Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-25T16:23:13.115Z Has data issue: false hasContentIssue false
  • English
  • Français

Inverse Spectropolarimetric Modelling of Hot Star Wind Structure and Variability

Published online by Cambridge University Press:  12 April 2016

John C. Brown ,
Richard Ignace  and
M. Piana
John C. Brown
Affiliation:
Dept of Physics and Astronomy, University of Glasgow, G12 8QQ, UK
Richard Ignace
Affiliation:
Dept of Physics and Astronomy, University of Glasgow, G12 8QQ, UK
M. Piana
Affiliation:
INFN, Universita di Genova, Genova, Italy

Extract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Merits and limitations are discussed of using an inferential inverse, as opposed to the usual model-fitting, approach to diagnose stellar wind structure. We aspire to encourage the stellar wind community to use inversion rather than forward modelling by making it clear what inversion means, when and why it is valuable, and by giving examples of successful applications.

A sub-discipline of astrophysics advances beyond the discovery era as the quality of data moves from single numbers (flux, colour, size) to well measured functions or data strings g(y) (e.g., light curves or spectra where g is flux and y is time or wavelength). As the precision δg/g and the resolution δy/y improve, we progress from data gathering and qualitative description to quantitative modelling in terms of some relevant source model function f(x), describing source “structure” in some sense. In general g(y) and f(x) do not correspond one-to-one but rather f maps to g in a “convolved” (sometimes complex and non-linear) way through the radiation processes, while f itself may be a combination of important source properties. Here we consider only the simplest situation (though our arguments can be generalised) where the relationship is of the linear integral form

where the operator function K, represents the emission physics which we assume known. The diagnostic problem is to determine as much as possible about f(x) within the noise and resolution limits of the data g(y) and the smearing effect of K(x, y).

Type
Section I Observations of Non-spherical Winds
Information
International Astronomical Union Colloquium , Volume 169: Variable and Non-spherical Stellar Winds in Luminous Hot Stars , 1999 , pp. 111 - 114
Copyright
Copyright © Springer-Verlag 1999

References

Brown, J.C. (1971): Solar Phys. 18, 489–502 CrossRefGoogle Scholar
Brown, J.C., Wood, K. (1992): Astron. Astrophys. 265, 663–668 Google Scholar
Brown, J.C., Wood, K. (1994): Astron. Astrophys. 290, 634–638 Google Scholar
Brown, J.C., Richardson, L.L., Ignace, R., Cassinelli, J.P. (1997): Astron. Astrophys. 325, 677–684 Google Scholar
Calvini, P., Bertero, M., Brown, J.C (1995): Astron. Astrophys. 309, 235–244 Google Scholar
Craig, I.J.D., Brown, J.C. (1986): Inverse Problems in Astronomy (Hilger, Bristol)Google Scholar
Fox, G.K., Brown, J.C. (1991): Astrophys.J. 375, 300–313 Google Scholar
Ignace, R., Brown, J.C., Richardson, L.L., Cassinelli, J.P. (1998a): Astron. Astrophys. 330, 253–264 Google Scholar
Ignace, R., Brown, J.C., Milne, J.E., Cassinelli, J.P. (1998b): Astron. Astrophys. 337, 223–232 Google Scholar
Piana, M., Brown, J.C., Calvini, P. (1995): Inverse Problems 11, 961–973 Google Scholar
Thompson, A.M., Brown, J.C., Craig, I.J.D., Fulber, C. (1992): Astron. Astrophys. 265, 278–288 Google Scholar
Wood, K., Bjorkman, J.E. (1995): Astrophys. J., 443, 348–362 Google Scholar