3D non-LTE Ca II line formation in metal-poor FGK stars. I. Abundance corrections, radial velocity corrections, and synthetic spectra
Description
Title: 3D non-LTE Ca II line formation in metal-poor FGK stars. I. Abundance corrections, radial velocity corrections, and synthetic spectra
Authors: Cis Lagae, Anish M. Amarsi, Karin Lind
Abstract: The Ca II resonance doublet (HK) and the near-infrared triplet (CaT) are among the strongest features in stellar spectra of FGK-type stars. These spectral lines remain prominent down to extremely low metallicities and are thus useful for providing stellar parameters via ionisation balance and as radial velocity diagnostics. However, the majority of studies that model these lines in late-type stars still rely on one dimensional (1D) hydrostatic model atmospheres and the assumption of local thermodynamic equilibrium (LTE). We present 3D non-LTE radiative transfer calculations of the CaT and HK lines in an extended grid of 3D model atmospheres of metal-poor FGK-type. We investigate the impact of 3D non-LTE effects on abundances, line bisectors and radial velocities. We used a subset of 3D model atmospheres from the recently published STAGGER-grid to synthesize spectra in 3D (non-)LTE. For comparison, similar calculations were performed in 1D (non-)LTE using models from the MARCS grid. Abundance corrections for the CaT lines relative to 1D LTE range from +0.1 to -1.0 dex, with more severe corrections for strong lines in giants. With fixed line strength, the abundance corrections become more negative with increasing effective temperature and decreasing surface gravity. Radial velocity corrections relative to 1D LTE based on cross-correlation of the whole line profile range from -0.2 km/s to +1.5 km/s, with more severe corrections where the CaT lines are strongest. The corrections are even more severe if the line core alone is used to infer the radial velocity. The line strengths and shapes, and consequently the abundance and radial velocity corrections, are strongly affected by the chosen radiative transfer assumption, 1/3D (non)-LTE. We release grids of theoretical spectra that can be used to improve the accuracy of stellar spectroscopic analyses based on the Ca II triplet lines.
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We provide all the synthetic normalized flux spectra together with equivalent widths and abundance corrections only for the CaT lines. All of the output files contain python dictionaries stored in hdf5 format. Each model is defined by an unique identifier, allowing easy access of its properties across the different output files. This identifier is the first dictionnary key.
An example identifier is the following: 't65g45m30_z295(a100)'
t65 -> Teff = 6500 K
g45 -> logg = 4.5
m30 -> [Fe/H] = -3.0
z295 -> A(Ca) = 2.95 #Calcium abundance
a200 -> microtubulent velocity = 2.00 km/s #This is only added in the EW1D.h5 file
An example on how to read the files using python, which also clarifies the dictionnary structure, is given in example.py.
We do not provide any interpolation routines to interpolate inside the grid. We refer to Canocchi et al. (2024, DOI: 10.1051/0004-6361/202451972) who provided interpolation routines for the flux spectrum, for a similar grid.
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The flux grid is set on a 6-dimensional grid with the following dimensions:
Number of models (~50) x number of abundances (9) x 1D,3D,LTE,NLTE (4) x microturbulence (0 or 3) x number of lines (5) x number of wavelength points (~900)
The corrections and equivalent widths are only computed for the Ca Triplet lines, with the following dimensions:
Number of models (~50) x number of abundances (9) x 1D,3D,LTE,NLTE (4) x microturbulence (0 or 3) x number of lines (3)
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For completeness, the vacuum and air wavelengths used to compute the reduced equivalent widths are the following:
wl0_8497_vac = 8500.358770604962 #Å
wl0_8542_vac = 8544.434860987318 #Å
wl0_8662_vac = 8664.521664166832 #Å
wl0_8497_air = 8498.023772239989 #Å
wl0_8542_air = 8542.087945880607 #Å
wl0_8662_air = 8662.142276340805 #Å
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File Summary:
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FileName Explanations
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ReadMe This file
wl.5 Wavelength grid corresponding to the grid of fluxes
fluxes.h5 Grid of synthetic normalized fluxes
EW1D.h5 Grid of 1D equivalent widths
EW3D.h5 Grid of 3D equivalent widths
corrections.h5 Grid of abundance corrections and equivalent widths
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Detailed description of each file:
Each file contains a pandas.dataframe type object (similar to a python dictionary).
