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

Abstract

The need for high-speed, energy-efficient computing in machine learning and communications necessitates innovations beyond conventional electronics to sustain computational power advances without requiring prohibitive energy amounts. Photonics have emerged in various applications, demonstrating significant highlights in optical linear transformations, while if successfully employed can also be used in nonlinear processes and matching functionalities. Towards this we demonstrate nonlinear optical vector processing in the form of hamming distance calculations and content addressable memory banks, using linear silicon photonic circuits at the high-speed of 50 Gb/s, enabling pattern matching and look-up operations. The processor employs a 4×4 crossbar architecture utilizing silicon germanium modulators computing hamming distance between 2-bit optical vectors. It achieves error-rates of ~10⁻³ in binary/ternary content matching, improving state-of-the-art demonstration speeds by >2.5×. Scalability is enhanced through space-wavelength multiplexing via a wavelength-division multiplexing cell, experimentally demonstrated at 50 Gb/s, offering increased computational capacity with reduced insertion losses and power consumption.

Photonic technologies enable energy-efficient, high-speed computing, beyond electronics. The work shows nonlinear optical vector processing via linear transformations and wavelength multiplexing, for Hamming Distance and CAMs at 50 Gb/s, via silicon photonics.