Multiwavelength Variability Surveys: Reaping the Stellar Harvest

Over the past decade, a number of dedicated stellar variability surveys have launched from both the ground and space. Many of these programs focus on the detection of specific events, such as exoplanet transits, microlensing amplification, or extragalactic transients. Yet the observed variability behavior encompasses a much larger range of stellar phenomena. To take full advantage of variability survey data, we must detect and classify distinct morphological features in light curves. This task has been particularly challenging for the young (1–10 million year old) stars, which are well known to vary at the 1–100% level on timescales of hours to years. Here we highlight recent progress in the identification, classification, and physical understanding of young star variability. We introduce a selection of time series of pre-main sequence stars from state-of-the-art datasets, including the Young Stellar Object Variability (YSOVAR) campaign with the Spitzer Space Telescope. We describe the data storage approaches and time series analysis techniques employed to extract physically meaningful information from the light curves. The lessons learned from YSOVAR and other campaigns should be broadly applicable to massive future surveys such as TESS and LSST