Pub Date : 2025-06-27DOI: 10.1109/JMMCT.2025.3583976
P. Agilandeswari;G. Thavasi Raja;R. Rajasekar;R. Parthasarathy
A novel deep learning-based reconfigurable and multifunctional Photonic Crystal Ring Resonator (PCRR) is designed with narrow bandwidth, low insertion loss and ultracompact size for lightwave communication and optical computing applications. The designed coupled nanoring resonator is used to realize four different functions of optical switch, narrow bandpass filter, encoder and XOR gate. The periodic structure of photonic bandgap frequency range is calculated by the Plane Wave Expansion (PWE) technique. The multifunctional nanoscale structure performance parameters of extinction ratio, quality factor and insertion loss are numerically analyzed by Finite-Difference-Time-Domain (FDTD) method. The deep learning algorithm of Long Short Term Memory- Neural Network (LSTM-NN) is used to predict the design parameters with low mean square error and less computation time of 50 seconds. The nanoring resonators is designed with high quality factor of 2566.83, high extinction ratio of 34.87 dB and ultracompact size of 179.20 μm2. Hence, this multifunctional platform is highly appropriate for photonic integrated circuits and optical computing system.
{"title":"Deep Learning-Based Prediction of Multifunctional Photonic Crystal Ring Resonator With Ultra High-Quality Factor","authors":"P. Agilandeswari;G. Thavasi Raja;R. Rajasekar;R. Parthasarathy","doi":"10.1109/JMMCT.2025.3583976","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3583976","url":null,"abstract":"A novel deep learning-based reconfigurable and multifunctional Photonic Crystal Ring Resonator (PCRR) is designed with narrow bandwidth, low insertion loss and ultracompact size for lightwave communication and optical computing applications. The designed coupled nanoring resonator is used to realize four different functions of optical switch, narrow bandpass filter, encoder and XOR gate. The periodic structure of photonic bandgap frequency range is calculated by the Plane Wave Expansion (PWE) technique. The multifunctional nanoscale structure performance parameters of extinction ratio, quality factor and insertion loss are numerically analyzed by Finite-Difference-Time-Domain (FDTD) method. The deep learning algorithm of Long Short Term Memory- Neural Network (LSTM-NN) is used to predict the design parameters with low mean square error and less computation time of 50 seconds. The nanoring resonators is designed with high quality factor of 2566.83, high extinction ratio of 34.87 dB and ultracompact size of 179.20 μm<sup>2</sup>. Hence, this multifunctional platform is highly appropriate for photonic integrated circuits and optical computing system.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"295-303"},"PeriodicalIF":1.8,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144606341","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}
This contribution reports a comprehensive investigation into the development and validation of optimized models for simulating the electronic properties of large-scale graphene-based geometric diodes. Our study incorporates unique features as, for example, a general treatment for the boundary conditions, that include arbitrary impedance constrains for the diode output-terminals. The observed diode-like rectification behavior has its physical origin to be an intrinsic property of in the nonlinear carrier transport partial differential equations with polarity-dependent coefficients in asymmetric geometries. While atomistic methods offer, in principle, high accuracy at the atomic scale, their computational cost renders them impractical for simulating devices with dimensions exceeding a few nanometers. To address this limitation, we have developed an improved drift-diffusion framework that captures the essential physics of charge transport in the non-ballistic limit. Through extensive numerical simulations and new proposed diode topologies, we have investigated the impact of geometric parameters and external bias on the device characteristics. Direct quantitative comparison of independent results, obtained assuming fully coherent and fully diffusive transport in four-terminal diodes, has also been reported. The present model can be effectively used to preliminarily compare different diode geometries and to design/optimize large multi-terminal structures based on graphene.
