Observational constraints on the origin of the elements

Abstract

Manganese (Mn) is a key Fe-group element, commonly employed in stellar population and nucleosynthesis studies to explore the role of SN Ia. We have developed a new non-local thermodynamic equilibrium (NLTE) model of Mn, including new photo-ionisation cross-sections and new transition rates caused by collisions with H and H− atoms. We applied the model in combination with one-dimensional (1D) LTE model atmospheres and 3D hydrodynamical simulations of stellar convection to quantify the impact of NLTE and convection on the line formation. We show that the effects of NLTE are present in Mn I and, to a lesser degree, in Mn II lines, and these increase with metallicity and with the effective temperature of a model. Employing 3D NLTE radiative transfer, we derive a new abundance of Mn in the Sun, A(Mn) = 5.52 ± 0.03 dex, consistent with the element abundance in C I meteorites. We also applied our methods to the analysis of three metal-poor benchmark stars. We find that 3D NLTE abundances are significantly higher than 1D LTE. For dwarfs, the differences between 1D NLTE and 3D NLTE abundances are typically within 0.15 dex, however, the effects are much larger in the atmospheres of giants owing to their more vigorous convection. We show that 3D NLTE successfully solves the ionisation and excitation balance for the RGB star HD 122563 that cannot be achieved by 1D LTE or 1D NLTE modelling. For HD 84937 and HD 140283, the ionisation balance is satisfied, however, the resonance Mn I triplet lines still show somewhat lower abundances compared to the high-excitation lines. Our results for the benchmark stars confirm that 1D LTE modelling leads to significant systematic biases in Mn abundances across the full wavelength range from the blue to the IR. We also produce a list of Mn lines that are not significantly biased by 3D and can be reliably, within the 0.1 dex uncertainty, modelled in 1D NLTE.

A high-precision abundance analysis of the nuclear benchmark star HD 20

“…More recently, Sitnova et al (2016) found lower NLTE corrections and therefore weaker -but still non-zero -ionization imbalances for stars in common with Bergemann (2011), which they mainly attributed to the inclusion of high-excitation levels of Ti i in their model atom. Bergemann et al (2019) corroborated the strong NLTE corrections found in the earlier study. Moreover, the authors remark that Mn i transitions at a lower excitation potential of more than 2 eV are not strongly affected by convection -that is 3D effects -and are recommended as 1D NLTE estimator.…”

Testing the Spectroscopic Extraction of Suppression of Convective Blueshift

“…Meunier et al (2017a) (hereafter M17) have developed one model to isolate RV conv contributions based on the observed non-linear relationship between relative depths and absolute RV blueshifts of spectral lines of a given species (here neutral iron) driven by plasma flow in granules, as described in Gray (2009);Reiners et al (2016); Meunier et al (2017b); Gray & Oostra (2018). The exact physical origin of this observed correlation is non-trivial: a correct description of spectral line formation necessitates the summation of many different line profiles, each formed at different depths in the photosphere, and requires a full threedimensional treatment (e.g., see Nordlund et al 2009;Stein 2012;Cegla et al 2013;Bergemann et al 2019 and references therein). An intuitive (though inexact) understanding of this relationship may be determined by considering a simplified 1D picture: in this model, rising plasma low in the photosphere exhibits strong RV blueshift, while plasma closer to the surface has most of its motion directed tangentially as it merges into intergranular lanes, thus exhibiting less RV blueshift (Dravins et al 1981).…”

The influence of NLTE effects in Fe I lines on an inverted atmosphere

“…A few years later, Nordlund (1985) for the first time studied the spectral line formation in 3D with NLTE effects in a realistic 3D model atmosphere. Since then, 3D NLTE computations on 3D model atmospheres have been used to compute spectral lines of, for example, lithium (Asplund et al 2003), oxygen (Kiselman & Nordlund 1995;Asplund et al 2004Asplund et al , 2005Pereira et al 2009;Prakapavičius et al 2013;Steffen et al 2015), iron (Lind et al 2017), manganese (Bergemann et al 2019), and barium (Gallagher et al 2020) to determine their abundances in solar and other stellar atmospheres. Recently, forward-modeling of chromospheric lines such as the Ca ii 8542 Å line (Leenaarts et al 2009), the Na i D1 line (Leenaarts et al 2010), the Hα line (Leenaarts et al 2012(Leenaarts et al , 2015, the Mg ii h and k lines (Leenaarts et al 2013), and the Ca ii H and K lines (Anusha & Nagendra 2013;Bjørgen et al 2018) were carried out in 3D NLTE to understand the line formation and to study different chromospheric features that are observed with these lines.…”

“…Sukhorukov & Leenaarts (2017) synthesized the Mg ii h and k, Lyα, and Lyβ lines taking the complexities of partial frequency redistribution in 3D NLTE into account. Bergemann et al (2019) modelled different chromospheric lines observed in active regions using 3D NLTE computations. 6302.5 Å lines that are formed in a network region.…”