Automated supervised classification of variable stars I. Methodology

The fast classification of new variable stars is an important step in making them available for further research. Selection of science targets from large databases is much more efficient if they have been classified first. Defining the classes in terms of physical parameters is also important to get an unbiased statistical view on the variability mechanisms and the borders of instability strips. Our goal is twofold: provide an overview of the stellar variability classes that are presently known, in terms of some relevant stellar parameters; use the class descriptions obtained as the basis for an automated `supervised classification' of large databases. Such automated classification will compare and assign new objects to a set of pre-defined variability training classes. For every variability class, a literature search was performed to find as many well-known member stars as possible, or a considerable subset if too many were present. Next, we searched on-line and private databases for their light curves in the visible band and performed period analysis and harmonic fitting. The derived light curve parameters are used to describe the classes and define the training classifiers. We compared the performance of different classifiers in terms of percentage of correct identification, of confusion among classes and of computation time. We describe how well the classes can be separated using the proposed set of parameters and how future improvements can be made, based on new large databases such as the light curves to be assembled by the CoRoT and Kepler space missions.Comment: This paper has been accepted for publication in Astronomy and Astrophysics (reference AA/2007/7638) Number of pages: 27 Number of figures: 1

How semiregular are irregular variables?

We investigate the question whether there is a real difference in the light change between stars classified as semiregular (SRV) or irregular (Lb) variables by analysing photometric light curves of 12 representatives of each class. Using Fourier analysis we try to find a periodic signal in each light curve and determine the S/N of this signal. For all stars, independent of their variability class we detect a period above the significance threshold. No difference in the measured S/N between the two classes could be found. We propose that the Lb stars can be seen as an extension of the SRVs towards shorter periods and smaller amplitudes. This is in agreement with findings from other quantities which also showed no marked difference between the two classes.Comment: 7 pages, accepted for publication by A

Global stellar variability study in the field-of-view of the Kepler satellite

We present the results of an automated variability analysis of the Kepler public data measured in the first quarter (Q1) of the mission. In total, about 150 000 light curves have been analysed to detect stellar variability, and to identify new members of known variability classes. We also focus on the detection of variables present in eclipsing binary systems, given the important constraints on stellar fundamental parameters they can provide. The methodology we use here is based on the automated variability classification pipeline which was previously developed for and applied successfully to the CoRoT exofield database and to the limited subset of a few thousand Kepler asteroseismology light curves. We use a Fourier decomposition of the light curves to describe their variability behaviour and use the resulting parameters to perform a supervised classification. Several improvements have been made, including a separate extractor method to detect the presence of eclipses when other variability is present in the light curves. We also included two new variability classes compared to previous work: variables showing signs of rotational modulation and of activity. Statistics are given on the number of variables and the number of good candidates per class. A comparison is made with results obtained for the CoRoT exoplanet data. We present some special discoveries, including variable stars in eclipsing binary systems. Many new candidate non-radial pulsators are found, mainly Delta Sct and Gamma Dor stars. We have studied those samples in more detail by using 2MASS colours. The full classification results are made available as an online catalogue.Comment: 15 pages, 5 figures, Accepted for publication in Astronomy and Astrophysics on 09/02/201

Automated supervised classification of variable stars II. Application to the OGLE database

We aim to extend and test the classifiers presented in a previous work against an independent dataset. We complement the assessment of the validity of the classifiers by applying them to the set of OGLE light curves treated as variable objects of unknown class. The results are compared to published classification results based on the so-called extractor methods.Two complementary analyses are carried out in parallel. In both cases, the original time series of OGLE observations of the Galactic bulge and Magellanic Clouds are processed in order to identify and characterize the frequency components. In the first approach, the classifiers are applied to the data and the results analyzed in terms of systematic errors and differences between the definition samples in the training set and in the extractor rules. In the second approach, the original classifiers are extended with colour information and, again, applied to OGLE light curves. We have constructed a classification system that can process huge amounts of time series in negligible time and provide reliable samples of the main variability classes. We have evaluated its strengths and weaknesses and provide potential users of the classifier with a detailed description of its characteristics to aid in the interpretation of classification results. Finally, we apply the classifiers to obtain object samples of classes not previously studied in the OGLE database and analyse the results. We pay specific attention to the B-stars in the samples, as their pulsations are strongly dependent on metallicity.Comment: 42 pages, 39 figures. Accepted for publication in Astronomy and Astrophysic

The Many-faceted Light Curves of Young Disk-bearing Stars in Upper Sco –– Oph Observed by K2 Campaign 2

