Optical Loss

Optical loss, and its associated crosstalk noise, represent significant challenges in the development of silicon-photonic neural networks (SP-NNs). Current research focuses on comprehensive modeling of these losses across various SP-NN architectures, such as those based on Mach-Zehnder interferometers (MZIs), to understand their impact on inferencing accuracy and scalability. Studies reveal substantial performance degradation, highlighting the critical need for improved device fabrication and design strategies to mitigate these effects. Overcoming these limitations is crucial for realizing the potential of SP-NNs to deliver faster and more energy-efficient artificial intelligence applications.