Laser characterization with advanced digital signal processing

Molly Piels, Idelfonso Tafur Monroy, Darko Zibar

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Abstract

The use of machine learning techniques to characterize lasers with low output power is reviewed. Optimized phase tracking algorithms that can produce accurate noise spectra are discussed, and a method for inferring the amplitude noise spectrum and rate equation model of the laser under test is presented.
Original languageEnglish
Title of host publicationProceedings of the SPIE
Number of pages8
Volume9388
PublisherSPIE - International Society for Optical Engineering
Publication date2015
Article number938809
DOIs
Publication statusPublished - 2015
EventSPIE Photonics West 2015: Optical Metro Networks and Short-Haul Systems VII - The Moscone Center, San Francisco, United States
Duration: 7 Feb 201512 Feb 2015
Conference number: 9388

Conference

ConferenceSPIE Photonics West 2015: Optical Metro Networks and Short-Haul Systems VII
Number9388
LocationThe Moscone Center
CountryUnited States
CitySan Francisco
Period07/02/201512/02/2015
SeriesProceedings of SPIE, the International Society for Optical Engineering
Volume9388
ISSN0277-786X

Bibliographical note

Copyright 2015 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.

Keywords

  • Nanocavity devices
  • Optical interconnects
  • Digital signal processing

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