{"title":"Large-Area Geometric Diodes Based on Asymmetric and Nonlinear Transport in Patterned Graphene","authors":"Davide Mencarelli;Emiliano Laudadio;Heng Wang;Siti Nur Afifa Azman;Martino Aldrigo;Mircea Dragoman;Eleonora Pavoni;Elaheh Mohebbi;Luca Pierantoni","doi":"10.1109/JMMCT.2025.3583441","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3583441","url":null,"abstract":"This contribution reports a comprehensive investigation into the development and validation of optimized models for simulating the electronic properties of large-scale graphene-based geometric diodes. Our study incorporates unique features as, for example, a general treatment for the boundary conditions, that include arbitrary impedance constrains for the diode output-terminals. The observed diode-like rectification behavior has its physical origin to be an intrinsic property of in the nonlinear carrier transport partial differential equations with polarity-dependent coefficients in asymmetric geometries. While atomistic methods offer, in principle, high accuracy at the atomic scale, their computational cost renders them impractical for simulating devices with dimensions exceeding a few nanometers. To address this limitation, we have developed an improved drift-diffusion framework that captures the essential physics of charge transport in the non-ballistic limit. Through extensive numerical simulations and new proposed diode topologies, we have investigated the impact of geometric parameters and external bias on the device characteristics. Direct quantitative comparison of independent results, obtained assuming fully coherent and fully diffusive transport in four-terminal diodes, has also been reported. The present model can be effectively used to preliminarily compare different diode geometries and to design/optimize large multi-terminal structures based on graphene.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"315-323"},"PeriodicalIF":1.8,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11052628","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144640998","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}
Pub Date : 2025-06-13DOI: 10.1109/JMMCT.2025.3579349
Dohun Lee;Ahmad Ramadoni;Jaewook Lee
This study presents a numerical homogenization model to predict the effective nonlinear behavior of highly heterogeneous electropermanent magnet (EPM) composites. EPM composites consist of periodic microstructures composed of both soft and hard ferromagnetic materials (i.e., iron and permanent magnets). EPM composites possess unique ability to self-generate magnetic fields while adjusting them using external current, making them promising for use in electromechanical devices. However, direct numerical analysis of EPM composite structures requires huge computational costs, particularly in nonlinear ranges where electromechanical devices typically operate. This challenge can be alleviated through multiscale analysis using homogenization method. The developed homogenization model is constructed using the energy-based approach, assuming magnetic energy equivalence between heterogeneous and homogeneous media. Specifically, the effective B-H curve of EPM composite is computed by interpolating B-H pairs obtained by solving cell problems through finite element analysis. To validate the proposed homogenization model, three numerical examples including an actuator and a magnetic bearing, are investigated. In each example, the magnetic field distribution, magnetic energy, or magnetic force, along with computational time, of actual EPM heterogeneous structures are compared with those of equivalent structures having homogeneous effective B-H curve. These comparisons confirm the accuracy and computational efficiency of the developed numerical homogenization model.
