Beschreibung:
ABSTRACT To accurately measure a star’s atmospheric parameters and chemical abundances, it is crucial to have high-quality spectra. Analysing the detailed chemical abundances of groups of stars can help us better understand nucleosynthesis, galactic chemical enrichment, and stellar evolution. In this study, we explored whether stellar spots can affect a star’s inferred metallicity and, if so, where the impact is the strongest. To investigate this, we created synthetic infrared spectra that included stellar spots for a sample of main-sequence stars younger than the sun. We then applied two models to the data: one that accounted for spots and the other that did not. From this, we can determine the bias introduced when fitting spotted spectra with a non-spotted model and how this bias varies with different parameters. Our findings revealed that fitting spotted spectra with a non-spotted model can introduce a scatter of up to 0.05 dex in the inferred metallicity, especially for stars with high levels of spot coverage. This bias is similar in magnitude to other relevant effects, such as atomic diffusion, radiative levitation, or non-local thermodynamic equilibrium. We also found that the effect is most pronounced in young stars and decreases with age. These results suggest that stellar spots can introduce a systematic uncertainty in metallicity that is not currently accounted for in spectroscopic analysis. This could potentially limit scientific inferences for population-level studies of young stars and differential abundance analyses.