The Infrared Surface Brightness Technique Applied to RR Lyrae Stars from the Solar Neighborhood

Bartłomiej Zgirski, Wolfgang Gieren,Grzegorz Pietrzyński,Marek Górski,Piotr Wielgórski,Jesper Storm, Garance Bras, Pierre Kervella,Nicolas Nardetto,Gergely Hajdu, Rolf Chini, Martin Haas

arxiv(2024)

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摘要
The Baade-Wesselink method allows us to estimate distances to individual pulsating stars. Accurate geometric parallaxes obtained by the Gaia mission serve us in the calibration of the method and in the determination of its precision. The method also provides a way of determining mean radii of pulsating stars. The main aim of this work is to determine the scatter and possible dependence of p- factors of RR Lyrae stars on their pulsation periods. The secondary objective is to determine mean radius - period relations for these stars. Our calibrations for RR Lyrae stars are based on photometric data gathered at the Cerro Murphy Observatory. We obtained spectroscopic data specifically for this project using high resolution spectrographs. We use the Infrared Surface Brightness (IRSB) version of the method that relies on a surface brightness - color relation dependent on the (V-K) color. We obtain the spread of p- factors of around 0.07-0.08 for our sample of 9 RR Lyrae stars from the solar neighborhood. However, we also find relations between the p-factor and the pulsation period for RRab stars with the rms scatter around the relation of around 0.05, but with relatively large uncertainty of relations' parameters. We present relations between the mean radius and period for RR Lyrae pulsating in the fundamental mode with the rms scatter around the relation of 0.012R_⊙. We observe a clear offset between p- factors obtained using the IRSB technique (with mean p between 1.39 and 1.45) and values inferred by Bras et al. (2024) using the SPIPS tool (Mérand et al. 2015). On the other hand, we obtain a similar scatter of p of as observed by Bras et al. (2024). Our period-radius relations are in a good agreement with both the inference of Bras et al. (2024) based on SPIPS and theoretical predictions of Marconi et al. (2005, 2015)
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