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- caption: Platform-level In-situ and Co-Site Antenna Analysis |
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- caption: Quantum-assisted Smart Radio Environment |
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- caption: Statistical Wave Physics in Information Transmission |
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# Feel free to add content and custom Front Matter to this file. |
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# To modify the layout, see https://jekyllrb.com/docs/themes/#overriding-theme-defaults |
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layout: banner |
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title: Home |
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cardTitle: Goals |
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cardDesc: We focus on developing mathematical and computational models to further the understanding and prediction of classical, chaotic, and quantum wave phenomena. |
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# Recent Projects and Events |
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[Read More](/research/sample1) |
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Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum. |
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[Read More](/research/sample1) |
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[Read More](/research/sample3) |
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layout: banner |
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title: Applications |
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permalink: /applications/ |
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cardTitle: Topics |
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cardDesc: We tackle a broad set of problems relating to the electromagnetic phenomena, from antennas and propagation, to electromagnetic interference/compatiblity, to wireless communication. |
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# Engineering Applications |
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## Full-Wave Field Solvers for Signal Integrity (SI) and EM Interference (EMI) Analysis of Product-Level Integrated Circuits (ICs) and Electronics |
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Ever-increasing complexity in high-speed electronic devices and systems presents significant computational challenges in numerical analysis in terms of desired accuracy, efficiency, and scalable parallelism. We investigate high-resolution, high-performance full-wave field solvers for scalable electromagnetic simulations of product-level integrated circuits (ICs) and electronics. |
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[Read More](/applications/SIEMI/) |
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## Stochastic Wave Model Statistically Replicating Reverberation Chambers |
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We present a novel physics-oriented statistical representation for complex multipath environments, and develop a hybrid deterministic and stochastic formulation incorporating component-specific features. The advancements lead to a stochastic wave model statistically replicating mode-stirred reverberation chambers, and establish an imperative design-under-chaos capability for electronic devices and systems. The research work is evaluated and validated through representative experiments. |
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[Read More](/applications/reverberation-chamber/) |
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## Deterministic and Statistical Modeling of Wireless Channel |
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we present a full-wave field-based computational methodology for radio wave propagation in complex urban environments. Both transmitting/receiving antennas and propagation environments are modeled by first-principles calculations. System-level, large scene analysis is enabled by scalable, ultra-parallel algorithms on emerging high-performance computing platforms. The proposed computational framework is verified and validated with semi-analytical models and representative measurements. |
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[Read More](/applications/statistical-channel/) |
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layout: banner |
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title: Research |
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permalink: /research/ |
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cardTitle: Goals |
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cardDesc: Our goal is to simulate classical and quantum electrodynamic physics with intelligent algorithms on state-of-the-art computers, where virtual experiments can be performed for the prediction, discovery, and design of complex systems. |
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# Research Statement |
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The foundation of our research is theoretical, computational, and statistical electromagnetics. The classical electromagnetic (EM) theory guided by Maxwell’s Equations has been around for over 150 years. It has an incredible impact on many modern technologies such as antennas and wireless communication, integrated circuits and computer technologies, remote sensing, lasers and optoelectronics, and more. Nowadays, with the exponential growth in computing power, machine intelligence and data revolution, quantum technologies and materials, there are enormous opportunities to continue advancing fundamental EM theories toward next-generation technology developments and applications. |
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Our rudimentary research is the pursuit of mathematical and computational models that enable the prediction and discovery of classical and quantum electrodynamic phenomena. These models will allow for the design and optimization of novel electromagnetic and wireless systems at unprecedented scales, and contribute through education to the advancement of understanding. |
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Our recent research focus on four interrelated areas: (1) classical electromagnetism with scalable algorithms, (2) statistical electromagnetics integrating order and chaos, (3) quantum electromagnetics: simulating probability in space and time domain, and (4) Smart Radio Environments for NextG wireless systems. |
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# Research Topics |
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## Domain Decomposition Methodology for Solving Maxwell's Equations at Scale |
