The Lomb-Scargle periodogram is a well-known algorithm for detecting and characterizing periodic signals in unevenly-sampled data. This paper presents a conceptual introduction to the Lomb-Scargle periodogram and important practical considerations for its use. Rather than a rigorous mathematical treatment, the goal of this paper is to build intuition about what assumptions are implicit in the use of the Lomb-Scargle periodogram and related estimators of periodicity, so as to motivate important practical considerations required in its proper application and interpretation.

https://iopscience.iop.org/article/10.3847/1538-4365/aab766/pdf

Understanding the Lomb–Scargle Periodogram

Work aimed at compiling detailed catalogs of variable stars in the Galaxy, which has been carried out continuously by Moscow variable-star researchers since 1946 on behalf of the International Astronomical Union, has entered the stage of the publication of the 5th, completely electronic edition of the General Catalogue of Variable Stars (GCVS). This paper describes the requirements for the contents of the 5th edition and the current state of the catalog in its new version, GCVS 5.1. The complete revision of information for variable stars in the constellation Carina and the compilation of the 81st Name-list of Variable Stars are considered as examples of work on the 5th edition. The GCVS 5.1 is freely accessible on the Internet. We recommend the present paper as a unified reference to the 5th edition of the GCVS.

General catalogue of variable stars: Version GCVS 5.1

We present ~47,000 periodic variables found during the analysis of 5.4 million variable star candidates within a 20,000 deg^2 region covered by the Catalina Surveys Data Release-1 (CSDR1). Combining these variables with type ab RR Lyrae from our previous work, we produce an online catalog containing periods, amplitudes, and classifications for ~61,000 periodic variables. By cross-matching these variables with those from prior surveys, we find that >90% of the ~8000 known periodic variables in the survey region are recovered. For these sources, we find excellent agreement between our catalog and prior values of luminosity, period, and amplitude as well as classification. We investigate the rate of confusion between objects classified as contact binaries and type c RR Lyrae (RRc's) based on periods, colors, amplitudes, metallicities, radial velocities, and surface gravities. We find that no more than a few percent of the variables in these classes are misidentified. By deriving distances for this clean sample of ~5500 RRc's, we trace the path of the Sagittarius tidal streams within the Galactic halo. Selecting 146 outer-halo RRc's with SDSS radial velocities, we confirm the presence of a coherent halo structure that is inconsistent with current N-body simulations of the Sagittarius tidal stream. We also find numerous long-period variables that are very likely associated within the Sagittarius tidal stream system. Based on the examination of 31,000 contact binary light curves we find evidence for two subgroups exhibiting irregular light curves. One subgroup presents significant variations in mean brightness that are likely due to chromospheric activity. The other subgroup shows stable modulations over more than a thousand days and thereby provides evidence that the O'Connell effect is not due to stellar spots.

/pdf/the-catalina-surveys-periodic-variable-star-catalog-479uypsuxj.pdf

The Catalina Surveys Periodic Variable Star Catalog

Context. The Gaia second Data Release (DR2) presents a first mapping of full-sky RR Lyrae stars and Cepheids observed by the spacecraft during the initial 22 months of science operations.Aims. The Specific Objects Study (SOS) pipeline, developed to validate and fully characterise Cepheids and RR Lyrae stars (SOS Cep&RRL) observed by Gaia , has been presented in the documentation and papers accompanying the Gaia first Data Release. Here we describe how the SOS pipeline was modified to allow for processing the Gaia multi-band (G , G BP , and G RP ) time-series photometry of all-sky candidate variables and produce specific results for confirmed RR Lyrae stars and Cepheids that are published in the DR2 catalogue.Methods. The SOS Cep&RRL processing uses tools such as the period–amplitude and the period–luminosity relations in the G band. For the analysis of the Gaia DR2 candidates we also used tools based on the G BP and G RP photometry, such as the period–Wesenheit relation in (G , G RP ).Results. Multi-band time-series photometry and characterisation by the SOS Cep&RRL pipeline are published in Gaia DR2 for 150 359 such variables (9575 classified as Cepheids and 140 784 as RR Lyrae stars) distributed throughout the sky. The sample includes variables in 87 globular clusters and 14 dwarf galaxies (the Magellanic Clouds, 5 classical and 7 ultra-faint dwarfs). To the best of our knowledge, as of 25 April 2018, the variability of 50 570 of these sources (350 Cepheids and 50 220 RR Lyrae stars) has not been reported before in the literature, therefore they are likely new discoveries by Gaia . An estimate of the interstellar absorption is published for 54 272 fundamental-mode RR Lyrae stars from a relation based on the G -band amplitude and the pulsation period. Metallicities derived from the Fourier parameters of the light curves are also released for 64 932 RR Lyrae stars and 3738 fundamental-mode classical Cepheids with periods shorter than 6.3 days.

