Multimodal deep learning plays a pivotal role in supporting the processing and learning of
diverse data types within the realm of artificial intelligence generated content (AIGC) …

The demand for accurate perception of the physical world leads to a dramatic increase in
sensory nodes. However, the transmission of massive and unstructured sensory data from …

Integrated photonic neural networks (PNNs) are at the forefront of AI computing, leveraging
light's unique properties, such as large bandwidth, low latency, and potentially low power …

Monolithic integration of novel materials without modifying the existing photonic component
library is crucial to advancing heterogeneous silicon photonic integrated circuits. Here we …

Every multi-input multi-output linear optical system can be deemed as a matrix multiplier that
carries out a desired transformation on the input optical information, such as imaging …

With the rapid development of the Internet of Things, how to efficiently store, transmit, and
process massive amounts of data has become a major challenge now. Optical neural …

In the development of silicon photonics, the continued downsizing of photonic integrated
circuits will further increase the integration density, which augments the functionality of …

摘要光学神经网络是区别于冯· 诺依曼计算架构的一种高性能新型计算范式, 具有低延时,
低功耗, 大带宽以及并行信号处理等优势. 片上集成是光学神经网络微型化发展的一种典型方式 …

Bragg gratings offer high-performance filtering and routing of light on-chip through a periodic
modulation of a waveguide's effective refractive index. Here, we model and experimentally …

Silicon photonics arises as a viable solution to address the stringent resource demands of
emergent technologies, such as neural networks. Within this framework, photonic memories …