frequency (MHz and GHz) electromagnetic fluctuations are significantly enhanced near lossy material components in quantum applications, including metallic/superconducting gates necessary for controlling spin qubits in quantum computing devices and materials/nanostructures to be probed in quantum sensing. Although controlling this low-frequency electromagnetic fluctuation noise is crucial for improving the performance of quantum devices, current efforts are hindered by computational challenges. In this paper, we leverage advanced computational electromagnetics techniques, especially fast and accurate volume integral equation based solvers, to overcome the computational obstacle. We introduce a quantum computational electromagnetics framework to control low-frequency magnetic fluctuation noise and enhance spin qubit device performance. Our framework extends the application of computational electromagnetics to spin qubit quantum devices. Furthermore, we demonstrate the application of our framework in realistic quantum devices. Our work paves the way for device engineering to control magnetic fluctuations and improve the performance of spin qubit quantum sensing and computing.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142099794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multiphysics Model of Thomson-Coil Actuators With Closed-Form Inductance Formulas and Comprehensive Mechanical Interactions 采用闭式电感公式和综合机械相互作用的汤姆逊线圈致动器多物理场模型

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2024-07-18 DOI: 10.1109/JMMCT.2024.3430477

Zehui Sun;Jiazi Xu;Puyi Cui;Guoli Li;Zhong Chen;Guoyong Zhang;Qunjing Wang

引用次数: 0

Thermal-Mechanical-Electromagnetic Multiphysics Simulation of Satellite Phased Array Antenna Based on DGTD and FEM Method 基于 DGTD 和有限元方法的卫星相控阵天线热-机械-电磁多物理场仿真

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2024-07-16 DOI: 10.1109/JMMCT.2024.3428517

Huan Huan Zhang;Xin Yi Liu;Ying Liu;Zhan Chun Fan;Hai Long Du

引用次数: 0

Deep-Learning-Assisted Design of Polarization Conversion Metasurface With On-Demand Frequency Response and Ultra-Broadband Electromagnetic Scattering Reduction 按需频率响应和减少超宽带电磁散射的极化转换元表面的深度学习辅助设计

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2024-07-15 DOI: 10.1109/JMMCT.2024.3427629

Yuting Xiao;Ke Chen;Yijun Feng

{"title":"Deep-Learning-Assisted Design of Polarization Conversion Metasurface With On-Demand Frequency Response and Ultra-Broadband Electromagnetic Scattering Reduction","authors":"Yuting Xiao;Ke Chen;Yijun Feng","doi":"10.1109/JMMCT.2024.3427629","DOIUrl":"https://doi.org/10.1109/JMMCT.2024.3427629","url":null,"abstract":"Designing compacted electromagnetic (EM) polarization conversion (PC) devices with high efficiency and various frequency response has become crucial due to their irreplaceable role in many applications such as satellite communications, imaging and radar detection. Here, we propose a method that combines prior-knowledge with deep-learning intelligent algorithm to enable fast customization of reflective metasurface polarization converter with on-demand frequency responses. The PC meta-atoms are designed through a combination of forward and inverse convolutional neural networks (FCNN and ICNN). Instead of time-consuming full-wave simulations, the FCNN can accurately predict the PC spectral response, enabling rapid generation of large datasets. While the ICNN, in conjunction with these datasets, facilitates efficient design of the PC meta-atoms. The proposed methodology is demonstrated through the generation of various PC meta-atoms with on-demand specified frequency bands, such as broadband, dual-band or tri-band responses. As an application, a reflective metasurface composed of the ultra-broadband PC atom and its mirror atom obtained with ICNN is designed and optimized with genetic algorithm which achieves a measured ultra-broadband radar cross-section reduction from 8–37 GHz. Our approach offers a quick and intelligent design solution for reflective PC devices, and may be potential in radar, antenna and communication fields.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141965891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multiphysics Numerical Method for Modeling Josephson Traveling-Wave Parametric Amplifiers 约瑟夫森行波参数放大器建模的多物理场数值方法

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2024-07-15 DOI: 10.1109/JMMCT.2024.3428344

Samuel T. Elkin;Michael Haider;Thomas E. Roth

{"title":"Multiphysics Numerical Method for Modeling Josephson Traveling-Wave Parametric Amplifiers","authors":"Samuel T. Elkin;Michael Haider;Thomas E. Roth","doi":"10.1109/JMMCT.2024.3428344","DOIUrl":"https://doi.org/10.1109/JMMCT.2024.3428344","url":null,"abstract":"Josephson traveling-wave parametric amplifiers (JTWPAs) are wideband, ultralow-noise amplifiers used to enable the readout of superconducting qubits. While individual JTWPAs have achieved high performance, behavior between devices is inconsistent due to wide manufacturing tolerances. Amplifier designs could be modified to improve resilience towards variations in amplifier components; however, existing device models often rely on analytical techniques that typically fail to incorporate component variations. To begin addressing this issue, a 1D numerical method for modeling JTWPAs is introduced in this work. The method treats the Josephson junctions and transmission lines in an amplifier as coupled subsystems and can easily incorporate arbitrary parameter variations. We discretize the transmission line subsystem with a finite element time domain method and the Josephson junction subsystem with a finite difference method, with leap-frog time marching used to evolve the system in time. We validate our method by comparing the computed gain to an analytical model for a traditional JTWPA architecture and one with resonant phase matching. We then use our method to demonstrate the impact of variations in Josephson junctions and phase-matching resonators on amplification. In future work, the method will be adjusted to incorporate additional amplifier architectures and extended to a 3D full-wave approach.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141965524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sheet Element Approximation for Numerical Study of Current on Armature and Rail Interface 用于电枢和导轨界面电流数值研究的片元近似法

