Abstract
Analysis of Stark-broadened spectral line profiles is a powerful, non-intrusive diagnostic technique to extract the electron density of high-energy-density plasmas. The increasing number of applications and availability of spectroscopic measurements have stimulated new research on line broadening theory calculations and computer simulations, and their comparison. Here, we discuss a comparative study of Stark-broadened line shapes calculated with computer simulations using non-interacting and interacting particles, and with the multi-electron radiator line shape MERL code. In particular, we focus on Ar K-shell X-ray line transitions in He- and H-like ions, i.e., Heα, Heβ and Heγ in He-like Ar and Lyα, Lyβ and Lyγ in H-like Ar. These lines have been extensively used for X-ray spectroscopy of Ar-doped implosion cores in indirect- and direct-drive inertial confinement fusion (ICF) experiments. The calculations were done for electron densities ranging from 1023 to 3×1024 cm−3 and a representative electron temperature of 1 keV. Comparisons of electron broadening only and complete line profiles including electron and ion broadening effects, as well as Doppler, are presented. Overall, MERL line shapes are narrower than those from independent and interacting particles computer simulations performed at the same conditions. Differences come from the distinctive treatments of electron broadening and are more pronounced in α line transitions. We also discuss the recombination broadening mechanism that naturally emerges from molecular dynamics simulations and its influence on the line shapes. Furthermore, we assess the impact of employing either molecular dynamics or MERL line profiles on the diagnosis of core conditions in implosion experiments performed on the OMEGA laser facility.
Highlights
Stark-broadening theory has matured significantly over recent decades [1] and the analysis of Stark-broadened spectral lines shapes is currently used as a powerful, nonintrusive technique to diagnose the electron density in the context of glow discharges and in the extreme scenario of high-energy-density plasmas (HEDP).despite the undoubtedly advance in the understanding of broadening mechanisms, some puzzles remain to be solved
We present a comparative study of Stark-broadened line shapes calculated using the well-known Multi-Electron-Radiator-Line shape code (MERL) [9] and two kinds of classical computer simulations: the first one follows the independent-particle approach (IPA) and the second one comprises of a full molecular dynamics (MD) simulation of interacting particles
We performed a cross-comparison study of Stark-broadened line shapes using the well-known Multi-Electron-Radiator-Line shape code (MERL) as well as computer simulations with (a) non-interacting and (b) interacting particles
Summary
Stark-broadening theory has matured significantly over recent decades [1] and the analysis of Stark-broadened spectral lines shapes is currently used as a powerful, nonintrusive technique to diagnose the electron density in the context of glow discharges and in the extreme scenario of high-energy-density plasmas (HEDP).despite the undoubtedly advance in the understanding of broadening mechanisms, some puzzles remain to be solved. We notice that line broadening theory has been validated using independent methods of extracting plasma conditions, e.g., Thomson scattering, only for low-Z elements at free electron densities below 1019 cm−3 , so that it is often assumed that validity of Stark-broadening models can be extrapolated to the density range of interest. In this context, computer simulations provide a unique testbed for theory validation because of their ability for solving complex problems just relying on fundamental principles and barely using either physical or mathematical approximations. In order to scrutinize the differences between the model and simulations, comparisons are made for electron broadening only—Section 3.1—and for complete line profiles including electron and ion broadening mechanisms, as well as Doppler effect—Section 3.2
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