{"title":"Numerical Homogenization for Nonlinear Multiscale Analysis of Electropermanent Magnet Composites","authors":"Dohun Lee;Ahmad Ramadoni;Jaewook Lee","doi":"10.1109/JMMCT.2025.3579349","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3579349","url":null,"abstract":"This study presents a numerical homogenization model to predict the effective nonlinear behavior of highly heterogeneous electropermanent magnet (EPM) composites. EPM composites consist of periodic microstructures composed of both soft and hard ferromagnetic materials (i.e., iron and permanent magnets). EPM composites possess unique ability to self-generate magnetic fields while adjusting them using external current, making them promising for use in electromechanical devices. However, direct numerical analysis of EPM composite structures requires huge computational costs, particularly in nonlinear ranges where electromechanical devices typically operate. This challenge can be alleviated through multiscale analysis using homogenization method. The developed homogenization model is constructed using the energy-based approach, assuming magnetic energy equivalence between heterogeneous and homogeneous media. Specifically, the effective B-H curve of EPM composite is computed by interpolating B-H pairs obtained by solving cell problems through finite element analysis. To validate the proposed homogenization model, three numerical examples including an actuator and a magnetic bearing, are investigated. In each example, the magnetic field distribution, magnetic energy, or magnetic force, along with computational time, of actual EPM heterogeneous structures are compared with those of equivalent structures having homogeneous effective B-H curve. These comparisons confirm the accuracy and computational efficiency of the developed numerical homogenization model.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"271-282"},"PeriodicalIF":1.8,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144367021","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}
The simulation of carrier transport in power electronic devices imposes stringent requirements on numerical stability, confining the previous methods to low-order schemes. To address this issue, a stabilized higher-order hybridized discontinuous Galerkin method (S-HDG) is proposed, where we decouple the exponentially varying carrier density from the differential operator and project it onto a lower-dimensional equation. Based on the numerical jumps as indicator, an adaptive artificial diffusion term is introduced to dynamically control oscillatory errors and over diffusion during the iterations for solving nonlinear equations. We validate the proposed method to abrupt junction models, demonstrating its high-order accuracy and robustness against severe mesh skewness and curvature. Furthermore, we apply the method to lateral double-diffused MOSFET (LDMOS), a class of typical power electronic devices, achieving good agreement with the industrial-standard FVSG solver in simulating electrical parameters. Notably, our method can offer higher-order convergence and better compatibility with unstructured meshes.
{"title":"A Higher-Order Stabilized Hybridized Discontinuous Galerkin Method for Simulating Semiconductor Devices","authors":"Nian-En Zhang;Dongyan Zhao;Haoqiang Feng;Yin-Da Wang;Yanning Chen;Qi-Chao Wang;Zheng-Wei Du;Yingzong Liang;Fang Liu;Hao Xie;Qiwei Zhan;Wen-Yan Yin","doi":"10.1109/JMMCT.2025.3575845","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3575845","url":null,"abstract":"The simulation of carrier transport in power electronic devices imposes stringent requirements on numerical stability, confining the previous methods to low-order schemes. To address this issue, a stabilized higher-order hybridized discontinuous Galerkin method (S-HDG) is proposed, where we decouple the exponentially varying carrier density from the differential operator and project it onto a lower-dimensional equation. Based on the numerical jumps as indicator, an adaptive artificial diffusion term is introduced to dynamically control oscillatory errors and over diffusion during the iterations for solving nonlinear equations. We validate the proposed method to abrupt junction models, demonstrating its high-order accuracy and robustness against severe mesh skewness and curvature. Furthermore, we apply the method to lateral double-diffused MOSFET (LDMOS), a class of typical power electronic devices, achieving good agreement with the industrial-standard FVSG solver in simulating electrical parameters. Notably, our method can offer higher-order convergence and better compatibility with unstructured meshes.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"283-294"},"PeriodicalIF":1.8,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524412","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}
Pub Date : 2025-04-07DOI: 10.1109/JMMCT.2025.3558662
Nikolas Hadjiantoni;Dou Feng;Miguel Navarro-Cía;Stephen M. Hanham
Electromagnetic topological optimization holds the promise of the fully automated design of electromagnetic structures such as antennas, waveguides, metasurfaces and metamaterials; however, it often yields designs that are incompatible with fabrication processes. In this work, we describe a topological optimization framework that combines structural finite element analysis and electromagnetic finite-difference time-domain simulation to realize fabricable structures which meet specified electromagnetic design objectives. As a demonstration, the framework is applied towards the design of G-band low-profile leaky lens antennas suitable for future 6G communication applications. The 5$lambda _{0}$ radius, 2$lambda _{0}$ thick leaky lens antenna is compatible with stereolithography 3D printing and displays a realized gain of 23 dBi at 0.2 THz with a low side-lobe level of −20 dB. We foresee the proposed framework being applicable to a wide range of electromagnetic design problems intended for fabrication using additive manufacturing techniques.