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The goal of this research is to investigate first-principles modeling and analysis tools for these extremely large, multi-scale problems. The emphasis is placed on advancing parallel algorithms that are provably scalable, and facilitating a design-through-analysis paradigm for emerging and future complex systems. |
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[Read More](/research/domain-decomposition/) |
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## Physics-Oriented Statistical Wave Analysis for Chaotic and Disordered Scattering Environments |
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The main objective of this work is to investigate new fundamental mathematical models and computational algorithms for statistical wave analysis in complex, confined EM environments. This objective is attained by integrating wave chaos physics, random statistical analysis, and high-performance algorithms on state-of-the-art computational platforms. The research will overcome key challenges in the statistical characterization of three general classes of problems, fully wave chaotic systems, mixed integrable and chaotic systems, and complex fluctuating scattering environments. |
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[Read More](/research/physics-oriented-statistical-wave-analysis/) |
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## Quantum Computing and Optimization in Smart Radio Environments |
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Fusing electromagnetic models with quantum computing (QC) algorithms for rapid optimization of reconfigurable intelligent surfaces (RIS)-assisted beyond-5G/6G wireless networks. |
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[Read More](/research/Quantum-optimization-RIS/) |
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layout: post |
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title: Quantum Computing and Optimization in Smart Radio Environments |
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permalink: /research/Quantum-optimization-RIS/ |
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# Quantum Computing and Optimization in Smart Radio Environments |
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##### Collaborator: Gabriele Gradoni@Surrey |
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With rapidly evolving quantum devices and materials, in the near future, there will likely be special-purpose quantum computers with hundreds of high-quality qubits and controllable nearest-neighbor couplings. A forward- thinking question is, how do we leverage “quantum advantage” and develop quantum algorithms for electromagnetic problems and wireless applications? In this section, we will discuss our recent studies of quantum computing algorithms and hybrid classical-quantum computing models for reconfigurable wireless environments. |
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The reconfigurable intelligent surface (RIS) is emerging as a key technology for the next generation of wireless networks. The general goal is to turn the wireless environment into a smart/reconfigurable space that plays an active role in the wireless communication performance. Going beyond 5G and entering 6G, it is envisaged that large-scale, distributed RIS devices may be deployed at the surface of interacting objects, |
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e.,g. wall, windows, and furniture, in the propagation channel. A joint optimization of wireless endpoints and distributed RISs would lead to a dynamically programmable and customized wireless environment, with a goal of providing enhanced coverage with high energy efficiency and supporting ultra-fast and seamless connectivity. |
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To harness the full potential of a RIS-enabled smart wireless environment, one needs to rapidly optimize the states of RIS with prescribed objective functions, e.g., beamforming, localization/focusing, and channel diversity. This constitutes a substantial computational task in both the physical and network layer of wireless communication. Furthermore, one assumption adopted in the wireless community is that the RISs are nearly passive due to minimal hardware complexity and power requirements. Namely, the RIS may not have the capability to sense the wireless channel and estimate directions of arrival/departure. The channel estimation cannot be implemented on the RIS side, but rather at wireless endpoints of the communication link. This makes the channel optimization of RIS-assisted networks very challenging. |
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The scientific contribution in this work is a physics-oriented, mathematically tractable computational framework for optimizing RIS configuration in complex radio environments. Such optimization is performed without the need to estimate the segmented channels that link the transmitter to the RIS and the RIS to the receiver. The new idea starts with expressing the power of end-to-end channel transfer function as an Ising Hamiltonian model. A hybrid classical-quantum computing model is proposed next to navigate the RIS configuration space and to rapidly optimize the RIS state in a multipath radio environment. Compared to the state-of-the-art solutions, we show that the Ising Hamiltonian model serves as a unified mathematical model describing wave physics in the RIS-assisted wireless network. By leveraging the computing power of quantum adiabatic evolution and mathematics of tensor contraction, the channel estimation and optimization can be completed in the order of milliseconds. The outcomes enable the possibility of ultrafast optimization adapting to dynamic wireless environments. |
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We believe that the physics of complex systems fused with quantum computing will constitute a game changer in the modeling and design of large network of RIS devices cooperating in order to transform real-life propagation environments into a resource for future mobile networks, including SONs and cell-free networks. |
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### A basic introduction to quantum annealing for engineering metasurfaces: |
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#### C. Ross, G. Gradoni, Q. J. Lim, and Z. Peng, “Engineering reflective metasurfaces with Ising hamiltonian and quantum annealing,” IEEE Transactions on Antennas and Propagation, vol. 70, no. 4, pp. 2841–2854, 2022. |
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### A discussion of quantum-assisted combinatorial optimization for reconfigurable surfaces,: |
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#### Q. J. Lim, C. Ross, G. Gradoni, and Z. Peng, “Quantum-Assisted Combinatorial Optimization of Reconfigurable Intelligent Surfaces,” 16th European Conference on Antennas and Propagation, 27 March - 01 April, 2022 (Best Electromagnetics Paper Award). |
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