Modelling the clumping-induced polarimetric variability of hot star winds


Ben Davies(^1,2), Jorick S. Vink(^3,4,5), René D. Oudmaijer(^2)

1. Center for Imaging Science, Rochester Institute of Technology, 84 Lomb Memorial Drive, Rochester, NY 14623, USA
2. School of Physics & Astronomy, University of Leeds, Woodhouse Lane, Leeds LS2 9JT, UK
3. Imperial College, Blackett Laboratories, Prince Consort Road, London SW7 2BZ, UK
4. Lennard-Jones Laboratories, Keele University, Staffordshire ST5 5BG, UK
5. Armagh Observatory, College Hill, Armagh BT61 9DG, NI, UK

Clumping in the winds of massive stars may significantly reduce empirical mass-loss rates, and which in turn may have a large impact on our understanding of massive star evolution. Here, we investigate wind-clumping through the linear polarization induced by light scattering off the clumps. Through the use of an analytic wind clumping model, we predict the time evolution of the linear polarimetry over a large parameter space. We concentrate on the Luminous Blue Variables, which display the greatest amount of polarimetric variability and for which we recently conducted a spectropolarimetric survey. Our model results indicate that the observed level of polarimetric variability can be reproduced for two regimes of parameter space: one of a small number of massive, optically-thick clumps; and one of a very large number of low-mass clumps. Although a systematic time-resolved monitoring campaign is required to distinguish between the two scenarios, we currently favour the latter, given the short timescale of the observed polarization variability. As the polarization is predicted to scale linearly with mass-loss rate, we anticipate that all hot stars with very large mass-loss rates should display polarimetric variability. This is consistent with recent findings that intrinsic polarization is more common in stars with strong H$alpha$ emission.

Reference: Accepted for publication in A&A
Status: Manuscript has been accepted

Weblink: http://www.cis.rit.edu/~bxdpci/7193accepted.pdf

Comments:

Email: davies@cis.rit.edu