{"title":"Topological Optimization Framework for the Automated Design of 3D Printable THz Lens Antennas","authors":"Nikolas Hadjiantoni;Dou Feng;Miguel Navarro-Cía;Stephen M. Hanham","doi":"10.1109/JMMCT.2025.3558662","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3558662","url":null,"abstract":"Electromagnetic topological optimization holds the promise of the fully automated design of electromagnetic structures such as antennas, waveguides, metasurfaces and metamaterials; however, it often yields designs that are incompatible with fabrication processes. In this work, we describe a topological optimization framework that combines structural finite element analysis and electromagnetic finite-difference time-domain simulation to realize fabricable structures which meet specified electromagnetic design objectives. As a demonstration, the framework is applied towards the design of G-band low-profile leaky lens antennas suitable for future 6G communication applications. The 5<inline-formula><tex-math>$lambda _{0}$</tex-math></inline-formula> radius, 2<inline-formula><tex-math>$lambda _{0}$</tex-math></inline-formula> thick leaky lens antenna is compatible with stereolithography 3D printing and displays a realized gain of 23 dBi at 0.2 THz with a low side-lobe level of −20 dB. We foresee the proposed framework being applicable to a wide range of electromagnetic design problems intended for fabrication using additive manufacturing techniques.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"218-226"},"PeriodicalIF":1.8,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143900506","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}
Conventionally, the large sparse matrix equation ($Ax=b$) generated by the Laguerre-FDTD method is computed using direct matrix solvers, which is often numerically expensive and computationally slow. In this work, we demonstrate an innovative approach to replace direct matrix solver with an iterative algorithm for the Laguerre-FDTD method. A novel preconditioner, specifically targeted to improve the convergence rate of biconjugate gradient stabilized solver (BiCGSTAB), is derived and implemented in the Laguerre-FDTD method. Compared with the classical Jacobi preconditioner, the proposed preconditioner achieves on average an improvement of more than 1.3× in the convergence rate. To further leverage the computational efficiency, a modified sparse matrix-vector multiplication algorithm is proposed and implemented using a General-Purpose Graphics Processing Unit (GPGPU). The new algorithm ensures that all computations are performed within the GPU, with minimum number of device-to-host data transfer and global memory access. With GPU's accelerated computing capability, the proposed solver achieves more than 5× computational speed up with respect to a high performance CPU-based direct solver on average. In addition, due to the intrinsic memory efficient nature of iterative solver, our approach also shows maximally more than 31× reduction in memory consumption against the direct solver. Various numerical examples are simulated to validate the capability and improvement of the proposed method.
{"title":"GPU Accelerated Matrix Solution Using Novel Preconditioner for Three Dimensional Laguerre-FDTD Method","authors":"Yifan Wang;Yiliang Guo;Joshua Corsello;Madhavan Swaminathan","doi":"10.1109/JMMCT.2025.3572490","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3572490","url":null,"abstract":"Conventionally, the large sparse matrix equation (<inline-formula><tex-math>$Ax=b$</tex-math></inline-formula>) generated by the Laguerre-FDTD method is computed using direct matrix solvers, which is often numerically expensive and computationally slow. In this work, we demonstrate an innovative approach to replace direct matrix solver with an iterative algorithm for the Laguerre-FDTD method. A novel preconditioner, specifically targeted to improve the convergence rate of biconjugate gradient stabilized solver (BiCGSTAB), is derived and implemented in the Laguerre-FDTD method. Compared with the classical Jacobi preconditioner, the proposed preconditioner achieves on average an improvement of more than 1.3× in the convergence rate. To further leverage the computational efficiency, a modified sparse matrix-vector multiplication algorithm is proposed and implemented using a General-Purpose Graphics Processing Unit (GPGPU). The new algorithm ensures that all computations are performed within the GPU, with minimum number of device-to-host data transfer and global memory access. With GPU's accelerated computing capability, the proposed solver achieves more than 5× computational speed up with respect to a high performance CPU-based direct solver on average. In addition, due to the intrinsic memory efficient nature of iterative solver, our approach also shows maximally more than 31× reduction in memory consumption against the direct solver. Various numerical examples are simulated to validate the capability and improvement of the proposed method.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"259-270"},"PeriodicalIF":1.8,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144213617","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}
Pub Date : 2025-03-12DOI: 10.1109/JMMCT.2025.3569766
Rui Fang;Yu Mao Wu;Hongxia Ye
