Controlling electromagnetic waves and information simultaneously by information
metasurfaces is of central importance in modern society. Intelligent metasurfaces are smart …

Despite their widespread use for performing advanced computational tasks, digital signal
processors suffer from several restrictions, including low speed, high power consumption …

Deep-learning models have become pervasive tools in science and engineering. However,
their energy requirements now increasingly limit their scalability. Deep-learning …

Future wireless networks are expected to constitute a distributed intelligent wireless
communications, sensing, and computing platform, which will have the challenging …

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 …

Optical techniques offer a wide variety of applications as light-matter interactions provide
extremely sensitive mechanisms to probe or treat target media. Most of these …

We present wave-based signal differentiation with unprecedented fidelity and flexibility by
purposefully perturbing overmoded random scattering systems such that zeros of their …

Complex and inhomogeneous media are ubiquitous around us. Snow, fog, biological
tissues and turbid water—even just a piece of frosted glass—are opaque to light due to …

Training an artificial neural network with backpropagation algorithms to perform advanced
machine learning tasks requires an extensive computational process. This paper proposes …

Recent successes in deep learning for vision and natural language processing are
attributed to larger models but come with energy consumption and scalability issues. Current …