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Microcombs have sparked a surge of applications over the last decade, ranging from optical communications to metrology. Despite their diverse deployment, most microcomb-based systems rely on a tremendous amount of bulk equipment to fulfill…
The success of LTE Heterogeneous Networks (HetNets) with macro cells and pico cells critically depends on efficient spectrum sharing between high-power macros and low-power picos. Two important challenges in this context are, {(i)}…
Domain-specific machine learning (ML) accelerators such as Google's TPU and Apple's Neural Engine now dominate CPUs and GPUs for energy-efficient ML processing. However, the evolution of electronic accelerators is facing fundamental limits…
A central challenge in developing quantum computers and long-range quantum networks lies in the distribution of entanglement across many individually controllable qubits. Colour centres in diamond have emerged as leading solid-state…
For a system-level design of Networks-on-Chip for 3D heterogeneous System-on-Chip (SoC), the locations of components, routers and vertical links are determined from an application model and technology parameters. In conventional methods,…
Learning-based image compression has improved to a level where it can outperform traditional image codecs such as HEVC and VVC in terms of coding performance. In addition to good compression performance, device interoperability is essential…
Photonic chips can miniaturize complicate optical systems very tiny and portable, providing versatile functionalities for many optical applications. Increasing the photonic chip integration density is highly desired as it provides more…
Overheating has emerged as a primary challenge constraining the reliability and performance of next-generation high-performance electronics, such as chiplets and (ultra)wide bandgap electronics. Advanced heterogeneous integration not only…
Modern microelectronic processors have migrated towards parallel computing architectures with many-core processors. However, such expansion comes with diminishing returns exacted by the high cost of data movement between individual…
Co-Packaged Optics applications require scalable and high-yield optical interfacing solutions to silicon photonic chiplets, offering low-loss, broadband, and polarization-independent optical coupling while maintaining compatibility with…
Combining the long-coherence of spin qubits and the capability to transmit information and entanglement through photons, spin-photon interfaces (SPIs) are a promising platform for networked quantum computation and long-distance quantum…
Heterogeneous interfaces are central to many energy-related applications in the nanoscale. From the first-principles electronic structure perspective, one of the outstanding problems is accurately and efficiently calculating how the…
Efficient machine learning inference is essential for the rapid adoption of artificial intelligence across various domains.On-chip optical computing has emerged as a transformative solution for accelerating machine learning tasks, owing to…
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…
Silicon photonic devices are poised to enter high volume markets such as data-communications, telecommunications, biological sensing, and optical phased arrays; however, permanently attaching a fiber to the photonic chip with high optical…
Integrated nonlinear photonic circuits received rapid development in recent years, providing all-optical functionalities enabled by cavity-enhanced photon-photon interaction for classical and quantum applications. A high-efficiency…
Integrated photonic platforms have proliferated in recent years, each demonstrating its own unique strengths and shortcomings. However, given the processing incompatibilities of different platforms, a formidable challenge in the field of…
Spectrum manipulation is central to photonic systems, where advanced computing and sensing applications often demand highly complex spectral responses to achieve high throughput. Conventional methods for enhancing spectral complexity…
Recent advances in cold atom interferometry with optical and magnetic atom guides have set the stage for quantum inertial sensors capable of operating in dynamic environments. In this work, we present three key innovations, such as…
Heterointerfaces have been pivotal in unveiling extraordinary interfacial properties and enabling multifunctional material platforms. Despite extensive research on all-oxide interfaces, heterointerfaces between different material classes,…