The optimization of radar cross section (RCS) is now a significant issue in the designation of military and civilian equipment. Comparing with the expensive material approaches, changing the geometry of an object is a relatively flexible and low-cost way. However, the RCS optimization of large-scale models often faces two major problems: too large optimization space and slow RCS calculation, which caused by increasing geometry parameters and iterative numerical computation, respectively. In addition, secondary problems such as geometric information loss and RCS results lacking of gaurantees always remain even if dimensionality reduction has been carried out for alleviating these two problems. In this paper, we propose a novel end-to-end differentiable RCS optimization framework based on the physical optics (PO) method. The proposed framework utilize the differentiability of the PO method, and realize an efficient and interpretable RCS optimization without dimension reduction. The innovation of this paper lies in the combination of PO method and gradient-based optimization to achieve RCS optimization of large-scale complex 3D geometries. Experiments show that in ordinary 2D scenarios, our method achieves at least 16 times higher efficiency than the mainstream optimization method. Meanwhile, the optimization error of RCS has been reduced by 75.29$%$ compared to traditional methods (0.0515vs. 0.2084). We further validate the performance of the framework on more complex tasks such as 3D plane model and analyzed the effectiveness of the overall framework. The proposed optimization method is expected to be widely used in applications such as stealth and aircraft designs.
{"title":"End-to-End Differentiable RCS Optimization on 3D Geometry Based on Physical Optics Method","authors":"Rui Fang;Yu Mao Wu;Hongxia Ye","doi":"10.1109/JMMCT.2025.3569766","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3569766","url":null,"abstract":"The optimization of radar cross section (RCS) is now a significant issue in the designation of military and civilian equipment. Comparing with the expensive material approaches, changing the geometry of an object is a relatively flexible and low-cost way. However, the RCS optimization of large-scale models often faces two major problems: too large optimization space and slow RCS calculation, which caused by increasing geometry parameters and iterative numerical computation, respectively. In addition, secondary problems such as geometric information loss and RCS results lacking of gaurantees always remain even if dimensionality reduction has been carried out for alleviating these two problems. In this paper, we propose a novel end-to-end differentiable RCS optimization framework based on the physical optics (PO) method. The proposed framework utilize the differentiability of the PO method, and realize an efficient and interpretable RCS optimization without dimension reduction. The innovation of this paper lies in the combination of PO method and gradient-based optimization to achieve RCS optimization of large-scale complex 3D geometries. Experiments show that in ordinary 2D scenarios, our method achieves at least 16 times higher efficiency than the mainstream optimization method. Meanwhile, the optimization error of RCS has been reduced by 75.29<inline-formula><tex-math>$%$</tex-math></inline-formula> compared to traditional methods (0.0515vs. 0.2084). We further validate the performance of the framework on more complex tasks such as 3D plane model and analyzed the effectiveness of the overall framework. The proposed optimization method is expected to be widely used in applications such as stealth and aircraft designs.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"246-258"},"PeriodicalIF":1.8,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144196910","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}
Pub Date : 2025-03-11DOI: 10.1109/JMMCT.2025.3550117
Runwei Zhou;Dan Jiao
Solid-state spin qubits are one of the candidate platforms for future quantum computers due to their long coherence time and good controllability. However, qubits are susceptible to noise generated from external magnetic fields. In this paper, we present a fast and accurate volume integral equation solver for analyzing local/nonlocal optical responses in quantum nano-electromagnetic gate circuitry. Due to small electric sizes of quantum circuitry, conventional volume integral equation (VIE) solvers suffer from both numerical difficulties and deteriorated accuracy since the underlying numerical system is highly ill-conditioned. To overcome this problem, we introduce a well-conditioned VIE formulation. We further accelerate the VIE solution by transforming the six-dimensional integral arising from the nonlocal constitutive relation to the spectral domain using fast Fourier transform (FFT). The same FFT is also applied to efficiently compute the convolution of Green's function with equivalent volumetric currents. The resultant fast and robust VIE solver has been applied to analyze large-scale 3-D quantum gate devices. Both local and nonlocal optical responses of the devices are captured accurately and efficiently. This work offers a fast and accurate approach to guide the noise control of high-fidelity quantum gate circuitry design.
