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Image fusion technology is widely used to fuse the complementary information between multi-source remote sensing images. Inspired by the frontier of deep learning, this paper first proposes a heterogeneous-integrated framework based on a…
Xenium, a new spatial transcriptomics platform, enables subcellular-resolution profiling of complex tumor tissues. Despite the rich morphological information in histology images, extracting robust cell-level features and integrating them…
Any large-scale spiking neuromorphic system striving for complexity at the level of the human brain and beyond will need to be co-optimized for communication and computation. Such reasoning leads to the proposal for optoelectronic…
Photonics is a promising architecture for the realisation of quantum information processing, since the two-photon interaction, or non-linearity, necessary to build logical gates can efficiently be realised by the use of interference with…
Deep learning has led to unprecedented successes in solving some very difficult problems in domains such as computer vision, natural language processing, and general pattern recognition. These achievements are the culmination of…
Silicon photonics has been studied as an integratable optical platform where numerous applicable devices and systems are created based on modern physics and state-of-the-art nanotechnologies. The implementation of quantum mechanics has been…
Stacked intelligent metasurfaces (SIMs) extend the concept of reconfigurable intelligent surfaces by cascading multiple programmable layers, enabling advanced electromagnetic wave transformations for communication and sensing applications.…
Terahertz waves offer a profound platform for next-generation sensing, imaging, and information communications. However, all conventional terahertz components and systems suffer from a bulky design, sensitivity to imperfections, and…
A variety of topological Hamiltonians have been demonstrated in photonic platforms, leading to fundamental discoveries and enhanced robustness in applications such as lasing, sensing, and quantum technologies. To date, each topological…
Infrastructure Enabled Autonomy (IEA) is a new paradigm that employs a distributed intelligence architecture for connected autonomous vehicles by offloading core functionalities to the infrastructure. In this paper, we develop a simulation…
Photonic integrated circuits (PICs) offer ultra-broad optical bandwidths that enable unprecedented data throughputs for signal processing applications. Dynamic reconfigurability enables compensation of fabrication flaws and fluctuating…
Neuro-symbolic Artificial Intelligence (AI) models, blending neural networks with symbolic AI, have facilitated transparent reasoning and context understanding without the need for explicit rule-based programming. However, implementing such…
Electrical control of light in integrated photonics is central to a wide range of research and applications. It is conventionally achieved with thermo-optic tuning, but this suffers from high energy consumption and crosstalk.…
Optical networks with parallel processing capabilities are significant in advancing high-speed data computing and large-scale data processing by providing ultra-width computational bandwidth. In this paper, we present a photonic integrated…
Predictive simulations and experimental design involving extreme aero-chemo-thermo-mechanical regimes require high-fidelity material representation across diverse physical states. However, data for metals, polymers, and propellants,…
Quantum computing has made substantial progress in recent years; however, its scalability remains constrained on a monolithic quantum processing unit (QPU). Distributed quantum computing (DQC) offers a pathway by coordinating multiple QPUs…
In-Network Collective (INC) acceleration holds immense potential for optimizing AI training and inference; however, its cross-layer nature has historically hindered investment and adoption within the open Ethernet ecosystem. To bridge this…
In optical communication systems, fibre nonlinearity is the major obstacle in increasing the transmission capacity. Typically, digital signal processing techniques and hardware are used to deal with optical communication signals, but…
Large-scale numerical simulations underpin modern scientific discovery but remain constrained by prohibitive computational costs. AI surrogates offer acceleration, yet adoption in mission-critical settings is limited by concerns over…
Integrated nanophotonic biosensors offer a promising route toward future biomedical detection applications that may enable inexpensive, portable, and sensitive diagnosis of diseases with a small amount of biological samples for convenient…