The number of known periodic variables has grown rapidly in recent years. Thanks to its large field of view and faint limiting magnitude, the Zwicky Transient Facility (ZTF) offers a unique opportunity to detect variable stars in the northern sky. Here, we exploit ZTF Data Release 2 (DR2) to search for and classify variables down to r ∼ 20.6 mag. We classify 781,602 periodic variables into 11 main types using an improved classification method. Comparison with previously published catalogs shows that 621,702 objects (79.5%) are newly discovered or newly classified, including ∼700 Cepheids, ∼5000 RR Lyrae stars, ∼15,000 δ Scuti variables, ∼350,000 eclipsing binaries, ∼100,000 long-period variables, and about 150,000 rotational variables. The typical misclassification rate and period accuracy are on the order of 2% and 99%, respectively. 74% of our variables are located at Galactic latitudes, . This large sample of Cepheids, RR Lyrae, δ Scuti stars, and contact (EW-type) eclipsing binaries is helpful to investigate the Galaxy’s disk structure and evolution with an improved completeness, areal coverage, and age resolution. Specifically, the northern warp and the disk’s edge at distances of 15–20 kpc are significantly better covered than previously. Among rotational variables, RS Canum Venaticorum and BY Draconis-type variables can be separated easily. Our knowledge of stellar chromospheric activity would benefit greatly from a statistical analysis of these types of variables.

Photometric measurements are prone to systematic errors presenting a challenge to low-amplitude variability detection. In search for a general-purpose variability detection technique able to recover a broad range of variability types including currently unknown ones, we test 18 statistical characteristics quantifying scatter and/or correlation between brightness measurements. We compare their performance in identifying variable objects in seven time series data sets obtained with telescopes ranging in size from a telephoto lens to 1 m-class and probing variability on time-scales from minutes to decades. The test data sets together include light curves of 127 539 objects, among them 1251 variable stars of various types and represent a range of observing conditions often found in ground-based variability surveys. The real data are complemented by simulations. We propose a combination of two indices that together recover a broad range of variability types from photometric data characterized by a wide variety of sampling patterns, photometric accuracies and percentages of outlier measurements. The first index is the interquartile range (IQR) of magnitude measurements, sensitive to variability irrespective of a time-scale and resistant to outliers. It can be complemented by the ratio of the light-curve variance to the mean square successive difference, 1/η, which is efficient in detecting variability on time-scales longer than the typical time interval between observations. Variable objects have larger 1/η and/or IQR values than non-variable objects of similar brightness. Another approach to variability detection is to combine many variability indices using principal component analysis. We present 124 previously unknown variable stars found in the test data.

We have compiled the first all-sky mid-infrared variable-star catalog based on Wide-field Infrared Survey Explorer five-year survey data. Requiring more than 100 detections for a given object, 50,282 carefully and robustly selected periodic variables are discovered, of which 34,769 (69%) are new. Most are located in the Galactic plane and near the equatorial poles. A method to classify variables based on their mid-infrared light curves is established using known variable types in the General Catalog of Variable Stars. Careful classification of the new variables results in a tally of 21,427 new EW-type eclipsing binaries, 5654 EA-type eclipsing binaries, 1312 Cepheids, and 1231 RR Lyrae. By comparison with known variables available in the literature, we estimate that the misclassification rate is 5% and 10% for short- and long-period variables, respectively. A detailed comparison of the types, periods, and amplitudes with variables in the Catalina catalog shows that the independently obtained classifications parameters are in excellent agreement. This enlarged sample of variable stars will not only be helpful to study Galactic structure and extinction properties, but can also be used to constrain stellar evolution theory and provide potential candidates for the James Webb Space Telescope.

The mass-loss rate (MLR) is one of the most important parameters in astrophysics, because it impacts many areas of astronomy, such as ionizing radiation, wind feedback, star-formation rates, initial mass functions, stellar remnants, supernovae, and so on. However, the most important modes of mass loss are also the most uncertain, as the dominant physical mechanisms that lead to this phenomenon are stull largely unknown. Here we assemble the most complete and clean red supergiant (RSG) sample (2121 targets) so far in the Small Magellanic Cloud (SMC) with 53 different bands of data to study the MLR of RSGs. In order to match the observed spectral energy distributions (SEDs), we created a theoretical grid of 17 820 oxygen-rich models (“normal” and “dusty” grids are half-and-half) using the radiatively driven wind model of the DUSTY code, covering a wide range of dust parameters. We select the best model for each target by calculating the minimal modified chi-square and visual inspection. The resulting MLRs from DUSTY are converted to real MLRs based on the scaling relation, for which a total MLR of 6.16 × 10⁻³ M_⊙ yr⁻¹ is measured (corresponding to a dust-production rate of ∼6 × 10⁻⁶ M_⊙ yr⁻¹), with a typical MLR of ∼10⁻⁶ M_⊙ yr⁻¹ for the general population of the RSGs. The complexity of mass-loss estimations based on the SED is fully discussed for the first time, and our results indicate large uncertainties based on the photometric data (potentially up to one order of magnitude or more). The Hertzsprung-Russell (HR) and luminosity versus median-absolute-deviation (MAD) diagrams of the sample indicate the positive relation between luminosity and MLR. Meanwhile, the luminosity versus MLR diagrams show a “knee-like” shape with enhanced mass loss occurring above log₁₀(L/L_⊙)≈4.6, which may be due to the degeneracy of luminosity, pulsation, low surface gravity, convection, and other factors. We derive our MLR relation using a third-order polynomial to fit the sample and compare our results with previous empirical MLR prescriptions. Given that our MLR prescription is based on a much larger sample than previous determinations, it provides a more accurate relation at the cool and luminous region of the HR diagram at low metallicity compared to previous studies. Finally, nine targets in our sample were detected in the UV, which could be an indicator of OB-type companions of binary RSGs.