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Register a new userFitting Isochrones to Open Cluster photometric data: A new global optimization tool
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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.
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We present an improved version of FIT3D, a fitting tool for the analysis of the spectroscopic properties of the stellar populations and the ionized gas derived from moderate resolution spectra of galaxies. FIT3D is a tool developed to analyze Integral Field Spectroscopy data and it is the basis of Pipe3D, a pipeline already used in the analysis of datasets like CALIFA, MaNGA, and SAMI. We describe the philosophy behind the fitting procedure, and in detail each of the different steps in the analysis. We present an extensive set of simulations in order to estimate the precision and accuracy of the derived parameters for the stellar populations. In summary, we find that using different stellar population templates we reproduce the mean properties of the stellar population (age, metallicity, and dust attenuation) within ~0.1 dex. A similar approach is adopted for the ionized gas, where a set of simulated emission- line systems was created. Finally, we compare the results of the analysis using FIT3D with those provided by other widely used packages for the analysis of the stellar population (Starlight, Steckmap, and analysis based on stellar indices) using real high S/N data. In general we find that the parameters for the stellar populations derived by FIT3D are fully compatible with those derived using these other tools.
We present the Exoplanet Simple Orbit Fitting Toolbox (ExoSOFT), a new, open-source suite to fit the orbital elements of planetary or stellar mass companions to any combination of radial velocity and astrometric data. To explore the parameter space of Keplerian models, ExoSOFT may be operated with its own multi-stage sampling approach, or interfaced with third-party tools such as emcee. In addition, ExoSOFT is packaged with a collection of post-processing tools to analyze and summarize the results. Although only a few systems have been observed with both the radial velocity and direct imaging techniques, this number will increase thanks to upcoming spacecraft and ground based surveys. Providing both forms of data enables simultaneous fitting that can help break degeneracies in the orbital elements that arise when only one data type is available. The dynamical mass estimates this approach can produce are important when investigating the formation mechanisms and subsequent evolution of substellar companions. ExoSOFT was verified through fitting to artificial data and was implemented using the Python and Cython programming languages; available for public download at https://github.com/kylemede/ExoSOFT under the GNU General Public License v3.
Clusterix 2.0 is a web-based, Virtual Observatory-compliant, interactive tool for the determination of membership probabilities in stellar clusters based on proper motion data using a fully non-parametric method. In the area occupied by the cluster, the frequency function is made up of two contributions: cluster and field stars. The tool performs an empirical determination of the frequency functions from the Vector-Point Diagram without relying in any previous assumption about their profiles. Clusterix 2.0 allows to search in an interactive way the appropriate spatial areas until an optimal separation of the two populations is obtained. Several parameters can be adjusted to make the calculation computationally feasible without interfering in the quality of the results. The system offers the possibility to query different catalogues, such as Gaia, or upload the user own data. The results of the membership determination can be sent via SAMP to VO tools like TopCat. We apply Clusterix 2.0 to several open clusters with different properties and environments to show the capabilities of the tool: an area of five degrees around NGC 2682 (M 67), an old, well known cluster; a young cluster NGC 2516 with a striking elongate structure extended up to four degrees; NGC 1750 & NGC 1758, a pair of partly overlapping clusters; in the area of NGC 1817 we confirm a little-known cluster, Juchert 23; and in an area with many clusters we disentangle the existence of two overlapping clusters where only one was previously known: Ruprecht 26 and the new, Clusterix 1.
Young open clusters are ideal laboratories to understand star formation process. We present deep UBV I and Halpha photometry for the young open cluster IC 1590 in the center of the H II region NGC 281. Early-type members are selected from UBV photometric diagrams, and low-mass pre-main sequence (PMS) members are identified by using Halpha photometry. In addition, the published X-ray source list and Gaia astrometric data are also used to isolate probable members. A total of 408 stars are selected as members. The mean reddening obtained from early-type members is <E(B-V) = 0.40 +/- 0.06 (s.d.). We confirm the abnormal extinction law for the intracluster medium. The distance modulus to the cluster determined from the zero-age main-sequence fitting method is 12.3 +/- 0.2 mag (d = 2.88 +/- 0.28 kpc), which is consistent with the distance d = 2.70 ^+0.24 _-0.20 kpc from the recent Gaia parallaxes. We also estimate the ages and masses of individual members by means of stellar evolutionary models. The mode of the age of PMS stars is about 0.8 Myr. The initial mass function of IC 1590 is derived. It appears a steeper shape (Gamma = -1.49 +/- 0.14) than that of the Salpeter/Kroupa initial mass function for the high mass regime (m > 1 M_sun). The signature of mass segregation is detected from the difference in the slopes of the initial mass functions for the inner (r < 2.5) and outer region of this cluster. We finally discuss the star formation history in NGC 281.
I describe a new, open-source astronomical image-fitting program called Imfit, specialized for galaxies but potentially useful for other sources, which is fast, flexible, and highly extensible. A key characteristic of the program is an object-oriented design which allows new types of image components (2D surface-brightness functions) to be easily written and added to the program. Image functions provided with Imfit include the usual suspects for galaxy decompositions (Sersic, exponential, Gaussian), along with Core-Sersic and broken-exponential profiles, elliptical rings, and three components which perform line-of-sight integration through 3D luminosity-density models of disks and rings seen at arbitrary inclinations. Available minimization algorithms include Levenberg-Marquardt, Nelder-Mead simplex, and Differential Evolution, allowing trade-offs between speed and decreased sensitivity to local minima in the fit landscape. Minimization can be done using the standard chi^2 statistic (using either data or model values to estimate per-pixel Gaussian errors, or else user-supplied error images) or Poisson-based maximum-likelihood statistics; the latter approach is particularly appropriate for cases of Poisson data in the low-count regime. I show that fitting low-S/N galaxy images using chi^2 minimization and individual-pixel Gaussian uncertainties can lead to significant biases in fitted parameter values, which are avoided if a Poisson-based statistic is used; this is true even when Gaussian read noise is present.
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