We present a catalog of mean proper motions and membership probabilities of individual stars for optically visible open clusters, which have been determined using data from the UCAC4 catalog in a homogeneous way. The mean proper motion of the cluster and the membership probabilities of the stars in the region of each cluster were determined by applying the statistical method in a modified fashion. In this study, we applied a global optimization procedure to fit the observed distribution of proper motions with two overlapping normal bivariate frequency functions, which also take the individual proper motion errors into account. For 724 clusters, this is the first determination of proper motion, and for the whole sample, we present results with a much larger number of identified astrometric member stars. Furthermore, it was possible to estimate the mean radial velocity of 364 clusters (102 unpublished so far) with the stellar membership using published radial velocity catalogs. These results provide an increase of 30% and 19% in the sample of open clusters with a determined mean absolute proper motion and mean radial velocity, respectively.

We present a new technique to fit color-magnitude diagrams of open clusters based on the cross-entropy global optimization algorithm. The method uses theoretical isochrones available in the literature and maximizes a weighted likelihood function based on distances measured in the color-magnitude space. The weights are obtained through a non parametric technique that takes into account the star distance to the observed center of the cluster, observed magnitude uncertainties, the stellar density profile of the cluster among others. The parameters determined simultaneously are distance, reddening, age and metallicity. The method takes binary fraction into account and uses a Monte-Carlo approach to obtain uncertainties on the determined parameters for the cluster by running the fitting algorithm many times with a re-sampled data set through a bootstrapping procedure. We present results for 9 well studied open clusters, based on 15 distinct data sets, and show that the results are consistent with previous studies. The method is shown to be reliable and free of the subjectivity of most previous visual isochrone fitting techniques.

Aims. Open clusters are essential tools for understanding Galactic structure, as well as stellar evolution, because they are distributed over the whole Galactic plane, and because their ages, distances, and reddening can be determined. The values of derived cluster fundamental parameters can vary greatly because of the often subjective nature of both the isochrone fitting technique and member star selection. To minimize the subjectivity in the selection of stars and to improve the fitting procedure, our group has developed a nonparametric method that estimates the membership likelihood for apparent cluster stars. Methods. The cluster member selection method is based on the star position relative to the cluster center, the density of stars in the color-magnitude diagram (which can be multidimensional), the photometric errors, and the limiting magnitude of observations. We use this method, together with the global optimization tool developed in our previous articles, to fit theoretical isochrones to open cluster photometric data, making use of UBV and 2MASS data sets. Results. Using this likelihood estimation as a weight in the fitting procedure, we show that the method is robust in that it assigns low weights to most contaminating stars and high weights to the stars that are likely cluster members. Our results show that the fundamental parameters determined using 2MASS data agree with those from UBV data when both are determined from the global optimization fitting method, however, the analysis of the open cluster Dias 6 indicates that a revision of the determined parameters might be required for some cases.