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Abstract Galactic science encompasses a wide range of subjects in the study of the Milky Way and Magellanic Clouds, from young stellar objects to X-ray binaries. Mapping these populations, and exploring transient phenomena within them, are among the primary science goals of the Vera C. Rubin Observatory’s Legacy Survey of Space and Time. While early versions of the survey strategy dedicated relatively few visits to the Galactic Plane region, more recent strategies under consideration envision a higher cadence within selected regions of high scientific interest. The range of galactic science presents a challenge in evaluating which strategies deliver the highest scientific returns. Here we present metrics designed to evaluate Rubin survey strategy simulations, based on the cadence of observations they deliver within regions of interest to different topics in galactic science, using variability categories defined by timescale. We also compare the fractions of exposures obtained in each filter with those recommended for the different science goals. We find that the baseline _ v2.x simulations deliver observations of the high-priority regions at sufficiently high cadence to reliably detect variability on timescales >10 days or more. Follow-up observations may be necessary to properly characterize variability, especially transients, on shorter timescales. Combining the regions of interest for all the science cases considered, we identify those areas of the Galactic Plane and Magellanic Clouds of highest priority. We recommend that these refined survey footprints be used in future simulations to explore rolling cadence scenarios, and to optimize the sequence of observations in different bandpasses. 

Abstract SN 2017jgh is a type IIb supernova discovered by Pan-STARRS during the C16/C17 campaigns of the Kepler/K2 mission. Here we present the Kepler/K2 and ground based observations of SN 2017jgh, which captured the shock cooling of the progenitor shock breakout with an unprecedented cadence. This event presents a unique opportunity to investigate the progenitors of stripped envelope supernovae. By fitting analytical models to the SN 2017jgh lightcurve, we find that the progenitor of SN 2017jgh was likely a yellow supergiant with an envelope radius of ∼50 − 290 R⊙, and an envelope mass of ∼0 − 1.7 M⊙. SN 2017jgh likely had a shock velocity of ∼7500 − 10300 km s−1. Additionally, we use the lightcurve of SN 2017jgh to investigate how early observations of the rise contribute to constraints on progenitor models. Fitting just the ground based observations, we find an envelope radius of ∼50 − 330 R⊙, an envelope mass of ∼0.3 − 1.7 M⊙ and a shock velocity of ∼9, 000 − 15, 000 km s−1. Without the rise, the explosion time can not be well constrained which leads to a systematic offset in the velocity parameter and larger uncertainties in the mass and radius. Therefore, it is likely that progenitor property estimates through these models may have larger systematic uncertainties than previously calculated. 

We present the first asteroseismic results for δ Scuti and γ Doradus stars observed in Sectors 1 and 2 of the TESS mission. We utilize the 2-min cadence TESS data for a sample of 117 stars to classify their behaviour regarding variability and place them in the Hertzsprung–Russell diagram using Gaia DR2 data. Included within our sample are the eponymous members of two pulsator classes, γ Doradus and SX Phoenicis. Our sample of pulsating intermediate-mass stars observed by TESS also allows us to confront theoretical models of pulsation driving in the classical instability strip for the first time and show that mixing processes in the outer envelope play an important role. We derive an empirical estimate of 74 per cent for the relative amplitude suppression factor as a result of the redder TESS passband compared to the Kepler mission using a pulsating eclipsing binary system. Furthermore, our sample contains many high-frequency pulsators, allowing us to probe the frequency variability of hot young δ Scuti stars, which were lacking in the Kepler mission data set, and identify promising targets for future asteroseismic modelling. The TESS data also allow us to refine the stellar parameters of SX Phoenicis, which is believed to be a blue straggler.