{"title":"Fast Well-Conditioned Volume Integral Equation Solver for Analyzing Nonlocal Optical Responses in Quantum Nanostructures","authors":"Runwei Zhou;Dan Jiao","doi":"10.1109/JMMCT.2025.3550117","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3550117","url":null,"abstract":"Solid-state spin qubits are one of the candidate platforms for future quantum computers due to their long coherence time and good controllability. However, qubits are susceptible to noise generated from external magnetic fields. In this paper, we present a fast and accurate volume integral equation solver for analyzing local/nonlocal optical responses in quantum nano-electromagnetic gate circuitry. Due to small electric sizes of quantum circuitry, conventional volume integral equation (VIE) solvers suffer from both numerical difficulties and deteriorated accuracy since the underlying numerical system is highly ill-conditioned. To overcome this problem, we introduce a well-conditioned VIE formulation. We further accelerate the VIE solution by transforming the six-dimensional integral arising from the nonlocal constitutive relation to the spectral domain using fast Fourier transform (FFT). The same FFT is also applied to efficiently compute the convolution of Green's function with equivalent volumetric currents. The resultant fast and robust VIE solver has been applied to analyze large-scale 3-D quantum gate devices. Both local and nonlocal optical responses of the devices are captured accurately and efficiently. This work offers a fast and accurate approach to guide the noise control of high-fidelity quantum gate circuitry design.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"209-217"},"PeriodicalIF":1.8,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761369","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}
Pub Date : 2025-03-07DOI: 10.1109/JMMCT.2025.3563480
Boyuan Zhang;Weng Cho Chew
The discrete exterior calculus (DEC) $mathbf {A}$-$Phi$ solver is a broadband stable solver in computational electromagnetics which can work from DC to optics. In order to solve practical problems, which are often multi-scale ones with large number of unknowns and condition number, a broadband preconditioner to the DEC $mathbf {A}$-$Phi$ solver is proposed in this paper. The proposed preconditioner is based on sparsified nested dissection ordering (spa-NDO) technique. In this paper, introductions to the DEC $mathbf {A}$-$Phi$ solver and NDO technique are provided, as well as detailed implementation flow of the proposed modified spa-NDO preconditioner. Through numerical examples, it reveals that the proposed preconditioned solver has $O(N log N)$ computational complexity. The efficiency of the proposed preconditioner is almost independent of parameters such as frequency and conductivity in the problem, which indicates its broadband nature.
