Excitable logic for photonic information processing

光子信息处理的可兴奋逻辑

基本信息

  • 批准号:
    543613-2019
  • 负责人:
  • 金额:
    $ 1.82万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Engage Grants Program
  • 财政年份:
    2019
  • 资助国家:
    加拿大
  • 起止时间:
    2019-01-01 至 2020-12-31
  • 项目状态:
    已结题

项目摘要

Electronic systems are ubiquitously employed in highly-demanding data processing and computing applications; however, they are prone to numerous drawbacks related to security. While a scalable, general purpose digital optical computing processor has remained elusive, the demonstration of reconfigurable all-optical gates for specialized tasks such as in secure computing is attractive because optical devices neither generate an electromagnetic (EM) signature which can be observed from a distance nor can be jammed by external EM interference, hence posing less risk than their electronic counterparts. There is a pressing need to investigate optical logic using a single device, which is robust enough to operate in a rugged military environment while having the potential to increase computing speed. The objective of this project is to design, build and demonstrate a reconfigurable optical gate with a single device for ultrafast information processing. Specifically, the goal is to develop a reconfigurable AND/NOT logic device by engineering the dynamics of a graphene-based laser based on the principle of excitability (a non-linear dynamical mechanism underlying all-or-none responses to small perturbations). Excitability has been shown to enable thresholding and cascadability of photonic devices, while graphene has unique optical properties that are particularly useful in the context of processing, including a ultrafast response time, wideband frequency tunability, and a tunable modulation depth. Successful implementation of a reconfigurable optical logical gate with a single device, as envisioned here, would provide the fundamental technology to build larger scale networks that operate on principles of excitable logic, which could have potential applications in electronic warfare, sensing, physical layer security, military computing, and space applications.
电子系统广泛应用于高要求的数据处理和计算应用中;然而,它们容易出现许多与安全相关的缺点。虽然可扩展的通用数字光学计算处理器仍然难以捉摸,但用于安全计算等专门任务的可重构全光门的演示很有吸引力,因为光学设备既不会产生可以从远处观察到的电磁(EM)特征,也不会受到外部电磁干扰的干扰,因此比电子设备带来的风险更小。迫切需要使用单个设备来研究光学逻辑,该设备足够强大,可以在恶劣的军事环境中运行,同时具有提高计算速度的潜力。该项目的目标是设计、构建和演示一个可重新配置的光闸,使用单个设备进行超快信息处理。具体来说,我们的目标是通过基于兴奋性原理(一种对小扰动全或无响应的非线性动力学机制)设计石墨烯基激光器的动力学,开发可重构的“与/非”逻辑器件。兴奋性已被证明可以实现光子器件的阈值化和级联性,而石墨烯具有独特的光学特性,在处理环境中特别有用,包​​括超快响应时间、宽带频率可调性和可调调制深度。正如这里所设想的,用单个设备成功实现可重构光逻辑门将为构建按照可激励逻辑原理运行的更大规模网络提供基础技术,这可能在电子战、传感、物理层安全、军事计算和空间应用中具有潜在的应用。

项目成果

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Shastri, Bhavin其他文献

Advances in photonic neuromorphic computing (Conference Presentation)
光子神经形态计算的进展(会议演讲)
  • DOI:
    10.1117/12.2509838
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sorger, Volker J.;George, Jonathan K.;Mehrabian, Armin;Shastri, Bhavin;El-Ghazawi, Tarek;Prucnal, Paul R.;Lee, El-Hang;He, Sailing
  • 通讯作者:
    He, Sailing

Shastri, Bhavin的其他文献

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{{ truncateString('Shastri, Bhavin', 18)}}的其他基金

Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
用于深度学习和神经形态计算的可编程纳米光子学
  • 批准号:
    RGPIN-2018-05249
  • 财政年份:
    2022
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Cryogenic system for the exploration of low-temperature neuromorphic photonic systems
用于探索低温神经形态光子系统的低温系统
  • 批准号:
    RTI-2022-00457
  • 财政年份:
    2021
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Research Tools and Instruments
Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
用于深度学习和神经形态计算的可编程纳米光子学
  • 批准号:
    RGPIN-2018-05249
  • 财政年份:
    2021
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
用于深度学习和神经形态计算的可编程纳米光子学
  • 批准号:
    RGPIN-2018-05249
  • 财政年份:
    2020
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Neurophotonic-electronic brain-machine interface system
神经光子电子脑机接口系统
  • 批准号:
    RTI-2020-00407
  • 财政年份:
    2019
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Research Tools and Instruments
Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
用于深度学习和神经形态计算的可编程纳米光子学
  • 批准号:
    RGPIN-2018-05249
  • 财政年份:
    2019
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
用于深度学习和神经形态计算的可编程纳米光子学
  • 批准号:
    RGPIN-2018-05249
  • 财政年份:
    2018
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
用于深度学习和神经形态计算的可编程纳米光子学
  • 批准号:
    DGECR-2018-00208
  • 财政年份:
    2018
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Launch Supplement
Photonic cortical processor using graphene and silicon nanophotonics for complex systems analysis
使用石墨烯和硅纳米光子学进行复杂系统分析的光子皮质处理器
  • 批准号:
    469008-2014
  • 财政年份:
    2015
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Banting Postdoctoral Fellowships Tri-council
Photonic cortical processor using graphene and silicon nanophotonics for complex systems analysis
使用石墨烯和硅纳米光子学进行复杂系统分析的光子皮质处理器
  • 批准号:
    469008-2014
  • 财政年份:
    2014
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Banting Postdoctoral Fellowships Tri-council

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