Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Learning of Laser Dynamics using Bayesian Inference

Not Accessible

Your library or personal account may give you access

Abstract

Techniques from Bayesian machine learning and digital coherent detection are applied to perform frequency noise characterization. Significant advantages of the presented techniques are high-sensitivity and direct access to the uncertainty of the frequency noise measurement.

© 2018 The Author(s)

PDF Article
More Like This
Performance Optimisation of Dual-Pump NALM Fibre Laser Using Machine Learning Inference

Ilya Gukov, Sonia Boscolo, Christophe Finot, and Sergei K. Turitsyn
NpM2C.6 Nonlinear Photonics (NP) 2018

Improving the Performance of Coherent Quantum Communications with Bayesian Inference

S. Kleis and C. G. Schaeffer
W2A.64 Optical Fiber Communication Conference (OFC) 2018

Bayesian machine learning of frequency-bin CNOT

Hsuan-Hao Lu, Joseph M. Lukens, Brian P. Williams, Poolad Imany, Nicholas A. Peters, Andrew M. Weiner, and Pavel Lougovski
FF1F.3 CLEO: QELS_Fundamental Science (CLEO:FS) 2019

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved