Variable Bit-Width All-Optical Content-Addressable Memory Enabled by Sb2Se3 for Similarity Search

In the AI era of big data explosion, similarity search—a core task in machine learning and data mining—requires high speed, energy efficiency, and scenario adaptability. Conventional electronic CAMs face RC delay bottlenecks, while existing OCAMs are limited by fixed bit-widths and limited distance metrics. Here, we demonstrate a variable bit-width all-optical CAM architecture employing phase-change material Sb₂Se₃ integrated with Mach-Zehnder Interferometers (MZIs). The proposed multi-segment memory unit (MSMU) compresses N-bit binary data into a single analog photonic unit, supporting direct data writing/loading without DACs and flexible trade-offs between precision, storage capacity, noise immunity, and energy, while enabling Hamming and non-linear (NL) distance calculations. A 6-element 3-bit OCAM fabricated on a SiN-SOI platform realizes reliable storage and retrieval. kNN simulations on iris, wine, and breast cancer datasets show that the 3-bit mode achieves accuracy comparable to Manhattan/Euclidean distances under high SNR, while the 1-bit mode offers robust noise immunity. Energy consumption is 364 fJ/bit (3-bit) and 890 fJ/bit (1-bit). This architecture provides a high-speed, energy-efficient, and flexible all-optical similarity search solution, promising wide applications in machine learning and data mining.