PIC: Hybrid Photonic-Electronic Reprogrammable Reservoir Computing with Polarization Modes-enhanced Dimensionality

PIC：具有偏振模式增强维数的混合光子-电子可重编程储层计算

• 批准号: 2217453
• 负责人: Yeshaiahu Fainman
• 金额: $ 42万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-15 至 2026-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2217453&HistoricalAwards=false
• 关键词: PIC; Hybrid; Photonic; Electronic; Reprogrammable

The recent success of Machine Learning methods based on brain-inspired Neuromorphic Computing (NC) to perform complex information processing tasks spiked significant research in new unconventional computational schemes such as Recurrent Neural Networks (RNNs) and RNN-based Reservoir Computing (RC) which are capable to implement parallel data processing to overcome limitations of conventional sequential computing. Particularly, decomposing the reservoir into an inner network with static weights and an output neurons layer with adaptive and trainable weights allows realization of physical RC where optical-based RC platforms are attractive due to the “speed-of-light” propagation, inherent parallelism, relatively low operation power, and the possibility to harness additional degrees of freedom such as polarization and wavelength. Furthermore, on-chip Photonic Integrated Circuit (PIC) offer enhanced light-matter interaction and modes polarization for enlarged reservoir, and interconnection with CMOS compatible electronics for power efficient electrical reprogrammable feedback. The proposed physical RC PICs are expected to impact mobile applications such as unmanned autonomous vehicles (UAV) and robotic platforms by reducing the need for communication with remote computers, thus avoiding latency and prolonging battery life.(technical description) To realize the reservoir computing (RC) processor utilizing the polarization degrees of freedom on a photonic integrated chip (PIC), we propose the following objectives: (1) numerical and theoretical study aiming to explore the effect of introducing polarization as a new degree of freedom on RC efficiency depending on the underlying architecture of PIC with the electronic feedback elements providing dynamics control; (2) design, fabricate and characterize silicon PIC interconnected with external electronic feedback, admitting the designed architectures; (3) experimentally test the PIC system with external electronic feedback to realize reprogrammable RC tasks, validate the theoretical study and evaluate its performance for relevant applications providing higher accuracy and lower energy consumption compared to state-of-the-art. Rapid prototyping and testing will be performed at UCSD with full scale runs performed at the AIM Photonics foundry. The proposed research is transformative in nature as it will: (i) greatly expand the limits of applicability of RC in CMOS compatible PIC platforms, (ii) develop a fundamental understanding on the effect of reprogrammability on the induced reservoir dynamics and the corresponding performance error, (iii) expand the current notions of both RC and the optical degrees of freedom employed for RC (e.g., polarization). The transformative broader impact of the project arises from the creation of a new much faster and more efficient RC PIC accelerator that will impact mobile applications such as UAV and robotic platforms. The project will provide scientific training for students at graduate and undergraduate levels as well as serve as a basis for outreach, education and collaborative efforts with middle and high schools. Engagement of students of diverse ethnicity, gender and economic backgrounds in Science, Technology, Engineering and Mathematics (STEM) will be continued via the ongoing RET, REU, and COSMOS activities. The program will continue developing a plug & play Integrated Photonics Education Kit (IPEK) and disseminate it to other institutions to implement hands-on classes for a large number of students with diverse origins and gender, and workforce population in the U.S.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

基于脑启发的神经形态计算（NC）执行复杂信息处理任务的机器学习方法的最新成功在新的非常规的计算方案（例如复发性神经网络（RNN）和基于RNN的基于RNN的储藏计算（RC）中，跨越了大量研究，这些计算能够实施相关数据的序列限制性限制。尤其是，将储层分解为具有静态重量的内部网络和具有自适应和可训练重量的输出神经元层，可以实现物理RC，基于光学的RC平台由于“光线速度”的传播，相对低操作的功率，以及诸如pallavel和pallavel andergements的自由度之外的可能性。此外，片上光子集成电路（PIC）提供了增强的光 - 物质相互作用，并具有极化的模式，以增加储层，并与CMOS兼容电子设备互连，以提供电力有效的电气重编程反馈。 The proposed physical RC PICs are expected to impact mobile applications such as unmanned autonomous vehicles (UAV) and robotic platforms by reducing the need for communication with remote computers, thus avoiding latency and prolonging battery life.(technical description) To realize the reservoir computing (RC) processor utilizing the polarization degrees of freedom on a photonic integrated chip (PIC), we propose the following objectives: (1) numerical and理论研究旨在探索将极化作为新的自由度对RC效率的新效果，具体取决于PIC的基础结构，其电子反馈元素提供动态控制； （2）设计，制造和表征与外部电子反馈相互联系的硅图片，并承认设计的体系结构； （3）通过外部电子反馈实验测试PIC系统，以实现可重编程的RC任务，验证理论研究并评估其针对相关应用的性能，从而提供了更高的准确性和较低的能源消耗。快速原型制作和测试将在UCSD上进行，并在AIM Photonics Foundry进行全尺度运行。拟议的研究本质上是变革性的：（i）大大扩展了RC在CMOS兼容PIC平台中的适用性限制，（ii）对重编程对诱导的储层动力学和相应性能错误的影响有了基本的理解，并且相应的性能错误，（iii）扩展了RC和光学自由度的当前注释。该项目的变革性广播公司的影响源于创建一个更快，更高效的RC PIC加速器的新型，该加速器将影响移动应用程序，例如无人机和机器人平台。该项目将为研究生和本科生的学生提供科学培训，并作为与中学和高中的外展，教育和协作努力的基础。将通过正在进行的RET，REU和COSMOS活动继续参与科学，技术，工程和数学（STEM）中的潜水员，性别和经济背景的学生。该计划将继续开发插件综合光子学教育套件（IPEK），并将其传播给其他机构，以为许多具有潜水员起源和性别的学生实施动手课程，以及美国奖项中的劳动力人口反映了NSF的法定任务，并认为通过基金会的知识优点和广泛的criperia criperia criperia criperia criperia criperia criptia criperia被视为珍贵的支持。

项目成果

Vertical-cavity surface-emitting phase shifter

垂直腔面发射移相器

• DOI: 10.1364/oe.497606
• 发表时间: 2023
• 期刊: Optics Express
• 影响因子: 3.8
• 作者: Almutairi, Dhaifallah;Johnson, Karl;Smolyaninov, Alexei;Grieco, Andrew;Fainman, Yeshaiahu
• 通讯作者: Fainman, Yeshaiahu

Multirate Spectral Domain Optical Coherence Tomography

• DOI: 10.1109/jphot.2023.3313521
• 发表时间: 2023-10-01
• 期刊: IEEE PHOTONICS JOURNAL
• 影响因子: 2.4
• 作者: Gaur，Prabhav;Grieco，Andrew;Fainman，Yeshaiahu
• 通讯作者: Fainman，Yeshaiahu

Compensation of Kerr-induced impairments in silicon nitride third-harmonic generators

氮化硅三次谐波发生器中克尔引起的损伤的补偿

• DOI: 10.1364/oe.479059
• 发表时间: 2023
• 期刊: Optics Express
• 影响因子: 3.8
• 作者: Chen, Zijun;Fainman, Yeshaiahu
• 通讯作者: Fainman, Yeshaiahu