Quantifying Power in Silicon Photonic Neural Networks

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Tait, Alexander N. “Quantifying Power in Silicon Photonic Neural Networks”. Physical Review Applied, vol. 17, no. 5, 2022, https://doi.org/10.1103/physrevapplied.17.054029.
Tait, A. N. (2022). Quantifying Power in Silicon Photonic Neural Networks. Physical Review Applied, 17(5). https://doi.org/10.1103/physrevapplied.17.054029
Tait AN. Quantifying Power in Silicon Photonic Neural Networks. Physical Review Applied. 2022;17(5).
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Refrences
Title Journal Journal Categories Citations Publication Date
10.1201/9781315370590 2017
10.1109/JSTQE.2019.2941485
10.1109/JLT.2014.2345652
10.1109/JSSC.2020.3022851
Linearized modulator for suboctave-bandpass optical analog links IEEE Transactions on Microwave Theory and Techniques
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
 69 1994
Citations
Title Journal Journal Categories Citations Publication Date
Coherent Photonic Crossbar Arrays for Large-Scale Matrix-Matrix Multiplication IEEE Journal of Selected Topics in Quantum Electronics
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Science: Physics
  • Science: Physics: Optics. Light
  • Science: Physics
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Chemical technology
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Materials of engineering and construction. Mechanics of materials
 2 2023
Optical and Electrical Memories for Analog Optical Computing IEEE Journal of Selected Topics in Quantum Electronics
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Science: Physics
  • Science: Physics: Optics. Light
  • Science: Physics
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Chemical technology
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Materials of engineering and construction. Mechanics of materials
 2023
Citations Analysis
Category Category Repetition
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks2
Science: Physics2
Science: Physics: Optics. Light2
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics2
Technology: Chemical technology2
Technology: Electrical engineering. Electronics. Nuclear engineering: Materials of engineering and construction. Mechanics of materials2
The category Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks 2 is the most commonly referenced area in studies that cite this article.