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

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 $\sim$6.6 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 $IRAC1-IRAC2$/$IRAC2-IRAC3$ 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 $K_S-WISE3>1.0~mag$ and $WISE4<6.5~mag$, 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 $-6.1~M_\odot/yr^{-1}$. 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 variable AGN

One of the novelties of the Gaia-DR3 with respect to the previous data releases is the publication of the multiband light curves of about 1 million AGN. The goal of this work was the creation of a catalogue of variable AGN, whose selection was based on Gaia data only. We first present the implementation of the methods to estimate the variability parameters into a specific object study module for AGN. Then we describe the selection procedure that led to the definition of the high-purity variable AGN sample and analyse the properties of the selected sources. We started from a sample of millions of sources, which were identified as AGN candidates by 11 different classifiers based on variability processing. Because the focus was on the variability properties, we first defined some pre-requisites in terms of number of data points and mandatory variability parameters. Then a series of filters was applied using only Gaia data and the Gaia Celestial Reference Frame 3 (Gaia-CRF3) sample as a reference.The resulting Gaia AGN variable sample, named GLEAN, contains about 872000 objects, more than 21000 of which are new identifications. We checked the presence of contaminants by cross-matching the selected sources with a variety of galaxies and stellar catalogues. The completeness of GLEAN with respect to the variable AGN in the last Sloan Digital Sky Survey quasar catalogue is about 47%, while that based on the variable AGN of the Gaia-CRF3 sample is around 51%. From both a comparison with other AGN catalogues and an investigation of possible contaminants, we conclude that purity can be expected to be above 95%. Multiwavelength properties of these sources are investigated. In particular, we estimate that about 4% of them are radio-loud. We finally explore the possibility to evaluate the time lags between the flux variations of the multiple images of strongly lensed quasars, and show one case.Comment: 19 pages, 31 figures, 2 table. This paper is part of Gaia Data Release 3 (DR3). In press for A&

Evolved Massive Stars at Low-metallicity V. Mass-Loss Rate of Red Supergiant Stars in the Small Magellanic Cloud

We assemble the most complete and clean red supergiant (RSG) sample (2,121 targets) so far in the Small Magellanic Cloud (SMC) with 53 different bands of data to study the MLR of RSGs. In order to match the observed spectral energy distributions (SEDs), a theoretical grid of 17,820 Oxygen-rich models (``normal'' and ``dusty'' grids are half-and-half) is created by the radiatively-driven wind model of the DUSTY code, covering a wide range of dust parameters. We select the best model for each target by calculating the minimal modified chi-square and visual inspection. The resulting MLRs from DUSTY are converted to real MLRs based on the scaling relation, for which a total MLR of $6.16\times10^{-3}$ $M_\odot$ yr$^{-1}$ is measured (corresponding to a dust-production rate of $\sim6\times10^{-6}$ $M_\odot$ yr$^{-1}$), with a typical MLR of $\sim10^{-6}$ $M_\odot$ yr$^{-1}$ for the general population of the RSGs. The complexity of mass-loss estimation based on the SED is fully discussed for the first time, indicating large uncertainties based on the photometric data (potentially up to one order of magnitude or more). The Hertzsprung-Russell and luminosity versus median absolute deviation diagrams of the sample indicate the positive relation between luminosity and MLR. Meanwhile, the luminosity versus MLR diagrams show a ``knee-like'' shape with enhanced mass-loss occurring above $\log_{10}(L/L_\odot)\approx4.6$, which may be due to the degeneracy of luminosity, pulsation, low surface gravity, convection, and other factors. We derive our MLR relation by using a third-order polynomial to fit the sample and compare our result with previous empirical MLR prescriptions. Given that our MLR prescription is based on a much larger sample than previous determinations, it provides a more accurate relation at the cool and luminous region of the H-R diagram at low-metallicity compared to previous studies.Comment: 16 pages, 19 figures, accepted by A&

DU439Module 14.1 Software Release Note: Gaia Report to ESA (GAIA-C4-SP-OPM-PG-013)

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DU439Module 11.1 Software Release Note

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DU439Module 14.0 Software Release Note

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