/pdf/gaia-data-release-2-specific-characterisation-and-validation-304mgmzy5q.pdf

Gaia Data Release 2. Specific characterisation and validation of all-sky Cepheids and RR Lyrae stars

The Gaia Data Release 2 (DR2): we summarise the processing and results of the identification of variable source candidates of RR Lyrae stars, Cepheids, long period variables (LPVs), rotation modulation (BY Dra-type) stars, delta Scuti & SX Phoenicis stars, and short-timescale variables. In this release we aim to provide useful but not necessarily complete samples of candidates. 
The processed Gaia data consist of the G, BP, and RP photometry during the first 22 months of operations as well as positions and parallaxes. Various methods from classical statistics, data mining and time series analysis were applied and tailored to the specific properties of Gaia data, as well as various visualisation tools. 
The DR2 variability release contains: 228'904 RR Lyrae stars, 11'438 Cepheids, 151'761 LPVs, 147'535 stars with rotation modulation, 8'882 delta Scuti & SX Phoenicis stars, and 3'018 short-timescale variables. These results are distributed over a classification and various Specific Object Studies (SOS) tables in the Gaia archive, along with the three-band time series and associated statistics for the underlying 550'737 unique sources. We estimate that about half of them are newly identified variables. The variability type completeness varies strongly as function of sky position due to the non-uniform sky coverage and intermediate calibration level of this data. The probabilistic and automated nature of this work implies certain completeness and contamination rates which are quantified so that users can anticipate their effects. This means that even well-known variable sources can be missed or misidentified in the published data. 
The DR2 variability release only represents a small subset of the processed data. Future releases will include more variable sources and data products; however, DR2 shows the (already) very high quality of the data and great promise for variability studies.

/pdf/gaia-data-release-2-summary-of-the-variability-processing-51wnd0wevc.pdf

Gaia Data Release 2: Summary of the variability processing & analysis results

We describe the construction of a highly reliable sample of ~7000 optically faint periodic variable stars with light curves obtained by the asteroid survey LINEAR across 10,000 deg^2 of the northern sky. The majority of these variables have not been cataloged yet. The sample flux limit is several magnitudes fainter than most other wide-angle surveys; the photometric errors range from ~0.03 mag at r = 15 to ~0.20 mag at r = 18. Light curves include on average 250 data points, collected over about a decade. Using Sloan Digital Sky Survey (SDSS) based photometric recalibration of the LINEAR data for about 25 million objects, we selected ~200,000 most probable candidate variables with r < 17 and visually confirmed and classified ~7000 periodic variables using phased light curves. The reliability and uniformity of visual classification across eight human classifiers was calibrated and tested using a catalog of variable stars from the SDSS Stripe 82 region and verified using an unsupervised machine learning approach. The resulting sample of periodic LINEAR variables is dominated by 3900 RR Lyrae stars and 2700 eclipsing binary stars of all subtypes and includes small fractions of relatively rare populations such as asymptotic giant branch stars and SX Phoenicis stars. We discuss the distribution of these mostly uncataloged variables in various diagrams constructed with optical-to-infrared SDSS, Two Micron All Sky Survey, and Wide-field Infrared Survey Explorer photometry, and with LINEAR light-curve features. We find that the combination of light-curve features and colors enables classification schemes much more powerful than when colors or light curves are each used separately. An interesting side result is a robust and precise quantitative description of a strong correlation between the light-curve period and color/spectral type for close and contact eclipsing binary stars (β Lyrae and W UMa): as the color-based spectral type varies from K4 to F5, the median period increases from 5.9 hr to 8.8 hr. These large samples of robustly classified variable stars will enable detailed statistical studies of the Galactic structure and physics of binary and other stars and we make these samples publicly available.

https://iopscience.iop.org/article/10.1088/0004-6256/146/4/101/pdf

Exploring the variable sky with linear. iii. classification of periodic light curves

We describe the construction of a highly reliable sample of approximately 7,000 optically faint periodic variable stars with light curves obtained by the asteroid survey LINEAR across 10,000 sq.deg of northern sky. Majority of these variables have not been cataloged yet. The sample flux limit is several magnitudes fainter than for most other wide-angle surveys; the photometric errors range from ~0.03 mag at $r=15$ to ~0.20 mag at r=18. Light curves include on average 250 data points, collected over about a decade. Using SDSS-based photometric recalibration of the LINEAR data for about 25 million objects, we selected ~200,000 most probable candidate variables and visually confirmed and classified approximately 7,000 periodic variables using phased light curves. The reliability and uniformity of visual classification across eight human classifiers was calibrated and tested using a SDSS Stripe 82 region variable star catalog, and verified using an unsupervised machine learning approach. The resulting sample of periodic LINEAR variables is dominated by 3,900 RR Lyrae stars and 2,700 eclipsing binary stars of all subtypes, and includes small fractions of relatively rare populations such as asymptotic giant branch stars and SX Phoenicis stars. We discuss the distribution of these mostly uncataloged variables in various diagrams constructed with optical-to-infrared SDSS, 2MASS and WISE photometry, and with LINEAR light curve features. An interesting side result is a robust and precise quantitative description of a strong correlation between the light-curve period and color/spectral type for close and contact eclipsing binary stars. These large samples of robustly classified variable stars will enable detailed statistical studies of the Galactic structure and physics of binary and other stars, and we make them publicly available.

Martina Mesarić

Papers

Exploring the variable sky with linear. iii. classification of periodic light curves

Exploring the Variable Sky with LINEAR. III. Classification of Periodic Light Curves