No Arabic abstract
In the last decades we witnessed an increase in studies of open clusters of the Galaxy, especially because of the good determination for a wide range of values of parameters such as age, distance, reddening, and proper motion. The reliable determination of the parameters strongly depends on the photometry available and especially on the U filter, which is used to obtain the color excess E(B-V) through the color-color diagram (U-B) by (B-V) by fitting a zero age main-sequence. Owing to the difficulty of performing photometry in the U band, many authors have tried to obtain E(B-V) without the filter. But because of the near linearity of the color-color diagrams that use the other bands, combined with the fact that most fitting procedures are highly subjective (many done by eye) the reliability of those results has always been questioned. Our group has recently developed, a tool that performs isochrone fitting in open-cluster photometric data with a global optimization algorithm, which removes the need to visually perform the fits and thus removes most of the related subjectivity. Here we apply our method to a set of synthetic clusters and two observed open clusters (Trumpler 1 and Melotte 105) using only photometry for the BVRI bands. Our results show that, considering the cluster structural variance caused only by photometric and Poisson sampling errors, our method is able to recover the synthetic cluster parameters with errors of less than 10% for a wide range of ages, distances, and reddening, which clearly demonstrates its potential. The results obtained for Trumpler 1 and Melotte 105 also agree well with previous literature values.
In determining the distances to stars within the Milky Way galaxy, one often uses photometric or spectroscopic parallax. In these methods, the type of each individual star is determined, and the absolute magnitude of that star type is compared with the measured apparent magnitude to determine individual distances. In this article, we define the term statistical photometric parallax, in which statistical knowledge of the absolute magnitudes of stellar populations is used to determine the underlying density distributions of those stars. This technique has been used to determine the density distribution of the Milky Way stellar halo and its component tidal streams, using very large samples of stars from the Sloan Digital Sky Survey. Most recently, the volunteer computing platform MilkyWay@home has been used to find the best fit model parameters for the density of these halo stars.
A one-dimensional method for reconstructing the structure of prestellar and protostellar clouds is presented. The method is based on radiative transfer computations and a comparison of theoretical and observed intensity distributions at both millimeter and infrared wavelengths. The radiative transfer of dust emission is modeled for specified parameters of the density distribution, central star, and external background, and the theoretical distribution of the dust temperature inside the cloud is determined. The intensity distributions at millimeter and IR wavelengths are computed and quantitatively compared with observational data. The best-fit model parameters are determined using a genetic minimization algorithm, which makes it possible to reveal the ranges of parameter degeneracy as well. The method is illustrated by modeling the structure of the two infrared dark clouds IRDC-320.27+029 (P2) and IRDC-321.73+005 (P2). The derived density and temperature distributions can be used to model the chemical structure and spectral maps in molecular lines.
We investigate the capability of the UBVRIJHK photometric system to quantify star clusters in terms of age, metallicity and color excess by their integrated photometry in the framework of PEGASE single stellar population (SSP) models. The age-metallicity-extinction degeneracy was analyzed for various parameter combinations, assuming different levels of photometric accuracy. We conclude, that most of the parameter degeneracies, typical to the UBVRI photometric system, are broken in the case when the photometry data are supplemented with at least one infrared magnitude of the JHK passbands, with an accuracy better than ~0.05 mag. The presented analysis with no preassumptions on the distribution of photometric errors of star cluster models, provides estimate of the intrinsic capability of any photometric system to determine star cluster parameters from integrated photometry.
In this paper, we present our results for the photometric and kinematical studies of old open cluster NGC 188. We determined various astrophysical parameters like limited radius, core and tidal radii, distance, luminosity and mass functions, total mass, relaxation time etc. for the cluster using 2MASS catalog. We obtained the clusters distance from the Sun as 1721+/-41 pc and log (age)= 9.85+/-0.05 at Solar metallicity. The relaxation time of the cluster is smaller than the estimated cluster age which suggests that the cluster is dynamically relaxed. Our results agree with the values mentioned in the literature. We also determined the clusters apex coordinates as (281.88 deg, -44.76 deg) using AD-diagram method. Other kinematical parameters like space velocity components, cluster center and elements of Solar motion etc. have also been computed.
This work presents an approach (fitCMD) designed to obtain a comprehensive set of astrophysical parameters from colour-magnitude diagrams (CMDs) of star clusters. Based on initial mass function (IMF) properties taken from isochrones, fitCMD searches for the values of total (or cluster) stellar mass, age, global metallicity, foreground reddening, distance modulus, and magnitude-dependent photometric completeness that produce the artificial CMD that best reproduces the observed one; photometric scatter is also taken into account in the artificial CMDs. Inclusion of photometric completeness proves to be an important feature of fitCMD, something that becomes apparent especially when luminosity functions are considered. These parameters are used to build a synthetic CMD that also includes photometric scatter. Residual minimization between the observed and synthetic CMDs leads to the best-fit parameters. When tested against artificial star clusters, fitCMD shows to be efficient both in terms of computational time and ability to recover the input values.