Radiative acceleration calculation methods and abundance anomalies in Am stars
arXiv:2410.11104 · doi:10.1051/0004-6361/202451997
Abstract
Atomic diffusion with radiative levitation is a major transport process to consider to explain abundance anomalies in Am stars. Radiative accelerations vary from one species to another, yielding different abundance anomalies at the stellar surface. Radiative accelerations can be computed using different methods: some evolution codes use an analytical approximation, while others calculate them from monochromatic opacities. We compared the abundance evolutions predicted using these various methods. Our models were computed with the Toulouse-Geneva evolution code, in which both an analytical approximation (the single-valued parameter method) and detailed calculations from Opacity Project (OP) atomic data are implemented for the calculation of radiative accelerations. The time evolutions of the surface abundances were computed using macroscopic transport processes that are able to reproduce observed Am star surface abundances in presence of atomic diffusion, namely an ad hoc turbulent model or a global mass loss. The radiative accelerations obtained with the various methods are globally in agreement for all the models below the helium convective zone, but can be much greater between the bottom of the hydrogen convective zone and that of helium. The time evolutions of the surface abundances mostly agree within the observational error, but the abundance of some elements can exceed this error for the least massive mass-loss model. The gain in computing time from using analytical approximations is significant compared to sequential calculations from monochromatic opacities for the turbulence models and for the least massive wind model; the gain is small otherwise. Test calculations of turbulence models with the tabulated OPAL opacities yield quite similar abundances as OP for most elements but in a much shorter time, so that determining Am star parameters can be done using a two-step method.
11 pages, 8 figures
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