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Random forest automated supervised classification of Hipparcos periodic variable stars
We present an evaluation of the performance of an automatedclassification of the Hipparcos periodic variable stars into 26 types.The sub-sample with the most reliable variability types available in theliterature is used to train supervised algorithms to characterize thetype dependencies on a number of attributes. The most useful attributesevaluated with the random forest methodology include, in decreasingorder of importance, the period, the amplitude, the V-I colour index,the absolute magnitude, the residual around the folded light-curvemodel, the magnitude distribution skewness and the amplitude of thesecond harmonic of the Fourier series model relative to that of thefundamental frequency. Random forests and a multi-stage scheme involvingBayesian network and Gaussian mixture methods lead to statisticallyequivalent results. In standard 10-fold cross-validation (CV)experiments, the rate of correct classification is between 90 and 100per cent, depending on the variability type. The main mis-classificationcases, up to a rate of about 10 per cent, arise due to confusion betweenSPB and ACV blue variables and between eclipsing binaries, ellipsoidalvariables and other variability types. Our training set and thepredicted types for the other Hipparcos periodic stars are availableonline.
| The RAdial Velocity Experiment (RAVE): Third Data Release
We present the third data release of the RAdial Velocity Experiment(RAVE) which is the first milestone of the RAVE project, releasing thefull pilot survey. The catalog contains 83,072 radial velocitymeasurements for 77,461 stars in the southern celestial hemisphere, aswell as stellar parameters for 39,833 stars. This paper describes thecontent of the new release, the new processing pipeline, as well as anupdated calibration for the metallicity based upon the observation ofadditional standard stars. Spectra will be made available in a futurerelease. The data release can be accessed via the RAVE Web site.
| Distance determination for RAVE stars using stellar models
Aims: We develop a method for deriving distances fromspectroscopic data and obtaining full 6D phase-space coordinates for theRAVE survey's second data release. Methods: We used stellarmodels combined with atmospheric properties from RAVE (effectivetemperature, surface gravity and metallicity) and (J-Ks)photometry from archival sources to derive absolute magnitudes. Incombination with apparent magnitudes, sky coordinates, proper motionsfrom a variety of sources and radial velocities from RAVE, we are ableto derive the full 6D phase-space coordinates for a large sample of RAVEstars. This method is tested with artificial data, Hipparcostrigonometric parallaxes and observations of the open cluster M 67. Results: When we applied our method to a set of 16 146 stars, wefound that 25% (4037) of the stars have relative (statistical) distanceerrors of <35%, while 50% (8073) and 75% (12 110) have relative(statistical) errors smaller than 45% and 50%, respectively. Our varioustests show that we can reliably estimate distances for main-sequencestars, but there is an indication of potential systematic problems withgiant stars owing to uncertainties in the underlying stellar models. Forthe main-sequence star sample (defined as those with log(g) > 4), 25%(1744) have relative distance errors <31%, while 50% (3488) and 75%(5231) have relative errors smaller than 36% and 42%, respectively. Ourfull dataset shows the expected decrease in the metallicity of stars asa function of distance from the Galactic plane. The known kinematicsubstructures in the U and V velocity components of nearby dwarf starsare apparent in our dataset, confirming the accuracy of our data and thereliability of our technique. We provide independent measurements of theorientation of the UV velocity ellipsoid and of the solar motion, andthey are in very good agreement with previous work. Conclusions:The distance catalogue for the RAVE second data release is available athttp://www.astro.rug.nl/~rave,and will be updated in the future to include new data releases.
| Stars with the Largest Hipparcos Photometric Amplitudes
A list of the 2027 stars that have the largest photometric amplitudes inHipparcos Photometry shows that most variable stars are all Miras. Thepercentage of variable types change as a function of amplitude. Thiscompilation should also be of value to photometrists looking forrelatively unstudied, but large amplitude stars.
| On optical studies of high-velocity clouds
Lists of distant objects that can be used to study physical conditionsin, and distances of, 21 cm (Oort) high-velocity clouds are presented.Recent published observations are used to compile positions, velocities,and distances of the clouds.
| Note on the distribution of RR Lyrae variables.
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