I propose a new procedure to estimate the false alarm probability, the measure of significance for peaks of periodograms. The key element of the new procedure is the use of generalized extreme-value ...distributions, the limiting distribution for maxima of variables from most continuous distributions. This technique allows reliable extrapolation to the very high probability levels required by multiple hypothesis testing, and enables the derivation of confidence intervals for the estimated levels. The estimates are stable against deviations from distributional assumptions, which are otherwise usually made either about the observations themselves or about the theoretical univariate distribution of the periodogram. The quality and the performance of the procedure are demonstrated on simulations and on two multimode variable stars from Sloan Digital Sky Survey Stripe 82. PUBLICATION ABSTRACT
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 (CV) experiments, the rate of correct classification is between 90 and 100 per cent, depending on the variability type. The main mis-classification cases, up to a rate of about 10 per cent, 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.
Gaia Data Release 3 Creevey, O. L.; Sordo, R.; Pailler, F. ...
Astronomy and astrophysics (Berlin),
06/2023, Letnik:
674
Journal Article
Recenzirano
Odprti dostop
Gaia
Data Release 3 contains a wealth of new data products for the community. Astrophysical parameters are a major component of this release, and were produced by the Astrophysical parameters ...inference system (Apsis) within the
Gaia
Data Processing and Analysis Consortium (DPAC). The aim of this paper is to describe the overall content of the astrophysical parameters in
Gaia
DR3 and how they were produced. In Apsis, we use the mean BP/RP and mean RVS spectra along with astrometry and photometry, and we derive the following parameters: source classification and probabilities for 1.6 billion objects; interstellar medium characterisation and distances for up to 470 million sources, including a 2D total Galactic extinction map; 6 million redshifts of quasar candidates; 1.4 million redshifts of galaxy candidates; and an analysis of 50 million outlier sources through an unsupervised classification. The astrophysical parameters also include many stellar spectroscopic and evolutionary parameters for up to 470 million sources. These comprise
T
eff
, log
g
, and M/H (470 million using BP/RP, 6 million using RVS), radius (470 million), mass (140 million), age (120 million), chemical abundances (up to 5 million), diffuse interstellar band analysis (0.5 million), activity indices (2 million), H
α
equivalent widths (200 million), and further classification of spectral types (220 million) and emission-line stars (50 000). This paper is the first in a series of three papers, and focusses on describing the global content of the parameters in
Gaia
DR3. The accompanying Papers II and III focus on the validation and use of the stellar and non-stellar products, respectively. This catalogue is the most extensive homogeneous database of astrophysical parameters to date, and is based uniquely on
Gaia
data. It will only be superseded by
Gaia
Data Release 4, and will therefore remain a key reference over the next four years, providing astrophysical parameters independent of other ground- and space-based data.
Context. In the new era of large-scale astronomical surveys, automated methods of analysis and classification of bulk data are a fundamental tool for fast and efficient production of deliverables. ...This becomes ever more important as we enter the Gaia era. Aims. We investigate the potential detectability of eclipsing binaries with Gaia using a data set of all Kepler eclipsing binaries sampled with Gaia cadence and folded with the Kepler period. The performance of fitting methods is evaluated in comparison to real Kepler data parameters and a classification scheme is proposed for the potentially detectable sources based on the geometry of the light curve fits. Methods. The polynomial chain (polyfit) and two-Gaussian models are used for light curve fitting of the data set. Classification is performed with a combination of the t-distributed stochastic neighbor embedding (t-SNE) and density-based spatial clustering of applications with noise (DBSCAN) algorithms. Results. We find that ~68% of the Kepler Eclipsing Binary Catalog sources are potentially detectable by Gaia when folded with the Kepler period; we propose a classification scheme of the detectable sources based on the morphological type indicative of the light curve with subclasses that reflect the properties of the fitted model (presence and visibility of eclipses, their width, depth, etc.).
Gaia Data Release 3 Andrae, R.; Fouesneau, M.; Sordo, R. ...
Astronomy and astrophysics (Berlin),
06/2023, Letnik:
674, Številka:
A27
Journal Article
Recenzirano
Odprti dostop
Context.
The astrophysical characterisation of sources is among the major new data products in the third
Gaia
Data Release (DR3). In particular, there are stellar parameters for 471 million sources ...estimated from low-resolution BP/RP spectra.
Aims.
