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 OPTO 2015 - The Moscone Center, San Francisco, United States
    Duration: 7 Feb 201512 Feb 2015
    Conference number: 9388

    Conference

    ConferenceSPIE Photonics West OPTO 2015
    Number9388
    LocationThe Moscone Center
    Country/TerritoryUnited States
    CitySan Francisco
    Period07/02/201512/02/2015
    SeriesProceedings of SPIE - The International Society for Optical Engineering
    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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