Keynote speaker 1: Computational electromagnetics: Past, present, and future

W. Chew
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Abstract

Electromagnetics and Maxwell's equations have been instrumental in the conception of many electrical engineering technologies. It the beginning, it was telegraphy, and rotating machineries. Over the years, electromagnetics has given rise to numerous technologies like wireless communications, antennas, radar, and masers. On the optics side, simplified ray optics theory was used to design lenses and focusing systems. As many optical systems can be described by ray optics approximations, the first area that requires the full solution of Maxwell's equations is in microwave engineering, antenna design, and remote and subsurface sensing. Hence, there were pressing needs to design better antenna systems for communication, radar for target identification, and radio waves for remote sensing. While closed form solutions offered some physics insight, approximate solutions were invoked to further expand the insight of designers and engineers. When approximation solutions were exhausted, numerical methods or computational electromagnetics (CEM) were developed to further aid designers and engineers. As demand for numerical methods looms, fast and efficient methods of solving Maxwell's equations become a popular topic of research. There are essentially two classes of solvers for Maxwell's equations: differential equation solvers and integral equation solvers. While differential equation solvers use more unknowns than integral equation solvers, they are easy to implement and to maintain. Integral equation solvers, on the other hand, use fewer unknowns, but are more difficult to implement. They also yield dense matrix systems that are expensive to solve and store. However, the advent of fast solvers has greatly expedited their solution efficiency. As of this point, dense matrix systems with over three billion unknowns have been solved using fast solvers. Also, the path to large scale computing requires the use of iterative solvers. Over time, as the demand for CEM solvers grows, more complex structures with a disproportionate number of unknowns need to be solved. They give rise to ill-conditioned matrix systems. Hence, preconditioners or domain decomposition methods are designed to reduce the ill conditioning of matrix system. The preconditioners will greatly expedite iterative solutions to these problems. Maxwell's equations are also intimately related to mathematical geometry and to quantum physics. Differential geometry concepts can be invoked to help in the selection of basis and testing functions in finding the matrix representations of Maxwell operators. Furthermore, even when quantum theory is invoked in the quantization of electromagnetic fields, the fields are still governed by Maxwell's equations. Therefore, solutions of Maxwell's equations are needed even in the quantum regime. Since photons play an important role in the manipulation of quantum information, the solutions of Maxwell's equations will be instrumental even in quantum optics or quantum electromagnetics. They will play an important role in the area of quantum computers and quantum information.
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主讲人1:计算电磁学:过去、现在和未来
电磁学和麦克斯韦方程组在许多电气工程技术的概念中起着重要作用。最开始是电报和旋转机械。多年来,电磁学已经产生了许多技术,如无线通信、天线、雷达和脉泽。在光学方面,采用简化射线光学理论设计透镜和聚焦系统。由于许多光学系统可以用射线光学近似来描述,因此需要麦克斯韦方程组完整解的第一个领域是微波工程、天线设计、遥感和地下传感。因此,迫切需要为通信设计更好的天线系统,为目标识别设计更好的雷达,为遥感设计更好的无线电波。虽然封闭形式的解决方案提供了一些物理洞察力,但近似解被用来进一步扩展设计师和工程师的洞察力。当近似解被用尽时,数值方法或计算电磁学(CEM)被开发来进一步帮助设计师和工程师。随着对数值方法的需求日益迫切,快速有效地求解麦克斯韦方程组的方法成为研究的热门课题。麦克斯韦方程组基本上有两类求解器:微分方程求解器和积分方程求解器。虽然微分方程求解器比积分方程求解器使用更多的未知数,但它们易于实现和维护。另一方面,积分方程求解器使用较少的未知数,但更难实现。它们也会产生密集的矩阵系统,求解和存储都很昂贵。然而,快速求解器的出现大大提高了它们的求解效率。到目前为止,使用快速求解器已经解决了具有超过30亿个未知数的密集矩阵系统。此外,大规模计算的路径需要使用迭代求解器。随着时间的推移,随着对CEM求解器需求的增长,需要解决具有不成比例的未知数量的更复杂的结构。它们产生了病态矩阵系统。因此,设计了预调节器或区域分解方法来减少矩阵系统的病态。前置条件将大大加快这些问题的迭代求解。麦克斯韦方程组也与数学几何和量子物理密切相关。在寻找麦克斯韦算子的矩阵表示时,可以调用微分几何概念来帮助选择基和测试函数。此外,即使在电磁场的量子化中引用量子理论,电磁场仍然受麦克斯韦方程的支配。因此,即使在量子状态下,也需要麦克斯韦方程组的解。由于光子在量子信息的操纵中扮演着重要的角色,麦克斯韦方程组的解将在量子光学或量子电磁学中发挥重要作用。它们将在量子计算机和量子信息领域发挥重要作用。
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