Today's telecommunication networks have become sources of enormous amounts of widely
heterogeneous data. This information can be retrieved from network traffic traces, network …

Lithium niobate (LiNbO 3 or LN) is a well-known multifunctional crystal that has been widely
applied in various areas of photonics, electronics, and optoelectronics. In the past …

Complex-valued neural networks have many advantages over their real-valued
counterparts. Conventional digital electronic computing platforms are incapable of executing …

Deep learning has become a widespread tool in both science and industry. However,
continued progress is hampered by the rapid growth in energy costs of ever-larger deep …

Retrieving the pupil phase of a beam path is a central problem for optical systems across
scales, from telescopes, where the phase information allows for aberration correction, to the …

Optical computing promises to improve the speed and energy efficiency of machine learning
applications,,,,–. However, current approaches to efficiently train these models are limited by …

Computational meta-optics brings a twist on the accelerating hardware with the benefits of
ultrafast speed, ultra-low power consumption, and parallel information processing in …

Artificial neural networks (ANNs) have been widely used for industrial applications and have
played a more important role in fundamental research. Although most ANN hardware …

We review a novel paradigm that has emerged in analogue neuromorphic optical
computing. The goal is to implement a reservoir computer in optics, where information is …

Implementing on-chip non-volatile photonic memories has been a long-term, yet elusive
goal. Photonic data storage would dramatically improve performance in existing computing …