Engineers created light-activated materials that execute precise movements and form complex shapes without the need for wires, motors or other energy sources. The research could lead to smart light-driven systems such as high-efficiency solar cells that automatically follow the sun’s direction.
Researchers from the University of Bristol’s Quantum Engineering Technology Labs (QET Labs) and Université Côte d‘Azur have made a new miniaturized light detector to measure quantum features of light in more detail than ever before. The device, made from two silicon chips working together, was used to measure the unique properties of “squeezed” quantum light at record high speeds.
Machine learning performed by neural networks is a popular approach to developing artificial intelligence, as researchers aim to replicate brain functionalities for a variety of applications. A paper in the journal Applied Physics Reviews proposes a new approach to perform computations required by a neural network, using light instead of electricity. In this approach, a photonic tensor core performs multiplications of matrices in parallel, improving speed and efficiency of current deep learning paradigms.