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  1. Abstract

    Gyrochronology, the field of age dating stars using mainly their rotation periods and masses, is ideal for inferring the ages of individual main-sequence stars. However, due to the lack of physical understanding of the complex magnetic fields in stars, gyrochronology relies heavily on empirical calibrations that require consistent and reliable stellar age measurements across a wide range of periods and masses. In this paper, we obtain a sample of consistent ages using the gyro-kinematic age-dating method, a technique to calculate the kinematics ages of stars. Using a Gaussian process model conditioned on ages from this sample (∼1–14 Gyr) and known clusters (0.67–3.8 Gyr), we calibrate the first empirical gyrochronology relation that is capable of inferring ages for single, main-sequence stars between 0.67 and 14 Gyr. Cross-validating and testing results suggest our model can infer cluster and asteroseismic ages with an average uncertainty of just over 1 Gyr, and the inferred ages for wide binaries agree within 0.83 Gyr. With this model, we obtain gyrochronology ages for ∼100,000 stars within 1.5 kpc of the Sun with period measurements from Kepler and Zwicky Transient Facility and 384 unique planet host stars. A simple code is provided to infer gyrochronology ages of stars with temperature and period measurements.

     
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  2. ABSTRACT

    The distribution of small-scale magnetic fields in stellar photospheres is an important ingredient in our understanding of the magnetism of low-mass stars. Their spatial distribution connects the field generated in the stellar interior with the outer corona and the large scale field, and thereby affects the space weather of planets. Unfortunately, we lack techniques that can locate them on most low-mass stars. One strategy is to localize field concentrations using the flares that occur in their vicinity. We explore a new method that adapts the spot simulation software fleck to study the modulation of flaring times as a function of active latitude. We use empirical relations to construct flare light curves similar to those available from Kepler and the Transiting Exoplanet Survey Satellite (TESS), search them for flares, and use the waiting times between flares to determine the location of active latitudes. We find that the mean and standard deviations of the waiting time distribution provide a unique diagnostic of flaring latitudes as a function of the number of active regions. Latitudes are best recovered when stars have three or less active regions that flare repeatedly, and active latitude widths below 20 deg; when either increases, the information about the active latitude location is gradually lost. We demonstrate our technique on a sample of flaring G dwarfs observed with the Kepler satellite, and furthermore suggest that combining ensemble methods for spots and flares could overcome the limitations of each individual technique for the localization of surface magnetic fields.

     
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  3. Abstract The intermediate period gap, discovered by Kepler, is an observed dearth of stellar rotation periods in the temperature–period diagram at ∼20 days for G dwarfs and up to ∼30 days for early-M dwarfs. However, because Kepler mainly targeted solar-like stars, there is a lack of measured periods for M dwarfs, especially those at the fully convective limit. Therefore it is unclear if the intermediate period gap exists for mid- to late-M dwarfs. Here, we present a period catalog containing 40,553 rotation periods (9535 periods >10 days), measured using the Zwicky Transient Facility (ZTF). To measure these periods, we developed a simple pipeline that improves directly on the ZTF archival light curves and reduces the photometric scatter by 26%, on average. This new catalog spans a range of stellar temperatures that connect samples from Kepler with MEarth, a ground-based time-domain survey of bright M dwarfs, and reveals that the intermediate period gap closes at the theoretically predicted location of the fully convective boundary ( G BP − G RP ∼ 2.45 mag). This result supports the hypothesis that the gap is caused by core–envelope interactions. Using gyro-kinematic ages, we also find a potential rapid spin-down of stars across this period gap. 
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  4. Abstract

