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We demonstrate a new Bayesian technique to invert color-magnitude diagrams of main sequence and white dwarf stars to reveal the underlying cluster properties of age, distance, metallicity, and line-of-sight absorption, as well as individual stellar masses. The advantages our technique has over traditional analyses of color-magnitude diagrams are(More)
We investigate the application of neural networks to the automation of MK spectral classification. The data set for this project consists of a set of over 5000 optical (3800–5200Å) spectra obtained from objective prism plates from the Michigan Spectral Survey. These spectra, along with their two-dimensional MK classifications listed in the Michigan Henry(More)
We explore the application of artificial neural networks (ANNs) for the estimation of atmospheric parameters (T eff , log g, and [Fe/H]) for Galactic F-and G-type stars. The ANNs are fed with medium-resolution (∆λ ∼ 1 − 2 ˚ A) non flux-calibrated spectroscopic observations. From a sample of 279 stars with previous high-resolution determinations of(More)
Using HST and the WFPC2 we have acquired very deep V-and I-band photometry of stars in NGC 2420 and NGC 2477 to study cluster luminosity functions at approximately solar metallicity. We have determined these cluster luminosity functions down to M I = 10.5 (0.2 M ⊙) and find that the luminosity function of NGC 2420 turns over at M I ≈ 9.0, and possibly stops(More)
Our mid-infrared survey of 124 white dwarfs with the Spitzer Space Telescope and the IRAC imager has revealed an infrared excess associated with the white dwarf WD 2115−560 naturally explained by circumstellar dust. This object is the fourth white dwarf observed to have circumstellar dust. All four are DAZ white dwarfs, i.e., they have both photospheric(More)
A sample of white dwarfs is selected from SDSS DR3 imaging data using their reduced proper motions, based on improved proper motions from SDSS plus USNO-B combined data. Numerous SDSS and followup spectra (Kilic et al. 2005) are used to quantify completeness and contamination of the sample; kine-matic models are used to understand and correct for(More)
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The discovery of probable X-ray, optical, and radio counterparts to Gamma Ray Bursts (GRBs) may allow signiicant advances in GRB research. More data are sorely needed, however. We have a target of opportunity program this semester at the 0.9 meter telescope to search for optical counterparts to GRBs. Images from the search will be made publicly available at(More)
We investigate the application of neural networks to the automation of MK spectral classiication. The data set for this project consists of a set of over 5000 optical (3800{5200 A) spectra obtained from objective prism plates from the Michigan Spectral Survey. These spectra, along with their two-dimensional MK classiications listed in the Michigan Henry(More)
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