Analogue computing with metamaterials

超材料 计算机科学 巨量平行 信号处理 非常规计算 油藏计算 光学计算 光子学 模拟计算机 计算 计算复杂性理论 电子工程 计算机工程 计算科学 数字信号处理 人工智能 计算机硬件 分布式计算 并行计算 电气工程 物理 算法 人工神经网络 光学 工程类 循环神经网络 光电子学
作者
Farzad Zangeneh-Nejad,Dimitrios L. Sounas,Andrea Alù,Romain Fleury
出处
期刊:Nature Reviews Materials [Springer Nature]
卷期号:6 (3): 207-225 被引量:185
标识
DOI:10.1038/s41578-020-00243-2
摘要

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.
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