Search

Start Over Capability Type Simple Cone Search
1261. Automated classification of ASAS variables
ID:
ivo://CDS.VizieR/J/MNRAS/358/30
Title:
Automated classification of ASAS variables
Short Name:
J/MNRAS/358/30
Date:
21 Oct 2021
Publisher:
CDS
Description:
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 the All-Sky Automated Survey 1-2 (ASAS 1-2) by selecting the periodic stars 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 per cent 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 semiperiodic stars, which are classified in six 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 per cent.
1262. Automated classification of HIP variables
ID:
ivo://CDS.VizieR/J/MNRAS/414/2602
Title:
Automated classification of HIP variables
Short Name:
J/MNRAS/414/2602
Date:
21 Oct 2021
Publisher:
CDS
Description:
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.
1263. Automated triage and vetting of TESS candidates
ID:
ivo://CDS.VizieR/J/AJ/158/25
Title:
Automated triage and vetting of TESS candidates
Short Name:
J/AJ/158/25
Date:
21 Oct 2021
Publisher:
CDS
Description:
NASA's Transiting Exoplanet Survey Satellite (TESS) presents us with an unprecedented volume of space-based photometric observations that must be analyzed in an efficient and unbiased manner. With at least ~1000000 new light curves generated every month from full-frame images alone, automated planet candidate identification has become an attractive alternative to human vetting. Here we present a deep learning model capable of performing triage and vetting on TESS candidates. Our model is modified from an existing neural network designed to automatically classify Kepler candidates, and is the first neural network to be trained and tested on real TESS data. In triage mode, our model can distinguish transit-like signals (planet candidates and eclipsing binaries) from stellar variability and instrumental noise with an average precision (the weighted mean of precisions over all classification thresholds) of 97.0% and an accuracy of 97.4%. In vetting mode, the model is trained to identify only planet candidates with the help of newly added scientific domain knowledge, and achieves an average precision of 69.3% and an accuracy of 97.8%. We apply our model on new data from Sector 6, and present 288 new signals that received the highest scores in triage and vetting and were also identified as planet candidates by human vetters. We also provide a homogeneously classified set of TESS candidates suitable for future training.
1264. Automatic galaxy detection & classification
ID:
ivo://CDS.VizieR/J/MNRAS/463/2939
Title:
Automatic galaxy detection & classification
Short Name:
J/MNRAS/463/2939
Date:
21 Oct 2021
Publisher:
CDS
Description:
We present a study on galaxy detection and shape classification using topometric clustering algorithms. We first use the DBSCAN algorithm to extract, from CCD frames, groups of adjacent pixels with significant fluxes and we then apply the DENCLUE algorithm to separate the contributions of overlapping sources. The DENCLUE separation is based on the localization of pattern of local maxima, through an iterative algorithm, which associates each pixel to the closest local maximum. Our main classification goal is to take apart elliptical from spiral galaxies. We introduce new sets of features derived from the computation of geometrical invariant moments of the pixel group shape and from the statistics of the spatial distribution of the DENCLUE local maxima patterns. Ellipticals are characterized by a single group of local maxima, related to the galaxy core, while spiral galaxies have additional groups related to segments of spiral arms. We use two different supervised ensemble classification algorithms: Random Forest and Gradient Boosting. Using a sample of ~=24000 galaxies taken from the Galaxy Zoo 2 main sample with spectroscopic redshifts, and we test our classification against the Galaxy Zoo 2 catalogue. We find that features extracted from our pipeline give, on average, an accuracy of ~=93 per cent, when testing on a test set with a size of 20 per cent of our full data set, with features deriving from the angular distribution of density attractor ranking at the top of the discrimination power.
1265. Automatic stellar spectral classification
ID:
ivo://CDS.VizieR/J/A+A/538/A76
Title:
Automatic stellar spectral classification
Short Name:
J/A+A/538/A76
Date:
21 Oct 2021
Publisher:
CDS
Description:
As part of a project aimed at deriving extinction-distances for thirty-five planetary nebulae, spectra of a few thousand stars were analyzed to determine their spectral type and luminosity class. We present here the automatic spectral classification process used to classify stellar spectra. This system can be used to classify any other stellar spectra with similar or higher signal-to-noise ratios. Spectral classification was performed using a system of artificial neural networks that were trained with a set of line-strength indices selected among the spectral lines most sensitive to temperature and the best luminosity tracers. The training and validation processes of the neural networks are discussed and the results of additional validation probes, designed to ensure the accuracy of the spectral classification, are presented.
1266. Autoregressive planet search for Kepler stars
ID:
ivo://CDS.VizieR/J/AJ/158/58
Title:
Autoregressive planet search for Kepler stars
Short Name:
J/AJ/158/58
Date:
21 Oct 2021
Publisher:
CDS
Description:
The 4 yr light curves of 156717 stars observed with NASA's Kepler mission are analyzed using the autoregressive planet search (ARPS) methodology described by Caceres et al. (2019AJ....158...57C). The three stages of processing are maximum-likelihood ARIMA modeling of the light curves to reduce stellar brightness variations, constructing the transit comb filter periodogram to identify transit-like periodic dips in the ARIMA residuals, and Random Forest classification trained on Kepler team confirmed planets using several dozen features from the analysis. Orbital periods between 0.2 and 100 days are examined. The result is a recovery of 76% of confirmed planets, 97% when period and transit depth constraints are added. The classifier is then applied to the full Kepler data set; 1004 previously noticed and 97 new stars have light-curve criteria consistent with the confirmed planets, after subjective vetting removes clear false alarms and false positive cases. The 97 Kepler ARPS candidate transits mostly have periods of P<10 days; many are ultrashort period hot planets with radii <1% of the host star. Extensive tabular and graphical output from the ARPS time series analysis is provided to assist in other research relating to the Kepler sample.
