Inverse System Design using Machine Learning: the Raman
tical amplifica-tion and communication deal with inverse system design. Typically, a desired output (usually a gain profile, a noise profile, a transfer function or a similar continuous function) is given and
[2103.03837] Inverse design of Raman amplifier in frequency and
We present a Convolutional Neural Network (CNN) architecture for inverse Raman amplifier design. This model aims at finding the pump powers and wavelengths required for a target
Invited: Machine Learning Applied to Inverse Systems Design
We will show how the machine learning framework is optimized to generate on-demand arbitrary Raman gain profiles in a controlled and fast way and how it can become a key feature for future optical
Inverse design of Raman amplifier in frequency and distance
2021 We present a Convolutional Neural Network (CNN) ar-chitecture for inverse Raman amplifier design. This model aims at finding the pump powers and wave-
Flexible Raman Amplifier Optimization Based on Machine
V. RESULTS processes outlined in Section IV are run for the 5. Optimized Raman configuration when initialized to 20 remote and 20 forward the optimized RAs are input to two reference implementations
Inverse System Design Using Machine Learning: The Raman
We present a novel method for inverse system design using machine learning and apply it to Raman amplifier design. Inverse system design for Raman amplifiers consists of selecting pump
Experimental characterization of Raman amplifier optimization through
In this paper, we perform a thorough experimental characteriza-tion of such machine learning framework. The applicability of the proposed approach, as well as its ability to accurately provide flat
Inverse design of a Raman amplifier in frequency and distance
We present a convolutional neural network architecture for inverse Raman amplifier design. This model aims at finding the pump powers and wavelengths required for a target signal power evolution in both
Machine Learning Assisted Inverse Design for Ultrafine, Dynamic and
The broadband pump is optimized by machine learning based inverse design and shaped by programmable waveshaper, so as to realize the ultrafine, dynamic and arbitrary gain spectrum
Optical Power Meters & Sources
High-precision power meters (Ge/InGaAs) and stabilized light sources for insertion loss and return loss testing.
OTDR & Fiber Characterization
Full-featured OTDR, fiber OTDR testers, and modular OTDR test modules for network deployment and troubleshooting.
OSA & Eye Diagram Analyzer
High-resolution OSA for DWDM and eye diagram testers for signal integrity validation.
BERT & Endface Inspection
BERT up to 800G, fiber endface inspection probes, and extinction ratio meters for comprehensive testing.