2008/10/31 by Daniel J. Mortlock, D. Mortlock, Hiranya V. Peiris +2 · 8 citations
Physics and Astronomy · #Artificial intelligence #Astronomy #Astronomy and Astrophysical Research #Astrophysics #Degeneracy (biology) #Galaxy #Gamma-ray bursts and supernovae #Halo #Outlier #Physics #Sky #Spectral line #Stars #Stellar, planetary, and galactic studies #Surface gravity #White dwarf #astro-ph
paper · pdf · doi:10.1111/j.1365-2966.2009.15351.x
published in Monthly Notices of the Royal Astronomical Society 399(2), 699-714 (Oxford University Press) · MNRAS in press; 19 pages, 16 figures; major revisions to text but conclusions unchanged
arxiv created 2009/09/03 · openalex publication_date 2009/09/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
It is possible to reliably identify white dwarfs (WDs) without recourse to spectra, instead using photometric and astrometric measurements to distinguish them from main-sequence stars and quasars. WDs' colours can also be used to infer their intrinsic properties (effective temperature, surface gravity, etc.), but the results obtained must be interpreted with care. The difficulties stem from the existence of a solid angle degeneracy, as revealed by a full exploration of the likelihood, although this can be masked if a simple best-fitting approach is used. Conversely, this degeneracy can be broken if a Bayesian approach is adopted, as it is then possible to utilize the prior information on the surface gravities of WDs implied by spectroscopic fitting. The benefits of such an approach are particularly strong when applied to outliers, such as the candidate halo and ultracool WDs identified by Vidrih et al. A reanalysis of these samples confirms their results for the latter sample, but suggests that most of the halo candidates are thick-disc WDs in the tails of the photometric noise distribution.