The Milky Way Revealed by Variable Stars. I. Sample Selection of RR Lyrae Stars and Evidence for Merger History

In order to study the Milky Way, RR Lyrae (RRL) variable stars identified by Gaia, ASAS-SN, and ZTF sky survey projects have been analyzed as tracers in this work. Photometric and spectroscopic information of 3417 RRLs including proper motions, radial velocity, and metallcity are obtained from observational data of Gaia, LAMOST, GALAH, APOGEE, and RAVE. Precise distances of RRLs with typical uncertainties less than 3% are derived by using a recent comprehensive period–luminosity–metallicity relation. Our results from kinematical and chemical analysis provide important clues for the assembly history of the Milky Way, especially for the Gaia–Sausage ancient merger. The kinematical and chemical trends found in this work are consistent with those of recent simulations that indicated that the Gaia–Sausage merger had a dual origin in the Galactic thick disk and halo. As recent similar works have found, the halo RRL sample in this work contains a subset of radially biased orbits besides a more isotropic component. This higher orbital anisotropy component amounts to β ≃ 0.8, and it contributes between 42% and 83% of the halo RRLs at 4 < R( kpc) < 20.

Preparing to Discover the Unknown with Rubin LSST: Time Domain

Perhaps the most exciting promise of the Rubin Observatory Legacy Survey of Space and Time (LSST) is its capability to discover phenomena never before seen or predicted: true astrophysical novelties; but the ability of LSST to make these discoveries will depend on the survey strategy. Evaluating candidate strategies for true novelties is a challenge both practically and conceptually. Unlike traditional astrophysical tracers like supernovae or exoplanets, for anomalous objects, the template signal is by definition unknown. We approach this problem by assessing survey completeness in a phase space defined by object color and flux (and their evolution), and considering the volume explored by integrating metrics within this space with the observation depth, survey footprint, and stellar density. With these metrics, we explore recent simulations of the Rubin LSST observing strategy across the entire observed spatial footprint and in specific Local Volume regions: the Galactic Plane and Magellanic Clouds. Under our metrics, observing strategies with greater diversity of exposures and time gaps tend to be more sensitive to genuinely new transients, particularly over time-gap ranges left relatively unexplored by previous surveys. To assist the community, we have made all of the tools developed publicly available. While here we focus on transients, an extension of the scheme to include proper motions and the detection of associations or populations of interest will be communicated in Paper II of this series. This paper was written with the support of the Vera C. Rubin LSST Transients and Variable Stars and Stars, Milky Way, Local Volume Science Collaborations.

The Impact of Observing Strategy on the Reliable Classification of Standard Candle Stars: Detection of Amplitude, Period, and Phase Modulation (Blazhko Effect) of RR Lyrae Stars with LSST

The Vera C. Rubin Observatory will carry out its Legacy Survey of Space and Time (LSST) with a single-exposure depth of r ∼ 24.7 and an anticipated baseline of 10 yr, allowing access to the Milky Way’s old halo not only deeper than, but also with a longer baseline and better cadence than, e.g., PS1 3π. This will make the LSST ideal to study populations of variable stars such as RR Lyrae stars (RRL). Here, we address the question of observing strategy optimization of LSST, as survey footprint definition, single-visit exposure time, as well as the cadence of repeat visits in different filters are yet to be finalized. We present metrics used to assess the impact of different observing strategies on the reliable detectability and classification of standard candle variable stars, including detection of amplitude, period, and phase modulation effects of RRL (the so-called Blazhko effect), by evaluating metrics for simulated potential survey designs. So far, due to the depths and cadences of typical all-sky surveys, it has been nearly impossible to study this effect on a larger sample. All-sky surveys with relatively few observations over a moderately long baseline allow only for fitting phase-folded RRL light curves, thus integrating over the complete survey length and hiding any information regarding possible period or phase modulation during the survey. On the other hand, surveys with cadences fit to detect slightly changing light curves usually have a relatively small footprint. LSST’s survey strategy, however, will allow for studying variable stars in a way that makes population studies possible.

A New Classification Model for the ZTF Catalog of Periodic Variable Stars

Using the second data release from the Zwicky Transient Facility (ZTF), Chen et al. created a ZTF Catalog of Periodic Variable Stars (ZTF CPVS) of 781,602 periodic variables stars (PVSs) with 11 class labels. Here, we provide a new classification model of PVSs in the ZTF CPVS using a convolutional variational autoencoder and hierarchical random forest. We cross-match the sky-coordinate of PVSs in the ZTF CPVS with those presented in the SIMBAD catalog. We identify non-stellar objects that are not previously classified, including extragalactic objects such as Quasi-Stellar Objects, Active Galactic Nuclei, supernovae and planetary nebulae. We then create a new labeled training set with 13 classes in two levels. We obtain a reasonable level of completeness (≳90%) for certain classes of PVSs, although we have poorer completeness in other classes (∼40% in some cases). Our new labels for the ZTF CPVS are available via Zenodo.

