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Register a new userNeural Network identification of halo white dwarfs
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Added by
Enrique Garcia-Berro
Publication date
1998
fields
Physics
and research's language is
English
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The white dwarf luminosity function has proven to be an excellent tool to study some properties of the galactic disk such as its age and the past history of the local star formation rate. The existence of an observational luminosity function for halo white dwarfs could provide valuable information about its age, the time that the star formation rate lasted, and could also constrain the shape of the allowed Initial Mass Functions (IMF). However, the main problem is the scarce number of white dwarfs already identified as halo stars. In this Letter we show how an artificial intelligence algorithm can be succesfully used to classify the population of spectroscopically identified white dwarfs allowing us to identify several potential halo white dwarfs and to improve the significance of its luminosity function.
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White dwarfs are the fossils left by the evolution of low-and intermediate-mass stars, and have very long evolutionary timescales. This allows us to use them to explore the properties of old populations, like the Galactic halo. We present a population synthesis study of the luminosity function of halo white dwarfs, aimed at investigating which information can be derived from the currently available observed data. We employ an up-to-date population synthesis code based on Monte Carlo techniques, that incorporates the most recent and reliable cooling sequences for metal poor progenitors as well as an accurate modeling of the observational biases. We find that because the observed sample of halo white dwarfs is restricted to the brightest stars only the hot branch of the white dwarf luminosity function can be used for such purposes, and that its shape function is almost insensitive to the most relevant inputs, like the adopted cooling sequences, the initial mass function, the density profile of the stellar spheroid, or the adopted fraction of unresolved binaries. Moreover, since the cut-off of the observed luminosity has not been yet determined only lower limits to the age of the halo population can be placed. We conclude that the current observed sample of the halo white dwarf population is still too small to obtain definite conclusions about the properties of the stellar halo, and the recently computed white dwarf cooling sequences which incorporate residual hydrogen burning should be assessed using metal-poor globular clusters.
Since 1996 EROS 2 has surveyed 440 square degrees at high Galactic latitude in order to search for high proper motion stars in the Solar neighbourhood. We present here the analysis of 250 square degrees for which we have three years of data. No object with halo-like kinematics has been detected. Using a detailed Monte-Carlo simulation of the observations, we calculate our detection efficiency for this kind of object and place constraints on their contribution to various halo models. If 14 Gyr old, the halo cannot be made of more than 18% of hydrogen white dwarfs (95% C.L.).
White dwarfs with metal lines in their spectra act as signposts for post-main sequence planetary systems. Searching the Sloan Digital Sky Survey (SDSS) data release 12, we have identified 231 cool (<9000 K) DZ white dwarfs with strong metal absorption, extending the DZ cooling sequence to both higher metal abundances, lower temperatures, and hence longer cooler ages. Of these 231 systems, 104 are previously unknown white dwarfs. Compared with previous work, our spectral fitting uses improved model atmospheres with updated line profiles and line-lists, which we use to derive effective temperatures and abundances for up to 8 elements. We also determine spectroscopic distances to our sample, identifying two halo-members with tangential space-velocities >300 kms-1. The implications of our results on remnant planetary systems are to be discussed in a separate paper.
We use 156 044 white dwarf candidates with $geq5sigma$ significant parallax measurements from the Gaia mission to measure the velocity dispersion of the Galactic disc; $(sigma_U,sigma_V,sigma_W) = (30.8, 23.9, 20.0)$ km s$^{-1}$. We identify 142 objects that are inconsistent with disc membership at the $>5sigma$ level. This is the largest sample of field halo white dwarfs identified to date. We perform a detailed model atmosphere analysis using optical and near-infrared photometry and parallaxes to constrain the mass and cooling age of each white dwarf. The white dwarf cooling ages of our targets range from 7 Myr for J1657+2056 to 10.3 Gyr for J1049-7400. The latter provides a firm lower limit of 10.3 Gyr for the age of the inner halo based on the well-understood physics of white dwarfs. Including the pre-white dwarf evolutionary lifetimes, and limiting our sample to the recently formed white dwarfs with cooling ages of $<500$ Myr, we estimate an age of $10.9 pm 0.4$ Gyr (internal errors only) for the Galactic inner halo. The coolest white dwarfs in our sample also give similar results. For example, J1049-7400 has a total age of 10.9-11.1 Gyr. Our age measurements are consistent with other measurements of the age of the inner halo, including the white dwarf based measurements of the globular clusters M4, NGC 6397, and 47 Tuc.
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-fit approach is used. Conversely, this degeneracy can be broken if a Bayesian approach is adopted, as it is then possible to utilise 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 ultra-cool WDs identified by Vidrih et al. (2007). A reanalysis of these samples confirms their results for the latter sample but suggests that that most of the halo candidates are thick disk WDs in the tails of the photometric noise distribution.
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