Characterizing the transverse modes of optical fibers by singular value decomposition

A new approach to experimentally characterize the transverse modes of optical fibers is proposed in this submission. It analyzes a large volume of electric field data captured from the fiber under test and obtains the orthogonal modal base set of the fiber using the singular value decomposition. This procedure is similar to the principle of machine learning in the area of artificial intelligence. The results show a good agreement with the simulated transverse modes. Due to its operating principle, this approach can characterize any fiber regardless of its length and size.