  In this paper, the effects of electron beam on the X pinch produced spectra
of L-shell Mo plasma have been investigated by principal component analysis
(PCA), and this analysis is compared with that of line ratio diagnostics.
Spectral database for PCA extraction was arranged using the non-LTE collisional
radiative L-shell Mo model. PC vector spectra of L shell Mo including F, Ne, Na
and Mg- like transitions were studied to investigate the polarization types of
these transitions. PC1 vector spectra of F, Ne, Na and Mg- like transitions
resulted in linear polarization of Stokes Q profiles. Besides, PC2 vector
spectra showed linear polarization of Stokes U profiles of 2p53s of Ne like
transitions which were recognized as responsive to the magnetic field (Trabert
et al., 2017). 3D representation of PCA coefficients demonstrated that addition
of electron beam to the non-LTE model generates the quantized collective
clusters which are translations of each other and follow V-shaped cascade
trajectories except for the case f = 0.0. The extracted principal coefficients
were used as a database for the Artifical Neural Network (ANN) to estimate the
plasma electron temperature, density and beam fractions of time integrated
spatially resolved L-shell Mo X-pinch plasma spectrum. PCA based ANN provides
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=1x1020 cm-3 in the presence of
the fraction of the beams with f~0.1 and centered energy of 5 keV.
