@ -89,24 +89,24 @@ Best Student Paper Award in 26th Conference on Electrical Performance of Electro
[1] Q. J. Lim, C. Ross, A. Ghosh, F. Vook, G. Gradoni, and Z. Peng, “Quantum-Assisted Combinatorial Optimization for Reconfigurable Intelligent Surfaces in Smart Electromagnetic Environments,” IEEE Trans. Antennas Propag., vol. 72, no. 1, pp. 147-159, Jan. 2024.
* _Significance_: This paper presents a physics-based, hybrid classical-quantum optimization framework for reconfigurable intelligent surfaces (RIS), drawing inspiration from the statistical mechanics of correlated spins. The key innovation is mapping the electromagnetic power to the Ising Hamiltonian function, effectively transforming the RIS configuration optimization problem into finding the ground state of the Ising model. Moreover, this framework successfully demonstrates a quantum advantage in solving complex combinatorial optimization problems in smart radio environments.
* _Significance_: This paper presents a physics-based, hybrid classical-quantum optimization framework for reconfigurable intelligent surfaces (RIS), drawing inspiration from the statistical mechanics of correlated spins. The key innovation is mapping the electromagnetic power to the Ising Hamiltonian function, effectively transforming the RIS configuration optimization problem into finding the ground state of the Ising model. Moreover, this framework successfully demonstrates a quantum advantage in solving complex combinatorial optimization problems in smart radio environments.
[2] S. Lin, S. Luo, S. Ma, J. Feng, Y. Shao, Z. B. Drikas, B. D. Addissie, S. M. Anlage, T. Antonsen, and Z. Peng, “Predicting Statistical Wave Physics in Complex Enclosures: A Stochastic Dyadic Green’s Function Approach,” IEEE Trans. Electromagnetic Compatibility, vol. 65, no. 2, pp. 436-453, April 2023.
* _Significance_: This research focuses on developing physics-oriented statistical representations and algorithms for complex, wave-chaotic environments. The paper introduces an innovative computational methodology known as the stochastic Green’s function (SGF) method, which statistically describes the multipath, ray-chaotic interactions between transmitters and receivers. The work accomplishes a physics-oriented, mathematically tractable statistical wave model with diverse applications, including the mode-stirred reverberation chamber, information transmission in wave-chaotic indoor channels, statistical design of time-reversal systems, wavefront shaping and focusing, sensing and targeting.
* _Significance_: This research focuses on developing physics-oriented statistical representations and algorithms for complex, wave-chaotic environments. The paper introduces an innovative computational methodology known as the stochastic Green’s function (SGF) method, which statistically describes the multipath, ray-chaotic interactions between transmitters and receivers. The work accomplishes a physics-oriented, mathematically tractable statistical wave model with diverse applications, including the mode-stirred reverberation chamber, information transmission in wave-chaotic indoor channels, statistical design of time-reversal systems, wavefront shaping and focusing, sensing and targeting.
[3] G. Cao and Z. Peng, “RayProNet: A Neural Point Field Framework for Radio Propagation Modeling in 3D Environments,” IEEE Journal on Multiscale and Multiphysics Computational Techniques, vol. 9, pp. 330-340, 2024.
* _Significance_: This research introduces a novel machine learning-empowered methodology for wireless channel modeling. It leverages a point-cloud-based neural network combined with spherical harmonics encoding to predict radio path loss maps in both indoor and outdoor environments. By embedding electromagnetic wave propagation physics into neural networks, this framework enables efficient and scalable modeling of complex 3D wireless scenarios, significantly enhancing the speed and adaptability required for network design and optimization.
* _Significance_: This research introduces a novel machine learning-empowered methodology for wireless channel modeling. It leverages a point-cloud-based neural network combined with spherical harmonics encoding to predict radio path loss maps in both indoor and outdoor environments. By embedding electromagnetic wave propagation physics into neural networks, this framework enables efficient and scalable modeling of complex 3D wireless scenarios, significantly enhancing the speed and adaptability required for network design and optimization.
