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Nonlinear optical vector processing using linear silicon photonic circuits for 50 Gb/s memory and string similarity

T Moschos1,2, C Pappas3,4, S Kovaios3,4

  • 1Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece. moschost@csd.auth.gr.

Nature Communications
|December 17, 2025
PubMed
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This summary is machine-generated.

High-speed photonic processors perform nonlinear optical vector processing for machine learning. This silicon photonics approach enables faster pattern matching and look-up operations with improved energy efficiency.

Area of Science:

  • Photonics and optical computing
  • Silicon photonics for advanced computation
  • Nonlinear optical signal processing

Background:

  • Conventional electronics face limitations in speed and energy efficiency for machine learning and communications.
  • Photonics offer potential for high-speed, low-power computational tasks, including linear and nonlinear optical transformations.

Purpose of the Study:

  • To demonstrate nonlinear optical vector processing using silicon photonic circuits.
  • To enable high-speed pattern matching and look-up operations for machine learning and communications.

Main Methods:

  • Implementation of a 4x4 crossbar architecture with silicon germanium modulators.
  • Utilizing nonlinear optical vector processing for Hamming distance calculations between 2-bit optical vectors.

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  • Employing space-wavelength multiplexing with a wavelength-division multiplexing cell for scalability.

    • Main Results:

    • Achieved high-speed nonlinear optical vector processing at 50 Gb/s.
    • Demonstrated Hamming distance calculations and content addressable memory functionality.
    • Obtained error rates of approximately 10⁻³ in binary/ternary content matching, exceeding previous speeds by over 2.5 times.
    • Experimentally validated scalability using wavelength-division multiplexing, showing reduced losses and power consumption.

    Conclusions:

    • Silicon photonic processors can perform complex nonlinear optical vector operations at high speeds.
    • The demonstrated processor enables efficient pattern matching and look-up operations crucial for machine learning and communications.
    • Scalable photonic architectures offer a pathway to enhanced computational capacity with improved energy efficiency.