Variable Stars
This is the triennial report of IAU Commission 27, mostly presenting a review of recent advances in the field.
astro-ph.SR↗
arXiv subjects
L. Eyer
Publications and source records attributed to L. Eyer.
Long Period Variables in the Large Magellanic Cloud from the EROS-2 survey
Context. The EROS-2 survey has produced a database of millions of time series from stars monitored for more than six years, allowing to classify some of their sources into different variable star types. Among these, Long Period Variables (LPVs), known to follow sequences in the period-luminosity diagram, include long secondary period variables whose variability origin is still a matter of debate. Aims.We use the 856 864 variable stars available from the Large Magellanic Cloud (LMC) in the EROS-2 database to detect, classify and characterize LPVs. Methods. Our method to extract LPVs is based on the statistical Abbe test. It investigates the regularity of the light curve with respect to the survey duration in order to extract candidates with long-term variability. The period search is done by Deeming, Lomb-Scargle and generalized Lomb-Scargle methods, combined with Fourier series fit. Color-magnitude, period-magnitude and period-amplitude diagrams are used to characterize our candidates. Results. We present a catalog of 43 551 LPV candidates for the Large Magellanic Cloud. For each of them, we provide up to five periods, mean magnitude in EROS-2, 2MASS and Spitzer bands, BE-RE color, RE amplitude and spectral type.We use infrared data to make the distinction between RGB, O-rich, C-rich and extreme AGB stars. Properties of our LPV candidates are investigated by analyzing period-luminosity and period-amplitude diagrams.
astro-ph.SR↗
Long Period Variables in the Magellanic Clouds with EROS-2 survey
We use the EROS-2 database to analyze Long Period Variables (LPVs) in the Magellanic Clouds. It results in the creation of a catalog of more than 40 000 LPV candidates which is briefly introduced here.
astro-ph.SR↗
Hipparcos Variable Star Detection and Classification Efficiency
A complete periodic star extraction and classification scheme is set up and tested with the Hipparcos catalogue. The efficiency of each step is derived by comparing the results with prior knowledge coming from the catalogue or from the literature. A combination of two variability criteria is applied in the first step to select 17 006 variability candidates from a complete sample of 115 152 stars. Our candidate sample turns out to include 10 406 known variables (i.e., 90% of the total of 11 597) and 6600 contaminating constant stars. A random forest classification is used in the second step to extract 1881 (82%) of the known periodic objects while removing entirely constant stars from the sample and limiting the contamination of non-periodic variables to 152 stars (7.5%). The confusion introduced by these 152 non-periodic variables is evaluated in the third step using the results of the Hipparcos periodic star classification presented in a previous study (Dubath et al. [1]).
astro-ph.SR↗
Random forest automated supervised classification of Hipparcos periodic variable stars
We present an evaluation of the performance of an automated classification of the Hipparcos periodic variable stars into 26 types. The sub-sample with the most reliable variability types available in the literature is used to train supervised algorithms to characterize the type dependencies on a number of attributes. The most useful attributes evaluated with the random forest methodology include, in decreasing order of importance, the period, the amplitude, the V-I colour index, the absolute magnitude, the residual around the folded light-curve model, the magnitude distribution skewness and the amplitude of the second harmonic of the Fourier series model relative to that of the fundamental frequency. Random forests and a multi-stage scheme involving Bayesian network and Gaussian mixture methods lead to statistically equivalent results. In standard 10-fold cross-validation experiments, the rate of correct classification is between 90 and 100%, depending on the variability type. The main mis-classification cases, up to a rate of about 10%, arise due to confusion between SPB and ACV blue variables and between eclipsing binaries, ellipsoidal variables and other variability types. Our training set and the predicted types for the other Hipparcos periodic stars are available online.
astro-ph.SR↗
gamma Doradus stars in the COROT exoplanets fields: first inspection
We present here preliminary results concerning 32 stars identified as main gamma Doradus candidates by the COROT Variable Classifier (CVC) among the 4 first fields of the exoplanet CCDs.
astro-ph.SR↗
Detecting short period variable stars with Gaia
We analyzed the frequency domain of time series of simulated ZZ Ceti light-curves to investigate the detectability and period recovery performance of short period variables (periods < 2 hours) for the Gaia mission. In our analysis, first we used a non-linear ZZ Ceti light-curves simulator code to simulate the variability of ZZ Ceti stars (we assumed stationary power spectra over five years). Second we used the Gaia nominal scanning law and the expected photometric precision of Gaia to simulate ZZ Ceti time series with Gaia's time sampling and photometric errors. Then we performed a Fourier analysis of these simulated time series. We found that a correct period can be recovered in ~65% of the cases if we consider Gaia per CCD time series of a G ~ 18 magnitude multiperiodic ZZ Ceti star with 5%-10% light-curve variation. In the pre-whitened power spectrum a second correct period was also recovered in ~26% of the cases.
