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Register a new userSPIRITS Catalog of Infrared Variables: Identification of Extremely Luminous Long Period Variables
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V. R. Karambelkar
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We present a catalog of 417 luminous infrared variable stars with periods exceeding 250 days. These were identified in 20 nearby galaxies by the ongoing SPIRITS survey with the Spitzer Space Telescope. Of these, 359 variables have $M_{[4.5]}$ (phase-weighted mean magnitudes) fainter than $-12$ and periods and luminosities consistent with previously reported variables in the Large Magellanic Cloud. However, 58 variables are more luminous than $M_{[4.5]} = -12$, including 11 that are brighter than $M_{[4.5]} = -13$ with the brightest having $M_{[4.5]} = -15.51$. Most of these bright variable sources have quasi-periods longer than 1000 days, including four over 2000 days. We suggest that the fundamental period-luminosity relationship, previously measured for the Large Magellanic Cloud, extends to much higher luminosities and longer periods in this large galaxy sample. We posit that these variables include massive AGB stars (possibly super-AGB stars), red supergiants experiencing exceptionally high mass-loss rates, and interacting binaries. We also present 3.6, 4.5, 5.8 and 8.0 $mu$m photometric catalogs for all sources in these 20 galaxies.
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We aim to construct an exceptionally deep (V ~< 27) catalog of variable objects in selected Galactic and extragalactic fields visited multiple times by the Hubble Space Telescope (HST). While HST observations of some of these fields were searched for specific types of variables before (most notably, the extragalactic Cepheids), we attempt a systematic study of the population of variable objects of all types at the magnitude range not easily accessible with ground-based telescopes. The variability timescales that can be probed range from hours to years depending on how often a particular field has been visited. For source extraction and cross-matching of sources between visits we rely on the Hubble Source Catalog which includes 10^7 objects detected with WFPC2, ACS, and WFC3 HST instruments. The lightcurves extracted from the HSC are corrected for systematic effects by applying local zero-point corrections and are screened for bad measurements. For each lightcurve we compute variability indices sensitive to a broad range of variability types. The indices characterize the overall lightcurve scatter and smoothness. Candidate variables are selected as having variability index values significantly higher than expected for objects of similar brightness in the given set of observations. The Hubble Catalog of Variables will be released in 2018.
The Hubble Space Telescope (HST) has obtained multi-epoch observations providing the opportunity for a comprehensive variability search aiming to uncover new variables. We have therefore undertaken the task of creating a catalog of variable sources based on version 3 of the Hubble Source Catalog (HSC), which relies on publicly available images obtained with the WFPC2, ACS, and WFC3 instruments onboard the HST. We adopted magnitude-dependent thresholding in median absolute deviation (a robust measure of light curve scatter) combined with sophisticated preprocessing techniques and visual quality control to identify and validate variable sources observed by Hubble with the same instrument and filter combination five or more times. The Hubble Catalog of Variables (HCV) includes 84,428 candidate variable sources (out of 3.7 million HSC sources that were searched for variability) with $V leq 27$ mag; for 11,115 of them the variability is detected in more than one filter. The data points in the light curves of the variables in the HCV catalog range from five to 120 points (typically having less than ten points); the time baseline ranges from under a day to over 15 years; while $sim$8% of all variables have amplitudes in excess of 1 mag. Visual inspection performed on a subset of the candidate variables suggests that at least 80% of the candidate variables that passed our automated quality control are true variable sources rather than spurious detections resulting from blending, residual cosmic rays, and calibration errors. The HCV is the first, homogeneous catalog of variable sources created from archival HST data and currently is the deepest catalog of variables available. The catalog includes variable stars in our Galaxy and nearby galaxies, as well as transients and variable active galactic nuclei. (abbreviated)
The Hubble Catalog of Variables (HCV) project aims to identify the variable sources in the Hubble Source Catalog (HSC), which includes about 92 million objects with over 300 million measurements detected by the WFPC2, ACS and WFC3 cameras on board of the Hubble Space Telescope (HST), by using an automated pipeline containing a set of detection and validation algorithms. All the HSC sources with more than a predefined number of measurements in a single filter/instrument combination are pre-processed to correct systematic effect and to remove the bad measurements. The corrected data are used to compute a number of variability indexes to determine the variability status of each source. The final variable source catalog will contain variables stars, active galactic nuclei (AGNs), supernovae (SNs) or even new types of variables, reaching an unprecedented depth (V$leq$27 mag). At the end of the project, the first release of the HCV will be available at the Mikulski Archive for Space Telescopes (MAST) and the ESA Hubble Science Archives. The HCV pipeline will be deployed at the Space Telescope Science Institute (STScI) so that an updated HCV may be generated following future releases of HSC.
High precision Kepler photometry is used to explore the details of AGB light curves. Since AGB variability has a typical time scale on order of a year we discuss at length the removal of long term trends and quarterly changes in Kepler data. Photometry for a small sample of nine SR AGB stars are examined using a 30 minute cadence over a period of 45 months. While undergoing long period variations of many magnitudes, the light curves are shown to be smooth at the millimagnitude level over much shorter time intervals. No flares or other rapid events were detected on the sub-day time scale. The shortest AGB period detected is on the order of 100 days. All the SR variables in our sample are shown to have multiple modes. This is always the first overtone typically combined with the fundamental. A second common characteristic of SR variables is shown to be the simultaneous excitation of multiple closely separated periods for the same overtone mode. Approximately half the sample had a much longer variation in the light curve, likely a long secondary period. The light curves were all well represented by a combination of sinusoids. However, the properties of the sinusoids are time variable with irregular variations present at low level. No non-radial pulsations were detected. It is argued that the long secondary period variation seen in many SR variables is intrinsic to the star and linked to multiple mode pulsation.
The second Gaia data release (DR2, spring 2018) included a unique all-sky catalogue of large-amplitude long-period variables (LPVs) containing Miras and semi-regular variables. These stars are on the Asymptotic Giant Branch (AGB), and are characterized by high luminosity, changing surface composition, and intense mass loss, that make them of paramount importance for stellar, galactic, and extra-galactic studies. An initial investigation of LPVs in the Large Magellanic Cloud (LMC) from the DR2 catalog of LPVs has revealed the possibility to disentangle O-rich and C-rich stars using a combination of optical Gaia and infrared 2MASS photometry. The so-called Gaia-2MASS diagram constructed to achieve this has further been shown to enable the identification of sub-groups of AGB stars among the O-rich and C-rich LPVs. Here, we extend this initial study of the Gaia-2MASS diagram to the Small Magellanic Cloud and the Galaxy, and use a variability amplitude proxy to identify LPVs from the full Gaia DR2 archive. We show that the remarkable properties found in the LMC also apply to these other stellar systems. Interesting features, moreover, emerge as a result of the different metallicities between the three stellar environments, which we highlight in this exploratory presentation of Gaias potential to study stellar populations harboring LPVs. Finally, we look ahead to the future, and highlight the power of the exploitation of Gaia RP spectra for the identification of carbon stars using solely Gaia data in forthcoming data releases, as revealed in an Image of the Week published by the Gaia consortium on the European Space Agencys web site. These proceedings include three animated images that can be used as outreach material.
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