Investigating the origin of cyclical wind variability in hot, massive stars - II. Hydrodynamical simulations of co-rotating interaction regions using realistic spot parameters for the O giant $\xi$ Persei

Abstract

OB stars exhibit various types of spectral variability historically associated with wind structures, including the apparently ubiquitous discrete absorption components (DACs). These features have been proposed to be caused either by magnetic fields or non-radial pulsations. In this second paper of this series, we revisit the canonical phenomenological hydrodynamical modelling used to explain the formation of DACs by taking into account modern observations and more realistic theoretical predictions. Using constraints on putative bright spots located on the surface of the O giant $\xi$ Persei derived from high precision space-based broadband optical photometry obtained with the Microvariability and Oscillations of STars (MOST) space telescope, we generate two-dimensional hydrodynamical simulations of co-rotating interaction regions in its wind. We then compute synthetic ultraviolet (UV) resonance line profiles using Sobolev Exact Integration and compare them with historical timeseries obtained by the International Ultraviolet Explorer (IUE) to evaluate if the observed behaviour of $\xi$ Persei's DACs is reproduced. Testing three different models of spot size and strength, we find that the classical pattern of variability can be successfully reproduced for two of them: the model with the smallest spots yields absorption features that are incompatible with observations. Furthermore, we test the effect of the radial dependence of ionization levels on line driving, but cannot conclusively assess the importance of this factor. In conclusion, this study self-consistently links optical photometry and UV spectroscopy, paving the way to a better understanding of cyclical wind variability in massive stars in the context of the bright spot paradigm.

arXiv comment16 pages, 10 figures, accepted for publication by MNRAS

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