Integrated Platforms and Techniques for Photonic Neural Networks

Abstract

Review of integrated photonic platforms for constructing neural networks, covering the advantages of photons over electrons as information carriers: ultrafast processing, ultra-low energy consumption, and extremely high throughput.

Key Contributions

• Maps the landscape of photonic integrated circuit platforms for neural networks
• Compares silicon photonics, III-V semiconductors, polymer, and hybrid approaches
• Analyzes trade-offs between integration density, power efficiency, and manufacturability
• Advances in photonic integrated circuits provide compact, reliable hardware for PNNs

Results

Photonic neural networks exploit light's inherent parallelism, sub-nanosecond latency, and near-zero thermal losses for matrix operations. Key challenge remains achieving sufficient nonlinearity on-chip for deep network architectures.

Source: Integrated Platforms for Photonic Neural Networks — npj Nanophotonics