Memristors in electronics have shown the potential for a range of applications, ranging from
circuit elements to neuromorphic computing. In recent years, the ability to vary the …

Semiconductor plasmonics has become a frontier for light manipulation beyond the
diffraction limit, offering a broader spectral range and higher flexibility of plasmon …

Silicon photonics is evolving from laboratory research to real-world applications with the
potential to transform many technologies, including optical neural networks and quantum …

Phase-change materials (PCMs) offer a compelling platform for active metaoptics, owing to
their large index contrast and fast yet stable phase transition attributes. Despite recent …

Abstract Machine learning technologies have been extensively applied in high-performance
information-processing fields. However, the computation rate of existing hardware is …

Optical phase shifters constitute the fundamental building blocks that enable programmable
photonic integrated circuits (PICs)—the cornerstone of on-chip classical and quantum …

A novel class of programmable integrated photonic circuits has emerged over the past
years, strongly driven by approaches to tackle unsolved computing problems in the optical …

The biological visual system encodes optical information into spikes and processes them by
the neural network, which enables the perception with high throughput of visual processing …

The traditional ways of tuning a silicon photonic network are mainly based on the thermo-
optic effect or the free carrier dispersion. The drawbacks of these methods are the volatile …

The photonic in-memory computing architecture based on phase change materials (PCMs)
is increasingly attracting widespread attention due to its high computational efficiency and …