astro-ph.IM↗
Variability type classification of multi-epoch surveys
The classification of time series from photometric large scale surveys into variability types and the description of their properties is difficult for various reasons including but not limited to the irregular sampling, the usually few available photometric bands, and the diversity of variable objects. Furthermore, it can be seen that different physical processes may sometimes produce similar behavior which may end up to be represented as same models. In this article we will also be presenting our approach for processing the data resulting from the Gaia space mission. The approach may be classified into following three broader categories: supervised classification, unsupervised classifications, and "so-called" extractor methods i.e. algorithms that are specialized for particular type of sources. The whole process of classification- from classification attribute extraction to actual classification- is done in an automated manner.
astro-ph.IM↗
A study of supervised classification of Hipparcos variable stars using PCA and Support Vector Machines
We report on the automated classification of Hipparcos variable stars by a supervised classification algorithm known as Support Vector Machines. The dataset comprised about 3200 stars, each characterized by 51 features. These are the B-V and V-I colours, the skewness of the lightcurve, the median subtracted 10-percentiles and forty bins from the Fourier envelope of the lightcurve. We also tested whether the classification performance can be improved by using the most significant principal components calculated from this dataset. We show that the overall classification performance (as measured by the fraction of true positives) on the original dataset is of the order of 62%. For about 9 of the 18 different variability classes, the classification accuracy is significantly larger than 60% (up to 98%). Introducing principal components does not significantly improve this result. We further find that many of the different variability classes are not very distinct and possibly poorly defined, i.e. there exists a considerable class overlap. It is concluded that this `contamination' of the template set implies minimum errors and thus degrades the overall performance.
astro-ph↗
Gaia: Organisation and challenges for the data processing
Gaia is an ambitious space astrometry mission of ESA with a main objective to map the sky in astrometry and photometry down to a magnitude 20 by the end of the next decade. While the mission is built and operated by ESA and an industrial consortium, the data processing is entrusted to a consortium formed by the scientific community, which was formed in 2006 and formally selected by ESA one year later. The satellite will downlink around 100 TB of raw telemetry data over a mission duration of 5 years from which a very complex iterative processing will lead to the final science output: astrometry with a final accuracy of a few tens of microarcseconds, epoch photometry in wide and narrow bands, radial velocity and spectra for the stars brighter than 17 mag. We discuss the general principles and main difficulties of this very large data processing and present the organisation of the European Consortium responsible for its design and implementation.
astro-ph↗
Gaia Data Processing Architecture
Gaia is ESA's ambitious space astrometry mission the main objective of which is to astrometrically and spectro-photometrically map 1000 Million celestial objects (mostly in our galaxy) with unprecedented accuracy. The announcement of opportunity for the data processing will be issued by ESA late in 2006. The Gaia Data Processing and Analysis Consortium (DPAC) has been formed recently and is preparing an answer. The satellite will downlink close to 100 TB of raw telemetry data over 5 years. To achieve its required accuracy of a few 10s of Microarcsecond astrometry, a highly involved processing of this data is required. In addition to the main astrometric instrument Gaia will host a Radial Velocity instrument, two low-resolution dispersers for multi-color photometry and two Star Mappers. Gaia is a flying Giga Pixel camera. The various instruments each require relatively complex processing while at the same time being interdependent. We describe the overall composition of the DPAC and the envisaged overall architecture of the Gaia data processing system. We shall delve further into the core processing - one of the nine, so-called, coordination units comprising the Gaia processing system.
astro-ph↗
Observational results for northern and southern (candidate) gamma Doradus stars
We report on observational results obtained for 78 objects originally classified as bona-fide or candidate gamma Doradus stars. For the southern objects, we gathered echelle spectra with the CORALIE spectrograph attached to the Euler telescope in 1998-2003 and/or Johnson-Cousins B,V,Ic observations with the MODULAR photometer attached to the 0.5-m SAAO telescope in 1999-2000. For the northern objects, we obtained Geneva U,B,B1,B2,V,V1,G observations with the P7 photometer attached to the 1.2-m MERCATOR telescope in 2001-2004. At least 15 of our objects are binaries, of which 7 are new. For 6 binaries, we determined the orbit for the first time. At least 17 objects show profile variations and at least 12 objects are multiperiodic photometric variables. Our results allow us to upgrade 11 objects to bona-fide gamma Doradus stars and to downgrade 8 objects to constant up to the current detection limits. Mode identification is still ongoing, but so far, only l = 1 and 2 modes have been identified.
astro-ph↗
A spectroscopic study of southern (candidate) gamma Doradus stars. I. Time series analysis
We present results of a spectroscopic study of 37 southern (candidate) gamma Doradus stars based on echelle spectra. The observed spectra were cross-correlated with the standard template spectrum of an F0-type star for an easier detection of binary and intrinsic variations. We identified 15 objects as spectroscopic binaries, including 7 new ones, and another 3 objects are binary suspects. At least 12 objects show composite spectra. We could determine the orbital parameters for 9 binaries, of which 4 turn out to be ellipsoidal variables. For 6 binaries, we estimated the expected time-base of the orbital variations. Clear profile variations are observed for 17 objects, pointing towards stellar pulsation. For 8 of them, we have evidence that the main spectroscopic and photometric periods coincide. Our results, in combination with prior knowledge from the literature, lead to the classification of 10 objects as new bona-fide gamma Doradus stars, 1 object as new bona-fide delta Scuti star, and 8 objects as constant stars. Finally, we determined the projected rotational velocity with two independent methods. The resulting vsini values range from 3 to 135 km/s. For the bona-fide gamma Doradus stars, the majority has vsini below 60 km/s.