The K2 Mission has photometrically monitored thousands of stars at high precision and cadence in a series of ~80-day campaigns focused on sections of the ecliptic plane. During its second campaign, K2 targeted over 1000 young stellar objects (YSOs) in the ~1–3 Myr ρ Ophiuchus and 5–10 Myr Upper Scorpius regions. From this set, we have carefully vetted photometry from WISE and Spitzer to identify those YSOs with infrared excess indicative of primordial circumstellar disks. We present here the resulting comprehensive sample of 288 young disk-bearing stars from B through M spectral types and analysis of their associated K2 light curves. Using statistics of periodicity and symmetry, we categorize each light curve into eight different variability classes, notably including "dippers" (fading events), "bursters" (brightening events), stochastic, and quasi-periodic types. Nearly all (96%) of disk-bearing YSOs are identified as variable at 30-minute cadence with the sub-1% precision of K2. Combining our variability classifications with (circum)stellar properties, we find that the bursters, stochastic sources, and the largest amplitude quasi-periodic stars have larger infrared colors, and hence stronger circumstellar disks. They also tend to have larger Hα equivalent widths, indicative of higher accretion rates. The dippers, on the other hand, cluster toward moderate infrared colors and low Hα. Using resolved disk observations, we further find that the latter favor high inclinations, except for a few notable exceptions with close to face-on disks. These observations support the idea that YSO time-domain properties are dependent on several factors, including accretion rate and view angle

Ground-based observations of the beta Cephei CoRoT main target HD 180642: abundance analysis and mode identification

The known beta Cephei star HD 180642 was observed by the CoRoT satellite in 2007. From the very high-precision light curve, its pulsation frequency spectrum could be derived for the first time (Degroote and collaborators). In this paper, we obtain additional constraints for forthcoming asteroseismic modeling of the target. Our results are based on both extensive ground-based multicolour photometry and high-resolution spectroscopy. We determine T_eff = 24 500+-1000 K and log g = 3.45+-0.15 dex from spectroscopy. The derived chemical abundances are consistent with those for B stars in the solar neighbourhood, except for a mild nitrogen excess. A metallicity Z = 0.0099+-0.0016 is obtained. Three modes are detected in photometry. The degree l is unambiguously identified for two of them: l = 0 and l = 3 for the frequencies 5.48694 1/d and 0.30818 1/d, respectively. The radial mode is non-linear and highly dominant with an amplitude in the U-filter about 15 times larger than the strongest of the other modes. For the third frequency of 7.36673 1/d found in photometry, two possibilities remain: l = 0 or 3. In the radial velocities, the dominant radial mode presents a so-called stillstand but no clear evidence of the existence of shocks is observed. Four low-amplitude modes are found in spectroscopy and one of them, with frequency 8.4079 1/d, is identified as (l,m)=(3,2). Based on this mode identification, we finally deduce an equatorial rotational velocity of 38+-15 km/s.Comment: Accepted for publication in Astronomy and Astrophysic

An Upper Limit on the Albedo of HD 209458b: Direct Imaging Photometry with the MOST Satellite

We present space-based photometry of the transiting exoplanetary system HD 209458 obtained with the MOST (Microvariablity and Oscillations of STars) satellite, spanning 14 days and covering 4 transits and 4 secondary eclipses. The HD 209458 photometry was obtained in MOST's lower-precision Direct Imaging mode, which is used for targets in the brightness range $6.5 < V < 13$. We describe the photometric reduction techniques for this mode of observing, in particular the corrections for stray Earthshine. We do not detect the secondary eclipse in the MOST data, to a limit in depth of 0.053 mmag (1 \sigma). We set a 1 \sigma upper limit on the planet-star flux ratio of 4.88 x 10^-5 corresponding to a geometric albedo upper limit in the MOST bandpass (400 to 700 nm) of 0.25. The corresponding numbers at the 3 \sigma level are 1.34 x 10^-4 and 0.68 respectively. HD 209458b is half as bright as Jupiter in the MOST bandpass. This low geometric albedo value is an important constraint for theoretical models of the HD209458b atmosphere, in particular ruling out the presence of reflective clouds. A second MOST campaign on HD 209458 is expected to be sensitive to an exoplanet albedo as low as 0.13 (1 sigma), if the star does not become more intrinsically variable in the meantime.Comment: 29 pages, 9 figures. Accepted for publication in the Astrophysical Journal (July 2006, v645n1

Using a multiperiodic linear programming model and a simulation programme for competing field crops and energy orchards

Considering the land use of Hungary, there is a need to develop a rationale land use in which, beside the less-favoured areas, the use of set-aside areas are also permitted. There are several opportunities to utilize the less-favoured areas. We prepared a multiperiodic linear programming model in order to model the crop structure, in which field crops with woody energy orchards were also competed. After having each field and orchard technology compiled, we set the dynamic simulation model, that we prepared in MS Excel. After running the model we analyzed the shadow prices of the constraints and the marginal cost of variables. Considering the result of the analysis and the professional information we made a sensitivity analysis, which gave a basis to create new decision variants. The results of linear programming model were compared with those of Monte Cralo simulation’s, where we managed the enterprises’ profit contribution as probability variable with normal distribution in the course of modelling