Analogue computing with metamaterials

By Farzad Zangeneh-Nejad, Dimitrios L. Sounas, Andrea Alù, R. Fleury. Nature Reviews Materials, 2020

380 citations recorded by the source corpus.

Despite their widespread use for performing advanced computational tasks, digital signal processors suffer from several restrictions, including low speed, high power consumption and complexity, caused by costly analogue-to-digital converters. For this reason, there has recently been a surge of interest in performing wave-based analogue computations that avoid analogue-to-digital conversion and allow massively parallel operation. In particular, novel schemes for wave-based analogue computing have been proposed based on artificially engineered photonic structures, that is, metamaterials. Such kinds of computing systems, referred to as computational metamaterials, can be as fast as the speed of light and as small as its wavelength, yet, impart complex mathematical operations on an incoming wave packet or even provide solutions to integro-differential equations. These much-sought features promise to enable a new generation of ultra-fast, compact and efficient processing and computing hardware based on light-wave propagation. In this Review, we discuss recent advances in the field of computational metamaterials, surveying the state-of-the-art metastructures proposed to perform analogue computation. We further describe some of the most exciting applications suggested for these computing systems, including image processing, edge detection, equation solving and machine learning. Finally, we provide an outlook for the possible directions and the key problems for future research. Metamaterials provide a platform to leverage optical signals for performing specific-purpose computational tasks with ultra-fast speeds. This Review surveys the basic principles, recent advances and promising future directions for wave-based-metamaterial analogue computing systems.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/bd0388921c784f4cdfdba7eb7eeeebc00c776817

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In Artificial Intelligence

In Atomic and Molecular Physics, and Optics

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Citations in the corpus

Roadmap on spatiotemporal light fields (2022, background): “On the other hand, the all-optical computations of time-domain differentiations were realized based on on-chip ring resonators, fiber gratings, and cross-gain modulation, and proposed as all-optical differential equation solvers or pulse reshapers for sensing and control [150].”
Nonlocal flat optics (2022, background): “the system, is directly engineered to match the Fourier transform of the desired spatial operator [25],[42].”