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(Reference retrieved automatically from Google Scholar through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Kinematic segregation of nearby disk stars from the Hipparcos database

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Author(s):
De Souza‚ RE ; Teixeira‚ R.
Total Authors: 2
Document type: Journal article
Source: Astronomy & Astrophysics; v. 471, n. 2, p. 475-484, 2007.
Abstract

Aims. To better understand our Galaxy, we investigate the pertinency of describing the system of nearby disk stars in terms of a two-component Schwarzschild velocity distribution. Using the proper motion and parallax information of Hipparcos database, we determine the parameters characterizing the local stellar velocity field of a sample of 22 000 disk stars. The sample we use is essentially the same as the one described by the criteria adopted to study the LSR and the stream motion of the nearby stellar population. Methods. The selected data is modeled with a two component Schwarzschild velocity distribution whose parameters were determined by a least-square regression. The celestial sphere was divided into 72 equal area regions used to determine the parameters minimizing the. final velocity distribution function. Results. We verify that the results are not significantly different for the early type stars from the classical treatment using a single Gaussian population distribution. For late type stars in the subgiant branch, in contrast, we verify that the two-component model gives a much more satisfactory representation. Our results indicate for each spectral class the presence of these late type stars of a low velocity dispersion population, with sigma(u) similar or equal to 20 km s(-1) coexisting with a high velocity dispersion population having sigma(u) similar or equal to 40 km s(-1). Both populations belong to the disk with scale heights of 120 pc and 220 pc, respectively, relative to the Galactic disk. (AU)

FAPESP's process: 00/06695-0 - Galaxy Evolution and Activity
Grantee:Ronaldo Eustaquio de Souza
Support Opportunities: Research Projects - Thematic Grants