摘要：We present an update to the EVEREST K2 pipeline that addresses various limitations in the previous version andimproves the photometric precision of the light curves. We develop a fast regularization scheme for pixel-leveldecorrelation (PLD) and adapt the algorithm to include the PLD vectors of other stars to enhance the predictivepower of the model and minimize overfitting, particularly for faint stars. We also modify PLD to work for saturatedstars and improve its performance on variable stars, although some high-frequency variables may still suffer fromoverfitting. On average, EVEREST 2.0 light curves have 10–20% higher photometric precision than those inversion 1, yielding the highest-precision light curves at all Kp magnitudes of any publicly available K2 catalog. Formost K2 campaigns, we recover the original Kepler precision to at least Kp =14, and to at least Kp =15 forcampaigns 1, 5, 6, and 13. We also detrend most short-cadence targets observed by K2, obtaining even higherphotometric precision for these stars. Like all aggressive, flexible models, EVEREST is prone to overfitting, andmay cause a decrease in transit depths by ∼10%; we urge users to mask signals of interest using our open-sourcesoftware, which we show removes this bias. Light curves for campaigns 0–8 and 10–13 are available online in theEVEREST catalog, which will be updated with future campaigns. EVEREST 2.0 is open source and is coded in aframework that can be adapted to other photometric surveys, including Kepler and the upcoming TESS mission.
关键词：catalogs;planets and satellites: detection;techniques: photometric
