An empirical recipe for inelastic hydrogen-atom collisions in non-LTE calculations
arXiv:1612.09302 · doi:10.1051/0004-6361/201630352
Abstract
We investigate the role of hydrogen collisions in NLTE spectral line synthesis, and introduce a new general empirical recipe to determine inelastic charge transfer (CT) and bound-bound hydrogen collisional rates. This recipe is based on fitting the energy functional dependence of published quantum collisional rate coefficients of several neutral elements (BeI, NaI, MgI, AlI, SiI and CaI) using simple polynomial equations. We perform thorough NLTE abundance calculation tests using our method for four different atoms, Na, Mg, Al and Si, for a broad range of stellar parameters. We then compare the results to calculations computed using the published quantum rates for all the corresponding elements. We also compare to results computed using excitation collisional rates via the commonly used Drawin equation for different fudge factors, SH, applied. We demonstrate that our proposed method is able to reproduce the NLTE abundance corrections performed with the quantum rates for different spectral types and metallicities for representative NaI and AlI lines to within 0.05 dex and %\le%0.03 dex, respectively. For MgI and SiI lines, the method performs better for the cool giants and dwarfs, while larger discrepancies up to 0.2 dex could be obtained for some lines for the subgiants and warm dwarfs. We obtained larger NLTE correction differences between models incorporating Drawin rates relative to the quantum models by up to 0.4 dex. These discrepancies are potentially due to ignoring either or both CT and ionization collisional processes by hydrogen in our Drawin models. Our empirical fitting method performs well in its ability to reproduce, within narrow uncertainties, the abundance corrections computed with models incorporating quantum collisional rates. It could possibly be extended to other transitions or in the absence of published quantum calculations, to other elements as well.
15 pages, published in A&A at https://doi.org/10.1051/0004-6361/201630352
References in corpus (13)
- A grid of MARCS model atmospheres for late-type stars I. Methods and general properties
- The Radial Velocity Experiment (RAVE): first data release
- APOGEE: The Apache Point Observatory Galactic Evolution Experiment
- NLTE determination of the sodium abundance in a homogeneous sample of extremely metal-poor stars
- NLTE determination of the aluminium abundance in a homogeneous sample of extremely metal-poor stars
- Non-local thermodynamic equilibrium stellar spectroscopy with 1D and <3D> models - I. Methods and application to magnesium abundances in standard stars
- Mg line formation in late-type stellar atmospheres: I. The model atom
- 3D NLTE analysis of the most iron-deficient star, SMSS0313-6708
- Statistical equilibrium of silicon in the solar atmosphere
- Influence of departures from LTE on calcium, titanium, and iron abundance determinations in cool giants of different metallicities
- Excitation and charge transfer in low-energy hydrogen atom collisions with neutral iron
- New Fe I level energies and line identifications from stellar spectra
- Effective collision strengths between Mg I and electrons
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- Disentangling Milky Way halo populations at low metallicities using [Al/Fe]
- A method to derive self-consistent NLTE astrophysical parameters for 4 million high-resolution 4MOST stellar spectra in half a day with invertible neural networks
- Observational constraints on the origin of the elements. X. Combining NLTE and machine learning for chemical diagnostics of 4 million stars in the 4MIDABLE-HR survey