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Linearized spectrum correlation analysis for line emission measurements.
Nishizawa, T; Nornberg, M D; Den Hartog, D J; Sarff, J S.
Affiliation
  • Nishizawa T; Department of Physics, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA.
  • Nornberg MD; Department of Physics, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA.
  • Den Hartog DJ; Department of Physics, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA.
  • Sarff JS; Department of Physics, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA.
Rev Sci Instrum ; 88(8): 083513, 2017 Aug.
Article in En | MEDLINE | ID: mdl-28863643
ABSTRACT
A new spectral analysis method, Linearized Spectrum Correlation Analysis (LSCA), for charge exchange and passive ion Doppler spectroscopy is introduced to provide a means of measuring fast spectral line shape changes associated with ion-scale micro-instabilities. This analysis method is designed to resolve the fluctuations in the emission line shape from a stationary ion-scale wave. The method linearizes the fluctuations around a time-averaged line shape (e.g., Gaussian) and subdivides the spectral output channels into two sets to reduce contributions from uncorrelated fluctuations without averaging over the fast time dynamics. In principle, small fluctuations in the parameters used for a line shape model can be measured by evaluating the cross spectrum between different channel groupings to isolate a particular fluctuating quantity. High-frequency ion velocity measurements (100-200 kHz) were made by using this method. We also conducted simulations to compare LSCA with a moment analysis technique under a low photon count condition. Both experimental and synthetic measurements demonstrate the effectiveness of LSCA.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Rev Sci Instrum Year: 2017 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Rev Sci Instrum Year: 2017 Document type: Article Affiliation country: United States