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Volume 4 Issue 2
Mar.  2019
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Article Contents
Yilmaz M. F., Danisman Y., Ozdemir M., Karlık B., Larour J.. Investigation of electron beam effects on L-shell Mo plasma produced by a compact LC generator using pattern recognition[J]. Matter and Radiation at Extremes, 2019, 4(2): 027401. doi: 10.1063/1.5081676
Citation: Yilmaz M. F., Danisman Y., Ozdemir M., Karlık B., Larour J.. Investigation of electron beam effects on L-shell Mo plasma produced by a compact LC generator using pattern recognition[J]. Matter and Radiation at Extremes, 2019, 4(2): 027401. doi: 10.1063/1.5081676

Investigation of electron beam effects on L-shell Mo plasma produced by a compact LC generator using pattern recognition

doi: 10.1063/1.5081676
More Information
  • Corresponding author: a)Author to whom correspondence should be addressed: fthyilmaz53@gmail.com
  • Received Date: 2018-03-28
  • Accepted Date: 2018-06-26
  • Available Online: 2021-04-13
  • Publish Date: 2019-03-15
  • In this paper, the effects of an electron beam on X-pinch-produced spectra of L-shell Mo plasma are investigated for the first time by principal component analysis (PCA); this analysis is compared with that of line ratio diagnostics. A spectral database for PCA extraction is arranged using a non-Local Thermodynamic Equilibrium (non-LTE) collisional radiative L-shell Mo model. PC vector spectra of L-shell Mo, including F, Ne, Na and Mg-like transitions are studied to investigate the polarization types of these transitions. PC1 vector spectra of F, Ne, Na and Mg-like transitions result in linear polarization of Stokes Q profiles. Besides, PC2 vector spectra show linear polarization of Stokes U profiles of 2p53s of Ne-like transitions which are known as responsive to a magnetic field [Träbert, Beiersdorfer, and Crespo López-Urrutia, Nucl. Instrum Methods Phys. Res., Sect. B 408 , 107–109 (2017)]. A 3D representation of PCA coefficients demonstrates that addition of an electron beam to the non-LTE model generates quantized, collective clusters which are translations of each other that follow V-shaped cascade trajectories, except for the case f = 0.0. The extracted principal coefficients are used as a database for an Artificial Neural Network (ANN) to estimate the plasma electron temperature, density and beam fractions of the time-integrated, spatially resolved L-shell Mo X-pinch plasma spectrum. PCA-based ANNs provide an advantage in reducing the network topology, with a more efficient backpropagation supervised learning algorithm. The modeled plasma electron temperature is about Te ∼ 660 eV and density ne = 1 × 1020 cm−3, in the presence of the fraction of the beams with f ∼ 0.1 and centered energy of 5 keV.
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