354 research outputs found

    The massive star population of the Virgo Cluster galaxy NGC 4535

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    We analyzed the massive star population of the Virgo Cluster galaxy NGC 4535 using archival Hubble Space Telescope Wide Field Planetary Camera 2 images in filters F555W and F814W, equivalent to Johnson V and Kron-Cousins I. We performed high precision point spread function fitting photometry of 24353 sources including 3762 candidate blue supergiants, 841 candidate yellow supergiants and 370 candidate red supergiants. We estimated the ratio of blue to red supergiants as a decreasing function of galactocentric radius. Using Modules for Experiments in Stellar Astrophysics isochrones at solar metallicity, we defined the luminosity function and estimated the star formation history of the galaxy over the last 60 Myrs. We conducted a variability search in the V and I filters using three variability indexes: the median absolute deviation, the interquartile range and the inverse von-Neumann ratio. This analysis yielded 120 new variable candidates with absolute magnitudes ranging from MV_{V} = -4 to -11 mag. We used the MESA evolutionary tracks at solar metallicity, to classify the variables based on their absolute magnitude and their position on the color-magnitude diagram. Among the new candidate variable sources are eight candidate variable red supergiants, three candidate variable yellow supergiants and one candidate luminous blue variable, which we suggest for follow-up observations.Comment: Accepted by A&A, 7 pages, 7 Tables, 53 figure

    Comparative performance of selected variability detection techniques in photometric time series

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    Photometric measurements are prone to systematic errors presenting a challenge to low-amplitude variability detection. In search for a general-purpose variability detection technique able to recover a broad range of variability types including currently unknown ones, we test 18 statistical characteristics quantifying scatter and/or correlation between brightness measurements. We compare their performance in identifying variable objects in seven time series data sets obtained with telescopes ranging in size from a telephoto lens to 1m-class and probing variability on time-scales from minutes to decades. The test data sets together include lightcurves of 127539 objects, among them 1251 variable stars of various types and represent a range of observing conditions often found in ground-based variability surveys. The real data are complemented by simulations. We propose a combination of two indices that together recover a broad range of variability types from photometric data characterized by a wide variety of sampling patterns, photometric accuracies, and percentages of outlier measurements. The first index is the interquartile range (IQR) of magnitude measurements, sensitive to variability irrespective of a time-scale and resistant to outliers. It can be complemented by the ratio of the lightcurve variance to the mean square successive difference, 1/h, which is efficient in detecting variability on time-scales longer than the typical time interval between observations. Variable objects have larger 1/h and/or IQR values than non-variable objects of similar brightness. Another approach to variability detection is to combine many variability indices using principal component analysis. We present 124 previously unknown variable stars found in the test data.Comment: 29 pages, 8 figures, 7 tables; accepted to MNRAS; for additional plots, see http://scan.sai.msu.ru/~kirx/var_idx_paper

    Red supergiant stars in the Large Magellanic Cloud. II. Infrared properties and mid-infrared variability

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    The characteristics of IR properties and MIR variability of RSGs in the LMC are analyzed based on 12 bands of NIR to MIR co-added data from 2MASS, Spitzer and WISE, and \sim6.6 years of MIR time-series data collected by the ALLWISE and NEOWISE-R projects. 773 RSGs candidates were compiled from the literature and verified by using the CMD, SED and MIR variability. About 15\% of valid targets in the IRAC1IRAC2IRAC1-IRAC2/IRAC2IRAC3IRAC2-IRAC3 diagram may show PAH emission. We show that arbitrary dereddening Q parameters related to the IRAC4, S9W, WISE3, WISE4, and MIPS24 bands could be constructed based on a precise measurement of MIR interstellar extinction law. Several peculiar outliers in our sample are discussed, in which one outlier might be a RSG right before the explosion or an x-AGB star in the very late evolutionary stage based on the MIR spectrum and photometry. There are 744 identified RSGs in the final sample having both the WISE1- and WISE2-band time-series data. The results show that the MIR variability is increasing along with the increasing of brightness. There is a relatively tight correlation between the MIR variability, MLR, and the warm dust or continuum, where the MIR variability is evident for the targets with KSWISE3>1.0 magK_S-WISE3>1.0~mag and WISE4<6.5 magWISE4<6.5~mag, while the rest of the targets show much smaller MIR variability. The MIR variability is also correlated with the MLR for which targets with larger variability also show larger MLR with an approximate upper limit of 6.1 M/yr1-6.1~M_\odot/yr^{-1}. Both the variability and the luminosity may be important for the MLR since the WISE4-band flux is increasing exponentially along with the degeneracy of luminosity and variability. The identified RSG sample has been compared with the theoretical evolutionary models and shown that the discrepancy between observation and evolutionary models can be mitigated by considering both variability and extinction.Comment: 24 pages, 22 figures, A&A accepte

    Gaia Data Release 3. The first Gaia catalogue of eclipsing binary candidates

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    We present the first Gaia catalogue of eclipsing binary candidates released in Gaia DR3, describe its content, provide tips for its usage, estimate its quality, and show illustrative samples. The catalogue contains 2,184,477 sources with G magnitudes up to 20 mag. Candidate selection is based on the results of variable object classification performed within the Gaia Data Processing and Analysis Consortium, further filtered using eclipsing binary-tailored criteria based on the G light curves. To find the orbital period, a large ensemble of trial periods is first acquired using three distinct period search methods applied to the cleaned G light curve. The G light curve is then modelled with up-to two Gaussians and a cosine for each trial period. The best combination of orbital period and geometric model is finally selected using Bayesian model comparison based on the BIC. A global ranking metric is provided to rank the quality of the chosen model between sources. The catalogue is restricted to orbital periods larger than 0.2 days. About 530,000 of the candidates are classified as eclipsing binaries in the literature as well, out of ~600,000 available crossmatches, and 93% of them have published periods compatible with the Gaia periods. Catalogue completeness is estimated to be between 25% and 50%, depending on the sky region, relative to the OGLE4 catalogues of eclipsing binaries towards the Galactic Bulge and the Magellanic Clouds. The analysis of an illustrative sample of ~400,000 candidates with significant parallaxes shows properties in the observational HR diagram as expected for eclipsing binaries. The subsequent analysis of a sub-sample of detached bright candidates provides further hints for the exploitation of the catalogue. The orbital periods, light curve model parameters, and global rankings are all published in the catalogue with their related uncertainties where applicable.Comment: Submitted to A&A. Main text: 23 pages, 35 figures. Four appendices (17 pages) with 38 figure
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