Multi-Span Optical Power Spectrum Evolution Modeling using ML-based Multi-Decoder Attention Framework

Raj, Agastya, Wang, Zehao, Slyne, Frank, Chen, Tingjun, Kilper, Dan, Ruffini, Marco

arXiv.org Artificial Intelligence 

We implement a ML-based attention framework with component-specific decoders, improving optical power spectrum prediction in multi-span networks. By reducing the need for in-depth training on each component, the framework can be scaled to multi-span topologies with minimal data collection, making it suitable for brown-field scenarios.