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 language | English |
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Title of host publication | Proceedings of the SPIE |
Number of pages | 8 |
Volume | 9388 |
Publisher | SPIE - International Society for Optical Engineering |
Publication date | 2015 |
Article number | 938809 |
DOIs | |
Publication status | Published - 2015 |
Event | SPIE Photonics West OPTO 2015 - The Moscone Center, San Francisco, United States Duration: 7 Feb 2015 → 12 Feb 2015 Conference number: 9388 |
Conference
Conference | SPIE Photonics West OPTO 2015 |
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Number | 9388 |
Location | The Moscone Center |
Country/Territory | United States |
City | San Francisco |
Period | 07/02/2015 → 12/02/2015 |
Series | Proceedings of SPIE - The International Society for Optical Engineering |
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ISSN | 0277-786X |
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