[4] Zhen Peng, Yang Shao, Hong-Wei Gao, Shu Wang and Shen Lin, “High-Fidelity, High-Performance Computational Algorithms for Intra-System Electromagnetic Interference Analysis of IC and Electronics,” IEEE Transactions on Components, Packaging and Manufacturing Technology, vol. 7, no. 5, pp. 653-668, May 2017.
* _Significance_: As next-generation electronic systems evolve to achieve greater functionality and smaller sizes, electromagnetic interference (EMI) between components becomes a critical challenge, impacting performance. This paper introduces high-fidelity, high-performance full-wave field solvers for scalable electromagnetic simulations of product-level integrated circuits (ICs) and electronics. The work enables concurrent multiscale modeling, accounting for the mutual interactions of circuits, 3D interconnects, packages, and PCBs. These innovations offer a powerful verification tool during the design stage, enhancing the ability to predict and optimize the performance of complex IC systems with high confidence in their in situ performance.
* _Significance_: As next-generation electronic systems evolve to achieve greater functionality and smaller sizes, electromagnetic interference (EMI) between components becomes a critical challenge, impacting performance. This paper introduces high-fidelity, high-performance full-wave field solvers for scalable electromagnetic simulations of product-level integrated circuits (ICs) and electronics. The work enables concurrent multiscale modeling, accounting for the mutual interactions of circuits, 3D interconnects, packages, and PCBs. These innovations offer a powerful verification tool during the design stage, enhancing the ability to predict and optimize the performance of complex IC systems with high confidence in their in situ performance.
[5] Zhen Peng, Kheng-Hwee Lim, and Jin-Fa Lee, “A Discontinuous Galerkin Surface Integral Equation Method for Electromagnetic Wave Scattering from Nonpenetrable Targets,” IEEE Trans. Antennas Propag., vol. 61, no. 7, pp. 3617-3628, 2013.
* _Significance_: The objective of this work is to allow the solution of integral equations using discontinuous trial and test functions without any consideration of continuity requirements across element's boundaries. We can mix different types of elements and employ different order of basis functions within the same discretization. Built upon the DG-BEM, we investigate a rigorous, adaptive, and parallel coarse-graining method to reduce the computational complexity in multi-scale computation.
* _Significance_: The objective of this work is to allow the solution of integral equations using discontinuous trial and test functions without any consideration of continuity requirements across element's boundaries. We can mix different types of elements and employ different order of basis functions within the same discretization. Built upon the DG-BEM, we investigate a rigorous, adaptive, and parallel coarse-graining method to reduce the computational complexity in multi-scale computation.
[6] Zhen Peng and Jin-Fa Lee, “A Scalable Non-overlapping and Non-conformal Domain Decomposition Method for Solving Time-harmonic Maxwell Equations in R3,” SIAM Journal on Scientific Computing., vol. 34, no. 3, pp. A1266-A1295, 2012.
* _Significance_: This paper lays the theoretical foundation for nonoverlapping finite element domain decomposition methods (FE-DDM) for solving the time-harmonic Maxwell equations. It introduces three key innovations: (a) a true second order transmission condition (SOTC) to enforce field continuities across domain interfaces; (b) a corner edge penalty term to account for corner edges between neighbouring subdomains; and (c) a global plane wave deflation technique to further improve the convergence of DDM for electrically large problems.
* _Significance_: This paper lays the theoretical foundation for nonoverlapping finite element domain decomposition methods (FE-DDM) for solving the time-harmonic Maxwell equations. It introduces three key innovations: (a) a true second order transmission condition (SOTC) to enforce field continuities across domain interfaces; (b) a corner edge penalty term to account for corner edges between neighbouring subdomains; and (c) a global plane wave deflation technique to further improve the convergence of DDM for electrically large problems.
IncheolJung
2 months ago