    Stellar variability is driven by a multitude of internal physical processes that depend on fundamental stellar properties. These properties are our bridge to reconciling stellar observations with stellar physics and to understand the distribution of stellar populations within the context of galaxy formation. Numerous ongoing and upcoming missions are charting brightness fluctuations of stars over time, which encode information about physical processes such as the rotation period, evolutionary state (such as effective temperature and surface gravity), and mass (via asteroseismic parameters). Here, we explore how well we can predict these stellar properties, across different evolutionary states, using only photometric time-series data. To do this, we implement a convolutional neural network, and with data-driven modeling we predict stellar properties from light curves of various baselines and cadences. Based on a single quarter of Kepler data, we recover the stellar properties, including the surface gravity for red giant stars (with an uncertainty of ≲0.06 dex) and rotation period for main-sequence stars (with an uncertainty of ≲5.2 days, and unbiased from ≈5 to 40 days). Shortening the Kepler data to a 27 days Transiting Exoplanet Survey Satellite–like baseline, we recover the stellar properties with a small decrease in precision, ∼0.07 for loggand ∼5.5 days forProt, unbiased from ≈5 to 35 days. Our flexible data-driven approach leverages the full information content of the data, requires minimal or no feature engineering, and can be generalized to other surveys and data sets. This has the potential to provide stellar property estimates for many millions of stars in current and future surveys.

     
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  5. Precise Gaia measurements of positions, parallaxes, and proper motions provide an opportunity to calculate 3D positions and 2D velocities (i.e., 5D phase-space) of Milky Way stars. Where available, spectroscopic radial velocity (RV) measurements provide full 6D phase-space information, however there are now and will remain many stars without RV measurements. Without an RV it is not possible to directly calculate 3D stellar velocities; however, one can infer 3D stellar velocities by marginalizing over the missing RV dimension. In this paper, we infer the 3D velocities of stars in the Kepler field in Cartesian Galactocentric coordinates (vx, vy, vz). We directly calculate velocities for around a quarter of all Kepler targets, using RV measurements available from the Gaia, LAMOST, and APOGEE spectroscopic surveys. Using the velocity distributions of these stars as our prior, we infer velocities for the remaining three quarters of the sample by marginalizing over the RV dimension. The median uncertainties on our inferred vx, vy, and vz velocities are around 4, 18, and 4 km/s, respectively. We provide 3D velocities for a total of 148,590 stars in the Kepler field. These 3D velocities could enable kinematic age-dating, Milky Way stellar population studies, and other scientific studies using the benchmark sample of well-studied Kepler stars. Although the methodology used here is broadly applicable to targets across the sky, our prior is specifically constructed from and for the Kepler field. Care should be taken to use a suitable prior when extending this method to other parts of the Galaxy. 
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  8. The vast majority of Milky Way stellar halo stars were likely accreted from a small number (<~3) of relatively large dwarf galaxy accretion events. However, the timing of these events is poorly constrained and predominantly relies on indirect dynamical mixing arguments or imprecise age measurements of stars associated with debris structures. Here, we aim to infer robust stellar ages for stars associated with galactic substructures to more directly constrain the merger history of the Galaxy. By combining kinematic, asteroseismic, and spectroscopic data where available, we infer stellar ages for a sample of 10 red giant stars that were kinematically selected to be within the stellar halo, a subset of which are associated with the Gaia–Enceladus–Sausage halo substructure, and compare their ages to 3 red giant stars in the Galactic disk. Despite systematic differences in both absolute and relative ages determined here, age rankings of stars in this sample are robust. Passing the same observable inputs to multiple stellar age determination packages, we measure a weighted average age for the Gaia–Enceladus–Sausage stars in our sample of 8+/-3 (stat.)+/-1 (sys.) Gyr. We also determine hierarchical ages using isochrones for the populations of Gaia–Enceladus–Sausage, in situ halo and disk stars, finding a Gaia–Enceladus–Sausage population age of 8.0+2.3-3.2 Gyr. Although we cannot distinguish hierarchical population ages of halo or disk structures with our limited data and sample of stars, this framework should allow a distinct characterization of Galactic substructures using larger stellar samples and additional data available in the near future 
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