astro-ph↗
Discovery of nine quasars behind the Large Magellanic Cloud
We present the discovery of nine quasars behind the Large Magellanic Cloud, with emission redshifts ranging from 0.07 to 2.0. Six of them were identified as part of the systematic variability-based search for QSOs in the objects from the OGLE-II database. Combination of variability-based selection of candidates with the candidates' colours appears to be a powerful technique for identifying quasars, potentially reaching ca. 50% efficiency. We report an apparent correlation between variability magnitude and variability timescale, which - if confirmed - could put even more constraints on QSO candidate selection. The remaining three quasars were identified via followup spectroscopy of optical counterparts to X-ray sources found serendipitously by the Chandra X-ray Observatory satellite. Even though the locations of the candidates were quite uniformly distributed over the LMC bar, the confirmed QSOs all appear near the bar's outskirts.
astro-ph↗
Period recovery success rate expected with Gaia
The Gaia satellite was selected as a cornerstone mission of the European Space Agency (ESA) in October 2000 and confirmed in 2002 with a current target launch date of 2011. The Gaia mission will gather on the same observational principles as Hipparcos detailed astrometric, photometric and spectroscopic properties of about 1 billion sources brighter than mag V=20. The nature of the measured objects ranges from NEOs to gamma ray burst afterglows and encompasses virtually any kind of stars in our Galaxy. Gaia will provide multi-colour (in about 20 passbands extending over the visible range) photometry with typically 250 observations distributed over 40 well separated epochs during the 5-year mission. The multi-epoch nature of the project will permit to detect and analyse variable sources whose number is currently estimated in the range of several tens of million, among the detectable sources. In this paper, we assess the performances of Gaia in analysing photometric periodic phenomena. We first present quickly the overall observational principle before discussing the implication of the scanning law in the time sampling. Then from extensive simulations one assesses the performances in the recovery of periodic signals as a function of the period, signal-to-noise ratio and position on the sky for simple sinusoidal variability.
astro-ph↗
Variability-selected QSO candidates in OGLE-II Galactic Bulge fields
We present 97 QSO candidates in 48 Galactic Bulge fields of the Optical Gravitational Lensing Experiment II (OGLE-II) covering about 11 square degrees, which are selected via their variability. We extend light curves of variable objects which were detected in 3-year baseline in the OGLE-II variable star catalog to 4th year. We search for objects which are faint (16<I_0<18.5) and slowly variable during 4 years in this catalog by using the variogram/structure function. Finding the QSOs in such stellar-crowded and high extinction fields is challenging, but should be useful for the astrometric reference frame. Spectroscopic follow-up observations are required to confirm these QSO candidates. Follow-up observations are being prepared for four of these fields (BUL_SC1, 2, 32 and 45). Follow-up observations for other fields are strongly encouraged. The complete list and light curves of all 97 candidates are available in electronic format at http://www.astro.princeton.edu/~sumi/QSO-OGLEII/.
astro-ph↗
A purely geometric distance to the binary star Atlas, a member of the Pleiades
We present radial velocity and new interferometric measurements of the double star Atlas, which permit, with the addition of published interferometric data, to precisely derive the orbital parameters of the binary system and the masses of the components. The derived semi-major axis, compared with its measured angular size, allows to determine a distance to Atlas of 132+-4 pc in a purely geometrical way. Under the assumption that the location of Atlas is representative of the average distance of the cluster, we confirm the distance value generally obtained through main sequence fitting, in contradiction with the early Hipparcos result (118.3+-3.5 pc).
astro-ph↗
Automated classification of variable stars for ASAS 1-2 data
With the advent of surveys generating multi-epoch photometry and the discovery of large numbers of variable stars, the classification of these stars has to be automatic. We have developed such a classification procedure for about 1700 stars from the variable star catalogue of ASAS 1-2 (All Sky Automated Survey, Pojmanski 2000) by selecting the periodic ones and by applying an unsupervised Bayesian classifier using parameters obtained through a Fourier decomposition of the light curve. For irregular light curves we used the period and moments of the magnitude distribution for the classification. In the case of ASAS 1-2, 83% of variable objects are red giants. A general relation between the period and amplitude is found for a large fraction of those stars. The selection led to 302 periodic and 1429 semi-periodic stars which are classified in 6 major groups: eclipsing binaries, "sinusoidal curves", Cepheids, small amplitude red variables, SR and Mira stars. The type classification error level is estimated to be about 7%.
astro-ph↗