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Analogue computing with metamaterials
Nature Reviews Materials ( IF 79.8 ) Pub Date : 2020-10-19 , DOI: 10.1038/s41578-020-00243-2
Farzad Zangeneh-Nejad , Dimitrios L. Sounas , Andrea Alù , Romain Fleury

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.



中文翻译:

超材料的模拟计算

尽管数字信号处理器广泛地用于执行高级计算任务,但由于昂贵的模数转换器而导致其受到一些限制,包括低速,高功耗和复杂性。由于这个原因,最近在执行基于波的模拟计算方面引起了人们的兴趣,这些计算避免了模数转换并允许大规模并行操作。尤其是,已经提出了基于人工设计的光子结构,即超材料的基于波的模拟计算的新方案。这种类型的计算系统(称为计算超材料)可以与光速一样快,而与波长一样小,但是,在输入波包上进行复杂的数学运算,甚至提供积分微分方程的解。这些备受期待的功能有望使基于光波传播的新一代超快速,紧凑和高效的处理和计算硬件成为可能。在这篇综述中,我们讨论了计算超材料的最新进展,并调查了提出进行模拟计算的最先进的元结构。我们进一步描述了针对这些计算系统建议的一些最令人兴奋的应用程序,包括图像处理,边缘检测,方程求解和机器学习。最后,我们对可能的方向和未来研究的关键问题提供了展望。基于光波传播的紧凑高效的处理和计算硬件。在这篇综述中,我们讨论了计算超材料的最新进展,并调查了提出进行模拟计算的最先进的元结构。我们进一步描述了针对这些计算系统建议的一些最令人兴奋的应用程序,包括图像处理,边缘检测,方程求解和机器学习。最后,我们对可能的方向和未来研究的关键问题提供了展望。基于光波传播的紧凑高效的处理和计算硬件。在这篇综述中,我们讨论了计算超材料的最新进展,并调查了提出进行模拟计算的最先进的元结构。我们进一步描述了针对这些计算系统建议的一些最令人兴奋的应用程序,包括图像处理,边缘检测,方程求解和机器学习。最后,我们对可能的方向和未来研究的关键问题提供了展望。我们进一步描述了针对这些计算系统建议的一些最令人兴奋的应用程序,包括图像处理,边缘检测,方程求解和机器学习。最后,我们对可能的方向和未来研究的关键问题提供了展望。我们进一步描述了针对这些计算系统建议的一些最令人兴奋的应用程序,包括图像处理,边缘检测,方程求解和机器学习。最后,我们对可能的方向和未来研究的关键问题提供了展望。

更新日期:2020-10-19
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