摘要翻译：
近年来，通过对材料性质的时空调制来实现非互易性和建立非互易分量，作为利用法拉第旋转来替代传统的磁性材料的方法，引起了人们的广泛关注。在这封信中，我们回顾了时空电导调制的最新研究，它使低损耗、小占地、宽带宽和高功率处理的非互易元件从射频(RF)到毫米波（mm-waves）工作，并集成在CMOS平台上。本文将回顾四代非互易环行器和基于环行器的系统。我们还将讨论对无线应用和标准非常重要的性能指标，并介绍一个新的天线(ANT)接口效率指标($\eta_{ANT}$)，以便能够公平地比较各种类型的天线接口。
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英文标题：
《Integrated Conductivity-Modulation-Based RF Magnetic-Free Non-Reciprocal
  Components: Recent Results and Benchmarking》
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作者：
Negar Reiskarimian, Aravind Nagulu, Tolga Dinc and Harish Krishnaswamy
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最新提交年份：
2018
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分类信息：

一级分类：Physics        物理学
二级分类：Applied Physics        应用物理学
分类描述：Applications of physics to new technology, including electronic devices, optics, photonics, microwaves, spintronics, advanced materials, metamaterials, nanotechnology, and energy sciences.
物理学在新技术中的应用，包括电子器件、光学、光子学、微波、自旋电子学、先进材料、超材料、纳米技术和能源科学。
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一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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英文摘要：
  Achieving non-reciprocity and building nonreciprocal components through spatio-temporal modulation of material properties has attracted a lot of attention in the recent past as an alternative to the more traditional approach of exploiting Faraday rotation in magnetic materials. In this letter, we review recent research on spatio-temporal conductivity-modulation, which enables low-loss, small-footprint, wide-bandwidth and high-power-handling non-reciprocal components operating from radio frequencies (RF) to millimeter-waves (mm-waves) and integrated in a CMOS platform. Four generations of non-reciprocal circulators and circulator-based systems will be reviewed. We will also discuss metrics of performance that are important for wireless applications and standards, and introduce a new antenna (ANT) interface efficiency figure of merit ($\eta_{ANT}$) to enable a fair comparison between various types of antenna interfaces.
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PDF链接：
https://arxiv.org/pdf/1805.11662