We present the General Stellar Parameterizer from Photometry (GSP-Phot), which is part of the astrophysical parameters inference system (Apsis). GSP-Phot is designed to produce a homogeneous catalogue of parameters for hundreds of millions of single non-variable stars based on their astrometry, photometry, and low-resolution BP/RP spectra. These parameters are effective temperature, surface gravity, metallicity, absolute
M
G
magnitude, radius, distance, and extinction for each star.
Methods.
GSP-Phot uses a Bayesian forward-modelling approach to simultaneously fit the BP/RP spectrum, parallax, and apparent
G
magnitude. A major design feature of GSP-Phot is the use of the apparent flux levels of BP/RP spectra to derive, in combination with isochrone models, tight observational constraints on radii and distances. We carefully validate the uncertainty estimates by exploiting repeat
Gaia
observations of the same source.
Results.
The data release includes GSP-Phot results for 471 million sources with
G
< 19. Typical differences to literature values are 110 K for
T
eff
and 0.2–0.25 for log
g
, but these depend strongly on data quality. In particular, GSP-Phot results are significantly better for stars with good parallax measurements (
ϖ
/
σ
ϖ
> 20), mostly within 2 kpc. Metallicity estimates exhibit substantial biases compared to literature values and are only useful at a qualitative level. However, we provide an empirical calibration of our metallicity estimates that largely removes these biases. Extinctions
A
0
and
A
BP
show typical differences from reference values of 0.07–0.09 mag. MCMC samples of the parameters are also available for 95% of the sources.
Conclusions.
GSP-Phot provides a homogeneous catalogue of stellar parameters, distances, and extinctions that can be used for various purposes, such as sample selections (OB stars, red giants, solar analogues etc.). In the context of asteroseismology or ground-based interferometry, where targets are usually bright and have good parallax measurements, GSP-Phot results should be particularly useful for combined analysis or target selection.
Extreme value analyses of a large number of relatively short time series are in increasing demand in environmental sciences and design. Here, we present an automated procedure for the ...peaks-over-threshold (POT) approach to extreme value theory and use it to provide a climatology of extreme hourly precipitation in Switzerland. The POT approach fits the generalized Pareto distribution (GPD) to independent exceedances above some high threshold. To guarantee independence, the time series is pruned: exceedances separated by less than a fixed interval called the run parameter are considered a cluster, and all but the cluster maxima are discarded. We propose the automation of an existing graphical method for joint selection of threshold and run parameter. Hourly precipitation is analyzed at 59 stations of the MeteoSwiss observational network over the period 1981–2010. The four seasons are considered separately. When necessary, a simple detrending is applied. Results suggest that unnecessarily large run parameters have adverse effects on the estimation of the GPD parameters. The proposed method yields mean cluster sizes that reflect the seasonal and geographical variation of lag dependence of hourly precipitation. The climatology, as represented by the return level maps and Alpine cross-section, mirror known aspects of the Swiss climate. Unlike for daily precipitation, summer thunderstorm tracks are visible in the seasonal frequency of events, rather than in the amplitude of rare events.
Context. Large surveys producing tera- and petabyte-scale databases require machine-learning and knowledge discovery methods to deal with the overwhelming quantity of data and the difficulties of ...extracting concise, meaningful information with reliable assessment of its uncertainty. This study investigates the potential of a few machine-learning methods for the automated analysis of eclipsing binaries in the data of such surveys. Aims. We aim to aid the extraction of samples of eclipsing binaries from such databases and to provide basic information about the objects. We intend to estimate class labels according to two different, well-known classification systems, one based on the light curve morphology (EA/EB/EW classes) and the other based on the physical characteristics of the binary system (system morphology classes; detached through overcontact systems). Furthermore, we explore low-dimensional surfaces along which the light curves of eclipsing binaries are concentrated, and consider their use in the characterization of the binary systems and in the exploration of biases of the full unknown Gaia data with respect to the training sets. Methods. We have explored the performance of principal component analysis (PCA), linear discriminant analysis (LDA), Random Forest classification and self-organizing maps (SOM) for the above aims. We pre-processed the photometric time series by combining a double Gaussian profile fit and a constrained smoothing spline, in order to de-noise and interpolate the observed light curves. We achieved further denoising, and selected the most important variability elements from the light curves using PCA. Supervised classification was performed using Random Forest and LDA based on the PC decomposition, while SOM gives a continuous 2-dimensional manifold of the light curves arranged by a few important features. We estimated the uncertainty of the supervised methods due to the specific finite training set using ensembles of models constructed on randomized training sets. Results. We obtain excellent results (about 5% global error rate) with classification into light curve morphology classes on the Hipparcos data. The classification into system morphology classes using the Catalog and Atlas of Eclipsing binaries (CALEB) has a higher error rate (about 10.5%), most importantly due to the (sometimes strong) similarity of the photometric light curves originating from physically different systems. When trained on CALEB and then applied to Kepler-detected eclipsing binaries subsampled according to Gaia observing times, LDA and SOM provide tractable, easy-to-visualize subspaces of the full (functional) space of light curves that summarize the most important phenomenological elements of the individual light curves. The sequence of light curves ordered by their first linear discriminant coefficient is compared to results obtained using local linear embedding. The SOM method proves able to find a 2-dimensional embedded surface in the space of the light curves which separates the system morphology classes in its different regions, and also identifies a few other phenomena, such as the asymmetry of the light curves due to spots, eccentric systems, and systems with a single eclipse. Furthermore, when data from other surveys are projected to the same SOM surface, the resulting map yields a good overview of the general biases and distortions due to differences in time sampling or population.
