CCD photometry in the Vilnius system in the vicinity of the globular cluster M 56

Abstract

Abstract. CCD observations of field stars in an area north-east of the globular cluster M 56 were obtained in six bands of the Vilnius photometric system. The data sets cover a field of 9. × 9. 5. An outline of the data pathway from observations to reduction via IRAF is outlined in this text. Photometry of 366 stars brighter than 18th V magnitude has been obtained and the analysis of the observational errors is discussed.

Photometric determination of the [Fe/H] ratio for the globular cluster M 92

“…Moreover, no classification of stars is necessary, because the reddening in the direction of M 92 is already known and is negligible within the present accuracy. In a previous paper, Smriglio et al (2002) have shown that, with a 1.5-m class telescope, the rms error of the CCD photometry is generally less than 2% up to 16.5 V-magnitude. The rms error for the present photometry ranges between 2% and 3%, which is not very accurate.…”

“…We had several aims in view: e.g., automated photometric classification of a wide variety of stars (Smriglio et al 1986(Smriglio et al , 1988(Smriglio et al , 1990, CCD photometry in the Vilnius photometric system (Boyle et al 1990a,b;Boyle et al 1994;Dodd et al 1996;Boyle et al 1998;Smriglio et al 1998;Smriglio et al 2002), determination of interstellar extinction (Smriglio et al 1991;Boyle et al 1992;Janulis & Smriglio 1992), and the study of the cloudy structure of interstellar dust and the gas-to-dust ratio Smriglio et al 1995;Smriglio et al 1996). The observations of globular clusters give the opportunity of calibrating photometric systems in terms of temperature, luminosity, and metallicity, since these parameters, and the interstellar reddening of the cluster stars can be measured with rather good accuracy.…”

HNS-a hybrid neural system and its use for the classification of stars

“…[19] presents classification rates of this procedure analogous to the BU classification rates of the HNS. Their results are nearly as reliable as those obtained by the HNS.…”

“…Ongoing projects and basic attempts to develop procedures for an automated, fast and reliable spectral and luminosity, called Morgan-Keenan(MK), classification of stars are reported in [12], [11],[1], [18] and [19]. [16] employed a backproipagation neural network to perform the image classification only for a simple automated star-galaxy separation.…”