1267. Autoregressive planet search: irregular time series
ID:
ivo://CDS.VizieR/J/AJ/158/59
Title:
Autoregressive planet search: irregular time series
Short Name:
J/AJ/158/59
Date:
21 Oct 2021
Publisher:
CDS
Description:
Sensitive signal processing methods are needed to detect transiting planets from ground-based photometric surveys. Caceres et al. (2019AJ....158...58C) show that the autoregressive planet search (ARPS) method - a combination of autoregressive integrated moving average (ARIMA) parametric modeling, a new transit comb filter (TCF) periodogram, and machine learning classification - is effective when applied to evenly spaced light curves from space-based missions. We investigate here whether ARIMA and TCF will be effective for ground-based survey light curves that are often sparsely sampled with high noise levels from atmospheric and instrumental conditions. The ARPS procedure is applied to selected light curves with strong planetary signals from the Kepler mission that have been altered to simulate the conditions of ground-based exoplanet surveys. Typical irregular cadence patterns are used from the Hungarian-made Automated Telescope Network-South (HATSouth) survey. We also evaluate recovery of known planets from HATSouth. Simulations test transit signal recovery as a function of cadence pattern and duration, stellar magnitude, planet orbital period, and transit depth. Detection rates improve for shorter periods and deeper transits. The study predicts that the ARPS methodology will detect planets with >~0.1% transit depth and periods ~<40 days in HATSouth stars brighter than ~15 mag. ARPS methodology is therefore promising for planet discovery from ground-based exoplanet surveys with sufficiently dense cadence patterns.
1268. A variable star census in a Perseus field
ID:
ivo://CDS.VizieR/J/AJ/142/114
Title:
A variable star census in a Perseus field
Short Name:
J/AJ/142/114
Date:
21 Oct 2021
Publisher:
CDS
Description:
The Berlin Exoplanet Search Telescope is a small-aperture, wide-field telescope dedicated to time-series photometric observations. During an initial commissioning phase at the Thueringer Landessternwarte Tautenburg, Germany, and subsequent operations at the Observatoire de Haute-Provence, France, a 10{deg}^2^ circumpolar field close to the galactic plane centered at (RA, DE) = (02:39:23, +52:01:46) (J2000.0) was observed between 2001 August and 2006 December during 52 nights. From the 32129 stars observed, a subsample of 145 stars with clear stellar variability was detected out of which 125 are newly identified variable objects. For five bright objects, the system parameters were derived by modeling the light curve.
1269. Averaged Stellar Radial Velocities
ID:
ivo://CDS.VizieR/III/161
Title:
Averaged Stellar Radial Velocities
Short Name:
III/161
Date:
21 Oct 2021
Publisher:
CDS
Description:
This catalog contains means of measurements of radial velocities of galactic stars. The data supplement the catalogs of Wilson (1953) <III/21> and Evans (1978) <III/47> with observations published through December 1980. There are new mean velocities for 6023 stars with new radial velocity data; more than 4500 of these stars are not in the earlier catalogs. A weighting scheme was used to form the mean velocities with data from cross-correlation spectrometers given highest weight and low dispersion (less than 100 A/mm) spectra given lowest weight. No systematic zero-point corrections were made but observations were taken from the literature only if they were standardized to the IAU or Wilson (1953) systems.
1270. Avg pitch angles & spiral amplitudes in S4G
ID:
ivo://CDS.VizieR/J/A+A/631/A94
Title:
Avg pitch angles & spiral amplitudes in S4G
Short Name:
J/A+A/631/A94
Date:
21 Oct 2021
Publisher:
CDS
Description:
Spiral galaxies are very common in the local Universe, but their formation, evolution, and interplay with bars remain poorly understood after more than a century of astronomical research on the topic. We use a sample of 391 nearby galaxies from the S4G survey to characterise the winding angle and amplitude of spiral arms as a function of disc properties, such as bar strength, in all kinds of spirals (grand-design, multi-armed, and flocculent). We derived global pitch angles in 3.6um de-projected images from i) average measurements of individual logarithmic spiral segments, and ii) for a subsample of 32 galaxies, from 2-D Fourier analyses. The strength of spirals was quantified from the tangential-to-radial force ratio and from the normalised m=2 Fourier density amplitudes. In galaxies with more than one measured logarithmic segment, the spiral pitch angle varies on average by ~10{deg} between segments, but by up to >=15-20{deg}. The distribution of the global pitch angle versus Hubble type (T) is very similar for barred and non-barred galaxies when 1<=T<=5. Most spiral galaxies (>90%) are barred for T>5. The pitch angle is not correlated with bar strength, and only weakly with spiral strength. The amplitude of spirals is correlated with bar strength (and less tightly, with bar length) for all types of spirals. The mean pitch angle is hardly correlated with the mass of the supermassive black hole (estimated from central stellar velocity dispersion), with central stellar mass concentration, or with shear, questioning previous results in the literature using smaller samples. We do not find observational evidence that spiral arms are driven by stellar bars or by invariant manifolds. Most likely, discs that are prone to the development of strong bars are also reactive to the formation of prominent spirals, explaining the observed coupling between bar and spiral amplitudes.

Limit your search

more »

more »

more »

more »

  • 218,078
  • 111

more »

more »