Machine Learning for Raman Amplifier Design

Uiara Celine de Moura; Francesco Da Ros; Ann M. Rosa Brusin; Andrea Carena; Darko Zibar

Machine Learning for Raman Amplifier Design

Uiara Celine de Moura^* (Invited author), Francesco Da Ros (Invited author), Ann M. Rosa Brusin (Invited author), Andrea Carena (Invited author), Darko Zibar (Invited author)

^*Corresponding author for this work

Polytechnic University of Turin

Research output: Contribution to conference › Conference abstract for conference › Research › peer-review

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Abstract

A comprehensive discussion about the application of a machine learning tool to design Raman amplifiers is provided. Simulation and experimental results demonstrate its accuracy in achieving the desired gain profiles.

Original language	English
Publication date	2020
Number of pages	1
Publication status	Published - 2020
Event	OSA Advanced Photonics Congress 2020 - Online event Duration: 13 Jul 2020 → 17 Jul 2020

Conference

Conference	OSA Advanced Photonics Congress 2020
Location	Online event
Period	13/07/2020 → 17/07/2020

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Machine Learning for Raman Amplifier Design
Uiara Celine de Moura (Invited speaker)
13 Jul 2020
Activity: Talks and presentations › Conference presentations

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title = "Machine Learning for Raman Amplifier Design",

abstract = "A comprehensive discussion about the application of a machine learning tool to design Raman amplifiers is provided. Simulation and experimental results demonstrate its accuracy in achieving the desired gain profiles.",

author = "Moura, {Uiara Celine de} and {Da Ros}, Francesco and Brusin, {Ann M. Rosa} and Andrea Carena and Darko Zibar",

year = "2020",

language = "English",

note = "OSA Advanced Photonics Congress 2020 ; Conference date: 13-07-2020 Through 17-07-2020",

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TY - ABST

T1 - Machine Learning for Raman Amplifier Design

AU - Moura, Uiara Celine de

AU - Da Ros, Francesco

AU - Brusin, Ann M. Rosa

AU - Carena, Andrea

AU - Zibar, Darko

PY - 2020

Y1 - 2020

N2 - A comprehensive discussion about the application of a machine learning tool to design Raman amplifiers is provided. Simulation and experimental results demonstrate its accuracy in achieving the desired gain profiles.

AB - A comprehensive discussion about the application of a machine learning tool to design Raman amplifiers is provided. Simulation and experimental results demonstrate its accuracy in achieving the desired gain profiles.

M3 - Conference abstract for conference

T2 - OSA Advanced Photonics Congress 2020

Y2 - 13 July 2020 through 17 July 2020

ER -

Machine Learning for Raman Amplifier Design

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Conference

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Machine Learning for Raman Amplifier Design

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