Each key is a string.
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FileName Keys
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wl.5 wl_H, wl_K, wl_8497, wl_8542, wl_8662
fluxes.h5 HK, cat
-> model identifier (example: t65g45m40_z270)
-> 3D, 1D100, 1D150, 1D200
-> H, K OR 8497, 8542, 8662
-> IF 3D: mean_nflux_nlte, mean_nflux_lte; ELIF 1D: nflux_nlte, nflux_lte
EW1D.h5
-> model identifier (example: t65g45m40_z270a150)
-> Teff_target, logg, feh, ACa, CaFe, vmic,
W8497nlte, W8542nlte, W8662nlte, W8497lte, W8542lte, W8662lte
EW3D.h5
-> model identifier (example: t65g45m40_z270)
-> Teff_target, Teff_real, Teff_sigma, logg, feh, ACa, CaFe,
W8497nlte, W8542nlte, W8662nlte, W8497lte, W8542lte, W8662lte,
new, pec_outer
corrections.h5
-> model identifier (example: t65g45m40_z270)
-> Teff_target, Teff_real, Teff_sigma, logg, feh, ACa, CaFe,
Acorr8497_vm10, Acorr8497_vm15, Acorr8497_vm20,
Acorr8542_vm10, Acorr8542_vm15, Acorr8542_vm20,
Acorr8662_vm10, Acorr8662_vm15, Acorr8662_vm20
new, pec_outer
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Detailed description of each keyword:
NAME Description UNIT
Teff_target Effective temperature of the 1D model Kelvin
Teff_real Average effective temperature of the 3D model Kelvin
Teff_sigma Standard deviation on the 3D model Teff Kelvin
logg Surface gravity dex, log10(cgs)
feh Metallicity [Fe/H] dex
ACa Calcium abundance A(Ca) = [Ca/H] + A(Ca)_solar
CaFe Calcium-to-iron ratio [Ca/Fe]
W8497nlte non-LTE equivalent width of the CaT 8497 line Angstrom
W8542nlte non-LTE equivalent width of the CaT 8542 line Angstrom
W8662nlte non-LTE equivalent width of the CaT 8662 line Angstrom
W8497lte LTE equivalent width of the CaT 8497 line Angstrom
W8542lte LTE equivalent width of the CaT 8542 line Angstrom
W8662lte LTE equivalent width of the CaT 8662 line Angstrom
new True if 3D model is from the new Stagger grid (Rodriguez Diaz et al. 2024, DOI: 10.1051/0004-6361/202348480)
pec_outer True if model is flagged according to Section 3.2 in Rodriguez Diaz et al. (2024)
mean_nflux_nlte 3D spatially and temporally averaged normalized flux in non-LTE
mean_nflux_lte 3D spatially and temporally averaged normalized flux in LTE
nflux_nlte Normalized flux in 1D non-LTE
nflux_lte Normalized flux in 1D LTE
Acorr8497_vm10 3D non-LTE vs 1D LTE abundance correction for the 8497 line and microturbulence of 1.0 km/s
Acorr8497_vm15 " 8497 1.5 km/s
Acorr8497_vm20 " 8497 2.0 km/s
Acorr8542_vm10 " 8542 1.0 km/s
Acorr8542_vm15 " 8542 1.5 km/s
Acorr8542_vm20 " 8542 2.0 km/s
Acorr8662_vm10 " 8662 1.0 km/s
Acorr8662_vm15 " 8662 1.5 km/s
Acorr8662_vm20 " 8662 2.0 km/s
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