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Abstract Microwave transversal filters, which are implemented based on the transversal filter structure in digital signal processing, offer a high reconfigurability for achieving a variety of signal processing functions without changing hardware. When implemented using microwave photonic (MWP) technologies, also known as MWP transversal filters, they provide competitive advantages over their electrical counterparts, such as large operation bandwidth, strong immunity to electromagnetic interference, and low loss when processing signals at high frequencies. Recent advances in high‐performance optical microcombs provide compact and powerful multi‐wavelength sources for MWP transversal filters that require a larger number of wavelength channels to achieve high performance, allowing for the demonstration of a diverse range of filter functions with improved performance and new features. Here, a comprehensive performance analysis for microcomb‐based MWP spectral filters based on the transversal filter approach is presented. First, the theoretical limitations are investigated in the filter spectral response induced by finite tap numbers. Next, the distortions are analyzed in the filter spectral response resulting from experimental error sources. Finally, the influence of input signal's bandwidth on the filtering errors is assessed. These results provide a valuable guide for the design and optimization of microcomb‐based MWP transversal filters for a variety of applications.

Abstract Signal processing has become central to many fields, from coherent optical telecommunications, where it is used to compensate signal impairments, to video image processing. Image processing is particularly important for observational astronomy, medical diagnosis, autonomous driving, big data and artificial intelligence. For these applications, signal processing traditionally has mainly been performed electronically. However these, as well as new applications, particularly those involving real time video image processing, are creating unprecedented demand for ultrahigh performance, including high bandwidth and reduced energy consumption. Here, we demonstrate a photonic signal processor operating at 17 Terabits/s and use it to process video image signals in real-time. The system processes 400,000 video signals concurrently, performing 34 functions simultaneously that are key to object edge detection, edge enhancement and motion blur. As compared with spatial-light devices used for image processing, our system is not only ultra-high speed but highly reconfigurable and programable, able to perform many different functions without any change to the physical hardware. Our approach is based on an integrated Kerr soliton crystal microcomb, and opens up new avenues for ultrafast robotic vision and machine learning.

Optical microcombs are compact photonic-chip-based devices able to produce precise optical frequency combs. However, these combs are often limited in power, which can provide issues for implementation, especially for optical communications. Here, we provide our perspective on the use of a suite of techniques and technologies we call “comb distillation,” to help enable high-power, low-noise microcombs.

Microwave photonic (MWP) signal processors, which process microwave signals based on photonic technologies, bring advantages intrinsic to photonics such as low loss, large processing bandwidth, and strong immunity to electromagnetic interference. Optical microcombs can offer a large number of wavelength channels and compact device footprints, which make them powerful multi-wavelength sources for MWP signal processors to realize a variety of processing functions. In this paper, we experimentally demonstrate the capability of microcomb-based MWP signal processors to handle diverse input signal waveforms. In addition, we quantify the processing accuracy for different input signal waveforms, including Gaussian, triangle, parabolic, super Gaussian, and nearly square waveforms. Finally, we analyse the factors contributing to the difference in the processing accuracy among the different input waveforms, and our theoretical analysis well elucidates the experimental results. These results provide guidance for microcomb-based MWP signal processors when processing microwave signals of various waveforms.

Microcombs provide many opportunities for integration in optical communications systems. Here, the authors implement a soliton crystal microcomb as a tool to demonstrate more than 44 Tb/s communications with high spectral efficiency.