Taming complexity in computational electromagnetism: a model order reduction approach

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Electromagnetic phenomena play a critical role inside the integrated circuits (ICs) and antennas that empower many electronic systems around us, including smartphones, computers, and data centers. Behind the scenes, electromagnetism also plays a crucial role in emerging technologies such as the Internet of Things (IoT) and Artificial Intelligence (AI). It is estimated that, by 2020, 20 billion IoT devices will be connected to the Internet. Electromagnetic waves, and significant advancements in antenna technology, will be the only way to connect the myriad of future IoT devices to the Internet, due to the prohibitive cost of terrestrial infrastructure. Metasurfaces are a new type of antennas which is ideally suited to respond to soaring IoT needs. Unfortunately, metasurfaces are extremely complex. Since no existing electromagnetic simulator can handle their complexity, engineers are currently missing one of the most critical tools for metasurface design. Similar challenges are faced by microelectronic companies such as AMD, which extensively rely on electromagnetic simulators to design new ICs, including the hardware accelerators of neural networks that are increasingly needed by advanced AI applications. ******The significant gap between what electromagnetic solvers can do and what designers need is a major issue for both industry and academia. The proposed research aims to fill this gap by laying down the theoretical and algorithmic foundations of an electromagnetic solver with superior scalability. We propose to investigate an innovative approach based on the concept of model order reduction. While model order reduction is well established for circuit simulation, it has received limited attention in computational electromagnetism, despite a clear need. We propose to develop the first systematic techniques to create compact, reduced-complexity models of the electromagnetic behavior of complex objects, such as the unit cell of a metasurface. The proposed models will be compatible with mainstream simulators based on the method of moments, allowing designers to analyze very large layouts in reasonable time. Leveraging the proposed developments and parallel computing, we will create an electromagnetic solver with unprecedented scalability, capable of handling an entire metasurface antenna. These developments will greatly facilitate the design of new metasurface antennas and ICs, including those required by upcoming IoT and AI applications.******The proposed developments will be immediately translated to real design workflows, in collaboration with leading companies (AMD, Thales) and scientists (Profs. Eleftheriades and Hum). The proposed research will involve nine students who will receive comprehensive training of the highest quality, with access to world-class industrial partners, facilities and forefront technologies. Overall, this program is expected to result in nine graduates with a unique skillset, in high demand by industry and academia.