Machine Learning Framework for Loss Range Prediction of Hollow-core Anti-resonant Fibers

Abstract

A supervised machine learning framework is implemented to predict the propagation loss of randomly structured nested hollow-core anti-resonant fiber for the first time. The random forest classifier outperforms other methods in accurately predicting the loss.