可编程光子频率电路的现场训练

IF 6.6 2区 物理与天体物理 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Philip Rübeling, Oleksandr V. Marchukov, Filipe F. Bellotti, Ulrich B. Hoff, Nikolaj T. Zinner, Michael Kues
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引用次数: 0

摘要

光学人工神经网络(oann)利用光子技术的优势,包括高处理速度、低能耗和大规模生产,为机器学习应用建立了一个具有竞争力和可扩展的平台。虽然最近的进展主要集中在利用光的空间或时间模式,但频域吸引了很多关注,目前的实现包括频谱复用、非线性光学系统中的神经网络和极限学习机器。在这里,我们提出了一种可编程光子频率电路的实验实现,该电路由光纤元件实现,并实现了在频域工作的OANN的光权控制的原位训练。输入数据被编码成频率梳模式的相位,频谱模式的可编程相位和幅度操作可以实现OANN的原位训练,而无需采用设备的数字模型。经过训练的OANN实现了超过90%的多类分类准确率,与传统的机器学习方法相当。这一概念验证证明了多层OANN在频域的可行性,并且可以扩展到具有超快速权重更新的可扩展集成光子平台,具有在光谱学单次分类中的潜在应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
In-situ training in programmable photonic frequency circuits
Optical artificial neural networks (OANNs) leverage the advantages of photonic technologies including high processing speeds, low energy consumption, and mass production to establish a competitive and scalable platform for machine learning applications. While recent advancements have focused on harnessing spatial or temporal modes of light, the frequency domain attracts a lot of attention, with current implementations including spectral multiplexing, neural networks in nonlinear optical systems and extreme learning machines. Here, we present an experimental realization of a programmable photonic frequency circuit, realized with fiber-optical components, and implement the in-situ training with optical weight control of an OANN operating in the frequency domain. Input data is encoded into phases of frequency comb modes, and programmable phase and amplitude manipulations of the spectral modes enable in-situ training of the OANN, without employing a digital model of the device. The trained OANN achieves multiclass classification accuracies exceeding 90 %, comparable to conventional machine learning approaches. This proof-of-concept demonstrates the feasibility of a multilayer OANN in the frequency domain and can be extended to a scalable, integrated photonic platform with ultrafast weights updates, with potential applications to single-shot classification in spectroscopy.
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来源期刊
Nanophotonics
Nanophotonics NANOSCIENCE & NANOTECHNOLOGY-MATERIALS SCIENCE, MULTIDISCIPLINARY
CiteScore
13.50
自引率
6.70%
发文量
358
审稿时长
7 weeks
期刊介绍: Nanophotonics, published in collaboration with Sciencewise, is a prestigious journal that showcases recent international research results, notable advancements in the field, and innovative applications. It is regarded as one of the leading publications in the realm of nanophotonics and encompasses a range of article types including research articles, selectively invited reviews, letters, and perspectives. The journal specifically delves into the study of photon interaction with nano-structures, such as carbon nano-tubes, nano metal particles, nano crystals, semiconductor nano dots, photonic crystals, tissue, and DNA. It offers comprehensive coverage of the most up-to-date discoveries, making it an essential resource for physicists, engineers, and material scientists.
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