Astronomy and Astrophysics – Astrophysics
Scientific paper
Sep 1993
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1993apjs...88...53g&link_type=abstract
Astrophysical Journal Supplement Series (ISSN 0067-0049), vol. 88, no. 1, p. 53-80.
Astronomy and Astrophysics
Astrophysics
27
Angular Distribution, Astronomical Models, Astronomical Photometry, Galactic Structure, Hubble Space Telescope, Quasars, Star Distribution, Bias, Brightness, Cosmic Rays, Eddington Approximation, Gyroscopes, Point Spread Functions, Poisson Equation, Tables (Data)
Scientific paper
We report a photometric study of stars from 450 fields at high Galactic latitudes that were observed in the Hubble Space Telescope Snapshot Survey to an average limiting apparent magnitude of V = 21.4. There are 166 fields that contain quasars selected in radio, X-ray, and color-excess surveys. This sample of 273 stars is free of selection bias with respect to the density of stars. To within the Poisson errors, the total counts and magnitude distribution of this unbiased sample are in agreement with the Bahcall-Soneira model (Bahcall, 1986). The angular distribution of the faint stars favors, at the 2 sigma level, a somewhat steeper disk luminosity function and a smaller spheroid main-sequence normalization than given by the model. The sample does not have enough statistical power to distinguish between the two-component Bahcall-Soneira model and the three-component model first proposed by Gilmore and Reid (1983), which contains a thick disk. The statistical power of the survey would increase about 15-fold if colors were obtained for the stars: the data probe the main sequences of the disk, thick disk, and spheroid. Models with and without a thick disk could then be distinguished at the 6 sigma level. The HST Snapshot Survey includes an additional 284 fields, 279 of which are centered on quasars that were selected by objective-prism surveys. These 279 fields are expected to show and do exhibit bias against bright stars, making them unsuitable for testing Galactic models.
Bahcall John N.
Gould Andrew
Maoz Dan
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