Gaia Data Release 3 Fouesneau, M.; Frémat, Y.; Andrae, R. ...
Astronomy and astrophysics (Berlin),
06/2023, Letnik:
674
Journal Article
Recenzirano
Odprti dostop
Context.
The third
Gaia
data release (
Gaia
DR3) contains, beyond the astrometry and photometry, dispersed light for hundreds of millions of sources from the
Gaia
prism spectra (BP and RP) and the ...spectrograph (RVS). This data release opens a new window on the chemo-dynamical properties of stars in our Galaxy, essential knowledge for understanding the structure, formation, and evolution of the Milky Way.
Aims.
To provide insight into the physical properties of Milky Way stars, we used these data to produce a uniformly derived all-sky catalogue of stellar astrophysical parameters: atmospheric properties (
T
eff
, log
g
, M/H,
α
/Fe, activity index, emission lines, and rotation), 13 chemical abundance estimates, evolution characteristics (radius, age, mass, and bolometric luminosity), distance, and dust extinction.
Methods.
We developed the astrophysical parameter inference system (Apsis) pipeline to infer astrophysical parameters of
Gaia
objects by analysing their astrometry, photometry, BP/RP, and RVS spectra. We validate our results against those from other works in the literature, including benchmark stars, interferometry, and asteroseismology. Here we assess the stellar analysis performance from Apsis statistically.
Results.
We describe the quantities we obtained, including the underlying assumptions and the limitations of our results. We provide guidance and identify regimes in which our parameters should and should not be used.
Conclusions.
Despite some limitations, this is the most extensive catalogue of uniformly inferred stellar parameters to date. They comprise
T
eff
, log
g
, and M/H (470 million using BP/RP, 6 million using RVS), radius (470 million), mass (140 million), age (120 million), chemical abundances (5 million), diffuse interstellar band analysis (half a million), activity indices (2 million), H
α
equivalent widths (200 million), and further classifications of spectral types (220 million) and emission-line stars (50 thousand). More precise and detailed astrophysical parameters based on epoch BP, RP, and RVS spectrophotometry are planned for the next
Gaia
data release.
The original version of this article unfortunately contained a mistake. Please find below the relevant part of the Appendix, with changes in the last 2 formulae.
ABSTRACT Classical Cepheid variable stars are crucial calibrators of the cosmic distance scale thanks to a relation between their pulsation periods and luminosities. Their archetype, δ Cephei, is an ...important calibrator for this relation. In this paper, we show that δ Cephei is a spectroscopic binary based on newly obtained high-precision radial velocities. We combine these new data with literature data to determine the orbit, which has period 2201 days, semi-amplitude 1.5 km s−1, and high eccentricity (e = 0.647). We re-analyze Hipparcos intermediate astrometric data to measure δ Cephei's parallax ( mas) and find tentative evidence for an orbital signature, although we cannot claim detection. We estimate that Gaia will fully determine the astrometric orbit. Using the available information from spectroscopy, velocimetry, astrometry, and Geneva stellar evolution models ( ), we constrain the companion mass to within . We discuss the potential of ongoing and previous interactions between the companion and δ Cephei near pericenter passage, informing reported observations of circumstellar material and bow shock. The orbit may have undergone significant changes due to a Kozai-Lidov mechanism driven by the outer (visual and astrometric) companion HD 213307. Our discovery of δ Cephei's nature as a spectroscopic binary exposes a hidden companion and reveals a rich and dynamical history of the archetype of classical Cepheid variables.
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