Analysis of pulsating variable stars using the visibility graph algorithm

We study the light curves of pulsating variable stars using a complex network approach to build visibility graphs. We consider various types of variables stars (e.g., Cepheids, δ Scuti, RR Lyrae), build two types of graphs (the normal visibility graph (VG) and the horizontal visibility graph (HVG)), and calculate various metrics for the resulting networks. We find that all networks have a power-law degree distribution for the VG and an exponential distribution for the HVG, suggesting that it is a universal feature, regardless of the pulsation features. Metrics such as the average degree, the clustering coefficient and the transitivity coefficient, can distinguish between some star types. We also observe that the results are not strongly affected by the presence of observation gaps in the light curves. These findings suggest that the visibility graph algorithm may be a useful technique to study variability in stars.

Classification of Variable Stars Light Curves Using Long Short Term Memory Network

Owing to the current and upcoming extensive surveys studying the stellar variability, accurate and quicker methods are required for the astronomers to automate the classification of variable stars. The traditional approach of classification requires the calculation of the period of the observed light curve and assigning different variability patterns of phase folded light curves to different classes. However, applying these methods becomes difficult if the light curves are sparse or contain temporal gaps. Also, period finding algorithms start slowing down and become redundant in such scenarios. In this work, we present a new automated method, 1D CNN-LSTM, for classifying variable stars using a hybrid neural network of one-dimensional CNN and LSTM network which employs the raw time-series data from the variable stars. We apply the network to classify the time-series data obtained from the OGLE and the CRTS survey. We report the best average accuracy of 85% and F1 score of 0.71 for classifying five classes from the OGLE survey. We simultaneously apply other existing classification methods to our dataset and compare the results.

The relative calibration of radial velocity for LAMOST medium resolution stellar spectra

The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) started a median-resolution spectroscopic (MRS, R ∼7500) survey since October 2018. The main scientific goals of MRS, including binary stars, pulsators and other variable stars, were launched with a time-domain spectroscopic survey. However, the systematic errors, including the bias induced from wavelength calibration and the systematic difference between different spectrographs, have to be carefully considered during radial velocity measurement. In this work, we provide a technique to correct the systematics in the wavelength calibration based on the relative radial velocity measurements from LAMOST MRS spectra. We show that, for the stars with multi-epoch spectra, the systematic bias which is induced from the exposures on different nights can be corrected well for LAMOST MRS in each spectrograph. In addition, the precision of radial velocity zero-point of multi-epoch time-domain observations reaches below 0.5 km s−1. As a by-product, we also give the constant star candidates**, which can be the secondary radial-velocity standard star candidates of LAMOST MRS time-domain surveys.

Optical and Near-infrared Pulsation Properties of RR Lyrae and Population II Cepheid Variables in the Messier 15 Globular Cluster

Messier 15 (NGC 7078) is an old and metal-poor post core-collapse globular cluster that hosts a rich population of variable stars. We report new optical (gi) and near-infrared (NIR, JK s ) multi-epoch observations for 129 RR Lyrae, 4 Population II Cepheids (3 BL Herculis, 1 W Virginis), and 1 anomalous Cepheid variable candidate in M15 obtained using the MegaCam and the WIRCam instruments on the 3.6 m Canada–France–Hawaii Telescope. Multi-band data are used to improve the periods and classification of variable stars, and determine accurate mean magnitudes and pulsational amplitudes from the light curves fitted with optical and NIR templates. We derive optical and NIR period–luminosity relations for RR Lyrae stars which are best constrained in the K s band, m K s = − 2.333 ( 0.054 ) log P + 13.948 ( 0.015 ) with a scatter of only 0.037 mag. Theoretical and empirical calibrations of RR Lyrae period–luminosity–metallicity relations are used to derive a true distance modulus to M15: 15.196 ± 0.026 (statistical) ± 0.039 (systematic) mag. Our precise distance moduli based on RR Lyrae stars and Population II Cepheid variables are mutually consistent and agree with recent distance measurements in the literature based on Gaia parallaxes and other independent methods.