Every Datapoint Counts: Stellar Flares as a Case Study of Atmosphere-Aided Transients in the Rubin LSST Era

Stellar flares are short-duration, stochastic brightening events that occur on the surfaces of stars and act as tracers of stellar magnetic activity. Due to their short timescale, stellar flares are a challenging target for the most modern astrophysical sky surveys. The upcoming Vera C. Rubin Legacy Survey of Space and Time (LSST), which will detect over a million flares over its 10 year mission, is unlikely to detect flares with more than one data point in its main survey. We developed a methodology to enable LSST studies of stellar flares, with a focus on flare temperature and temperature evolution, which remain poorly constrained compared to flare morphology. Leveraging the exquisite image quality and sensitivity expected from the Rubin system, Differential Chromatic Refraction can be used to constrain flare temperature from a single-epoch detection, which will enable statistical studies of flare temperature evolution using the unprecedentedly high volume of data produced by Rubin over the 10-year LSST. Obtaining these statistics will constrain models of the physical processes behind flare emission as well as the relationship between flare parameters (e.g. temperature, duration, energy) and stellar parameters (e.g. spectral type, rotation, magnetic field). We model the refraction effect as a function of the atmospheric column density, photometric filter, and temperature of the flare, and show that flare temperatures at or above ∼10,000K can be constrained by a single g-band observation at airmass X ≳ 1.2, given the specified requirement on single-visit absolute astrometric accuracy of LSST, and that a surprisingly large number of LSST observations is in fact likely be conducted at X ≳ 1.2, in spite of image quality requirements pushing the survey to preferentially low X. Testing our method on LSST precursor surveys and finding that they do not enable measurement of flare DCR, we make recommendations on survey design, data products, and alert broker filters that will enable these studies in LSST and other future surveys.