Optical microcombs represent a new paradigm for generating laser frequency combs based
on compact chip-scale devices, which have underpinned many modern technological …

Despite technical efforts and upgrades, advances in complementary metal–oxide–
semiconductor circuits have become unsustainable in the face of inherent silicon limits. New …

The development of artificial intelligence is typically focused on computer algorithms and
integrated circuits. Recently, all-optical diffractive deep neural networks have been created …

Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …

Matrix computation, as a fundamental building block of information processing in science
and technology, contributes most of the computational overheads in modern signal …

Large-scale, highly integrated and low-power-consuming hardware is becoming
progressively more important for realizing optical neural networks (ONNs) capable of …

Microcombs have sparked a surge of applications over the past decade, ranging from optical
communications to metrology,,–. Despite their diverse deployment, most microcomb-based …

Magnonics addresses the physical properties of spin waves and utilizes them for data
processing. Scalability down to atomic dimensions, operation in the GHz-to-THz frequency …

Integrated silicon photonics has sparked a significant ramp-up of investment in both
academia and industry as a scalable, power-efficient, and eco-friendly solution. At the heart …

Deep neural networks with applications from computer vision to medical diagnosis,,,–are
commonly implemented using clock-based processors,,,,,,,–, in which computation speed is …