A mass-loss rate determination for zeta Puppis from the quantitative analysis of X-ray emission line profiles
David H. Cohen (1), Maurice A. Leutenegger (2), Emma E. Wollman (1,3),, Janos Zsarg\'o (4,5), D. John Hillier (4), Richard H. D. Townsend (6,7),, Stanley P. Owocki (6) ((1) Swarthmore College, (2) NASA-GSFC, (3) Caltech,, (4) Univ. Pittsburgh, (5) IPN, Mexico City

TL;DR
This study analyzes X-ray emission lines from zeta Puppis to accurately determine its mass-loss rate, revealing a lower value consistent with wind clumping effects, impacting stellar evolution models.
Contribution
First comprehensive measurement of optical depths across multiple lines in zeta Pup, linking wavelength dependence to wind absorption and refining mass-loss estimates.
Findings
Mass-loss rate of 3.5 ± 0.3 × 10^{-6} Msun/yr derived from X-ray line profiles.
Observed increase in optical depth with wavelength consistent with bound-free absorption.
Mass-loss rate lower than some previous H-alpha estimates, aligning with clumped wind models.
Abstract
We fit every emission line in the high-resolution Chandra grating spectrum of zeta Pup with an empirical line profile model that accounts for the effects of Doppler broadening and attenuation by the bulk wind. For each of sixteen lines or line complexes that can be reliably measured, we determine a best-fitting fiducial optical depth, tau_* = kappa*Mdot/4{pi}R_{\ast}v_{\infty}, and place confidence limits on this parameter. These sixteen lines include seven that have not previously been reported on in the literature. The extended wavelength range of these lines allows us to infer, for the first time, a clear increase in tau_* with line wavelength, as expected from the wavelength increase of bound-free absorption opacity. The small overall values of tau_*, reflected in the rather modest asymmetry in the line profiles, can moreover all be fit simultaneously by simply assuming a moderate…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
