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Topic Area: Optoelectronics

Displaying records 31 to 40 of 63 records.
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31. Applications of artificial neural networks in optical performance monitoring
Topic: Optoelectronics
Published: 8/15/2009
Authors: Jeffrey A Jargon, Xiaoxia Wu, Ronald Skoog, Loukas Paraschis, Alan Willner
Abstract: Applications using artificial neural networks (ANNs) for optical performance monitoring (OPM) are proposed and demonstrated. Simultaneous identification of optical signal-to-noise-ratio (OSNR), chromatic dispersion (CD), and polarization-mode-dispers ...

32. Long distance frequency transfer through an optical carrier
Topic: Optoelectronics
Published: 8/2/2009
Author: Paul A Williams
Abstract: Fiber optic networks are an attractive means for the remote distribution of highly stable frequencies from optical clocks. The highest performance is achieved by use of the frequency of the optical carrier itself as the transfer frequency. We will re ...

33. Full PMD vector measured directly from modulated data using linear optical sampling
Topic: Optoelectronics
Published: 7/15/2009
Authors: Paul A Williams, Tasshi Dennis
Abstract: We demonstrate a new technique to monitor the polarization-mode dispersion in a fiber communication channel by analyzing the modulated data at the fiber output measured with Polarization-Sensitive Linear Optical Sampling (PS-LOS).

34. Lateral variations in self-assembled InGaAs quantum dot distributions
Topic: Optoelectronics
Published: 6/26/2009
Authors: Alexana Roshko, Todd E Harvey, Brittany L Hyland, Lehman Y Susan, Keith D Cobry
Abstract: The lateral uniformity of self-assembled InGaAs quantum dots grown by molecular beam epitaxy(MBE) was assessed as a function of growth conditions. Variations in the dot density and height were determined from atomic force micrographs. Growth rate h ...

35. Electron Microscope Study of Strain in InGaN Quantum Wells in GaN Nanowires
Topic: Optoelectronics
Published: 4/1/2009
Authors: Roy Howard Geiss, David Thomas Read
Abstract: GaN nanowires with InGaN quantum wells (QW) were grown on heated Si(111) substrates by molecular beam epitaxy (MBE) using elemental Ga and In and a radio-frequency-plasma N2 source. The growth procedures and the morphology of these nanowires have bee ...

36. EEEL Technical Accomplishments
Series: NIST Interagency/Internal Report (NISTIR)
Report Number: 7568
Topic: Optoelectronics
Published: 3/30/2009
Author: Erik M Secula
Abstract: This document describes the technical work of the Electronics and Electrical Engineering Laboratory. In this report, you will find that EEEL researchers are developing the world's most advanced sensors, providing advanced gamma ray imagers for astro ...

37. Optical Performance Monitoring Using Artificial Neural Networks Trained with Parameters Derived from Delay-Tap Asynchronous Sampling
Topic: Optoelectronics
Published: 3/20/2009
Authors: Jeffrey A Jargon, Xiaoxia Wu, Alan Willner
Abstract: We demonstrate a technique for optical performance monitoring by simultaneously identifying optical signal-to-noise ratio (OSNR), chromatic dispersion (CD), and polarization-mode dispersion (PMD) using artificial neural networks trained with paramete ...

38. Calculation of pulse parameters and propagation of uncertainty
Topic: Optoelectronics
Published: 3/1/2009
Authors: Paul D Hale, Chih-Ming Wang
Abstract: The fundamental starting point for the analysis of all two-state waveforms is the determination of the low- and highstate levels. This is a two-step process. First, the data are grouped into points belonging to each state, and second, the value of ea ...

39. Measuring optical waveforms with fiber frequency combs
Topic: Optoelectronics
Published: 1/5/2009
Authors: Ian R Coddington, William C Swann, Nathan Reynolds Newbury
Abstract: A stabilized frequency comb provides a broadband array of highly resolved comb lines. Using a multiheterodyne technique, we measure the amplitude and phase of every comb line, allowing for massively parallel, high-resolution optical sampling.

40. Optical performance monitoring using artificial neural networks trained with eye-diagram parameters
Topic: Optoelectronics
Published: 1/1/2009
Authors: Jeffrey A Jargon, Xiaoxia Wu, Alan Willner
Abstract: We developed artificial neural network models to simultaneously identify three separate impairments that can degrade optical channels, namely optical signal-to-noise ratio, chromatic dispersion, and polarization mode dispersion. The neural networks w ...

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