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2024-07-03 DOI: 10.1109/JMMCT.2024.3422609

Jinghan Xu;Shengguo Xia;Lixue Chen;Chengxian Li;Hongdan Yang

{"title":"Sheet Element Approximation for Numerical Study of Current on Armature and Rail Interface","authors":"Jinghan Xu;Shengguo Xia;Lixue Chen;Chengxian Li;Hongdan Yang","doi":"10.1109/JMMCT.2024.3422609","DOIUrl":"https://doi.org/10.1109/JMMCT.2024.3422609","url":null,"abstract":"The armature and rail (A/R) interface is an imperfect contact that is made at discrete asperities at the microscale resulting from high contact pressure. The current distribution of the interface differs significantly from the bulk behavior. In this paper, based on the contact layer model (CLM) and the Cooper-Mikic-Yoranovich model (CMYM), sheet element approximation and boundary conditions are proposed to analyze the electromagnetic properties of the A/R interface. Assuming zero gradients of the magnetic vector in the thickness direction, there are two ways for the approximation, which are mathematical approximation (MA) and physical approximation (PA). Results from both methods show high agreement, consistent with results from slit boundary conditions. Current distributions on both stationary and sliding A/R interfaces are numerically investigated. On the stationary interface, current diffuses from the edges to the central part of the real contact area, whereas on the sliding interface, current concentration occurs at the trailing edge due to the velocity skin effect (VSE). Furthermore, the contour of the current distribution aligns with the erosion pattern observed in experiments, validating the accuracy of the computational method.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141725682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Two-Dimensional Coupled Electrothermal Method Based on the Unstructured Transmission-Line Modelling Method for Lightning Protection Simulations 基于非结构化输电线路建模法的二维耦合电热法用于雷电防护模拟

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2024-07-02 DOI: 10.1109/JMMCT.2024.3421958

Kaiqi Yan;Ana Vukovic;Phillip Sewell

引用次数: 0

Electrostatic Boundary Integral Method for 3D Structures in a Layered Conducting Medium 层状导电介质中三维结构的静电边界积分法

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2024-06-19 DOI: 10.1109/JMMCT.2024.3416688

Stephen D. Gedney;Nastaran Hendijani;John C. Young;Robert J. Adams

引用次数: 0

LB-ADI: An Efficient Method for Transient Thermal Simulation of Integrated Chiplets and Packages LB-ADI：集成芯片和封装瞬态热模拟的高效方法

IF 2.3

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2024-04-09 DOI: 10.1109/JMMCT.2024.3386842

Jie Li;Min Tang;Lin-Sheng Wu;Liguo Jiang;Wenliang Dai;Junfa Mao

引用次数: 0

A Hybrid Electromagnetic Optimization Method Based on Physics-Informed Machine Learning 基于物理信息机器学习的混合电磁优化方法

IF 2.3

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2024-04-05 DOI: 10.1109/JMMCT.2024.3385451

Yanan Liu;Hongliang Li;Jian-Ming Jin

{"title":"A Hybrid Electromagnetic Optimization Method Based on Physics-Informed Machine Learning","authors":"Yanan Liu;Hongliang Li;Jian-Ming Jin","doi":"10.1109/JMMCT.2024.3385451","DOIUrl":"https://doi.org/10.1109/JMMCT.2024.3385451","url":null,"abstract":"In this article, we present an optimization method based on the hybridization of the genetic algorithm (GA) and gradient optimization (grad-opt) and facilitated by a physics-informed machine learning model. In the proposed method, the slow-but-global GA is used as a pre-screening tool to provide good initial values to the fast-but-local grad-opt. We introduce a robust metric to measure the goodness of the designs as starting points and use a set of control parameters to fine tune the optimization dynamics. We utilize the machine learning with analytic extension of eigenvalues (ML w/AEE) model to integrate the two pieces seamlessly and accelerate the optimization process by speeding up forward evaluation in GA and gradient calculation in grad-opt. We employ the divide-and-conquer strategy to further improve modeling efficiency and accelerate the design process and propose the use of a fusion module to allow for end-to-end gradient propagation. Two numerical examples are included to show the robustness and efficiency of the proposed method, compared with traditional approaches.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10493126","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140813892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0