Abstract

A perspective on how machine learning can aid the next–generation of classical and quantum optical communication systems is given. We focus on the design of Raman amplifiers and phase tracking at the quantum limit.

© 2020 The Author(s)

PDF Article
More Like This
Machine Learning in Quantum Communication

Max Rückmann, Sebastian Kleis, Christian G. Schaeffer, and Darko Zibar
SpTu3I.6 Signal Processing in Photonic Communications (SPPCom) 2020

Machine learning concepts in coherent optical communication systems

Darko Zibar and Christian Schäffer
ST2D.1 Signal Processing in Photonic Communications (SPPCom) 2014

Workshop on Machine Learning for Optical Communication Systems: a summary

Josh Gordon, Abdella Battou, and Dan Kilper
M3E.3 Optical Fiber Communication Conference (OFC) 2020

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription