10.6084/m9.figshare.1012519.v1
V Zhaunerchyk
V
Zhaunerchyk
J H D Eland
J H D Eland
M Siano
M Siano
L J Frasinski
L J Frasinski
R J Squibb
R J Squibb
M Kaminska
M Kaminska
P vd Meulen
P vd Meulen
P Salén
P Salén
M Mucke
M Mucke
P Linusson
P Linusson
Integrated intensities of our model calculations and our experimental results associated with different features of the covariance maps relative to the intensity of the feature associated with the PAP process
IOP Publishing
2013
pap
electron emission processes
nonlinear correlation features
covariance mapping technique
fel
Different correction techniques
data
covariance maps
intensity
pulse
Linac Coherent Light Source Free Electron Laser
model
Atomic Physics
Molecular Physics
2013-08-13 00:00:00
Dataset
https://iop.figshare.com/articles/dataset/_Integrated_intensities_of_our_model_calculations_and_our_experimental_results_associated_with_diffe/1012519
<p><b>Table 2.</b> Integrated intensities of our model calculations and our experimental results associated with different features of the covariance maps relative to the intensity of the feature associated with the PAP process. The experimental values were corrected for the collection–detection efficiency of the spectrometer used, taking into account a decrease of about 50% for energetic valence and Auger electrons.</p> <p><strong>Abstract</strong></p> <p>We report on a detailed investigation into the electron emission processes of Ne atoms exposed to intense femtosecond x-ray pulses, provided by the Linac Coherent Light Source Free Electron Laser (FEL) at Stanford. The covariance mapping technique is applied to analyse the data, and the capability of this approach to disentangle both linear and nonlinear correlation features which may be hidden on coincidence maps of the same data set is demonstrated. Different correction techniques which enable improvements on the quality of the spectral features extracted from the covariance maps are explored. Finally, a method for deriving characteristics of the x-ray FEL pulses based on covariance mapping in combination with model simulations is presented.</p>