{"title":"A Broadband Preconditioner Based on Sparsified Nested Dissection Ordering Technique for the Vector-Scalar Potential Discrete Exterior Calculus Solver","authors":"Boyuan Zhang;Weng Cho Chew","doi":"10.1109/JMMCT.2025.3563480","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3563480","url":null,"abstract":"The discrete exterior calculus (DEC) <inline-formula><tex-math>$mathbf {A}$</tex-math></inline-formula>-<inline-formula><tex-math>$Phi$</tex-math></inline-formula> solver is a broadband stable solver in computational electromagnetics which can work from DC to optics. In order to solve practical problems, which are often multi-scale ones with large number of unknowns and condition number, a broadband preconditioner to the DEC <inline-formula><tex-math>$mathbf {A}$</tex-math></inline-formula>-<inline-formula><tex-math>$Phi$</tex-math></inline-formula> solver is proposed in this paper. The proposed preconditioner is based on sparsified nested dissection ordering (spa-NDO) technique. In this paper, introductions to the DEC <inline-formula><tex-math>$mathbf {A}$</tex-math></inline-formula>-<inline-formula><tex-math>$Phi$</tex-math></inline-formula> solver and NDO technique are provided, as well as detailed implementation flow of the proposed modified spa-NDO preconditioner. Through numerical examples, it reveals that the proposed preconditioned solver has <inline-formula><tex-math>$O(N log N)$</tex-math></inline-formula> computational complexity. The efficiency of the proposed preconditioner is almost independent of parameters such as frequency and conductivity in the problem, which indicates its broadband nature.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"235-245"},"PeriodicalIF":1.5,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145051026","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}
Pub Date : 2025-03-05DOI: 10.1109/JMMCT.2025.3567252
Takaya Sugiura
Loss visualization and analysis of 4H-silicon carbide (4H-SiC) power diodes were performed using the free energy loss analysis (FELA) method that was originally developed for photovoltaic cells. The FELA approach features several advantages, including the direct expression of loss in W/cm$^{2}$, representation of each electron- and hole-induced loss, and internal loss visualization by calculating the free energy at each point. Four 4H-SiC power diodes, including two PiN diodes, a Schottky barrier diode (SBD), and a junction-barrier Schottky diode (JBSD), were evaluated. The PiN diodes exhibited significant Joule losses owing to the inherently high recombination heating associated with these bipolar devices. In contrast, the SBD e$^-$-induced Joule loss, whereas h$^+$-induced Joule and recombination losses were negligible for this unipolar device. The JBSD exhibited a high allowable current density with low self-heating and was determined to be the best power diode. The FELA visualization of the e$^-$-induced Joule loss of this device revealed that the SBD interface, particularly the p$^+$-region, is the dominant source of Joule loss. Applying FELA to reversed characteristics revealed several insightful device phenomena and which physics were responsible for the loss in different situations.
{"title":"Internal Loss Analysis and Visualization of 4H-Silicon Carbide Power Diodes: Free Energy Loss Analysis Under the Static Condition","authors":"Takaya Sugiura","doi":"10.1109/JMMCT.2025.3567252","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3567252","url":null,"abstract":"Loss visualization and analysis of 4H-silicon carbide (4H-SiC) power diodes were performed using the free energy loss analysis (FELA) method that was originally developed for photovoltaic cells. The FELA approach features several advantages, including the direct expression of loss in W/cm<inline-formula><tex-math>$^{2}$</tex-math></inline-formula>, representation of each electron- and hole-induced loss, and internal loss visualization by calculating the free energy at each point. Four 4H-SiC power diodes, including two PiN diodes, a Schottky barrier diode (SBD), and a junction-barrier Schottky diode (JBSD), were evaluated. The PiN diodes exhibited significant Joule losses owing to the inherently high recombination heating associated with these bipolar devices. In contrast, the SBD e<inline-formula><tex-math>$^-$</tex-math></inline-formula>-induced Joule loss, whereas h<inline-formula><tex-math>$^+$</tex-math></inline-formula>-induced Joule and recombination losses were negligible for this unipolar device. The JBSD exhibited <bold>a high allowable current density with</b> low self-heating and was determined to be the best power diode. The FELA visualization of the e<inline-formula><tex-math>$^-$</tex-math></inline-formula>-induced Joule loss of this device revealed that the SBD interface, particularly the p<inline-formula><tex-math>$^+$</tex-math></inline-formula>-region, is the dominant source of Joule loss. Applying FELA to reversed characteristics revealed several insightful device phenomena and which physics were responsible for the loss in different situations.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"227-234"},"PeriodicalIF":1.8,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949153","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}
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