  We present ARC2 (Astrophysically Robust Correction 2), an open-source
Python-based systematics-correction pipeline to correct for the Kepler prime
mission long cadence light curves. The ARC2 pipeline identifies and corrects
any isolated discontinuities in the light curves, then removes trends common to
many light curves. These trends are modelled using the publicly available
co-trending basis vectors, within an (approximate) Bayesian framework with
`shrinkage' priors to minimise the risk of over-fitting and the injection of
any additional noise into the corrected light curves, while keeping any
astrophysical signals intact. We show that the ARC2 pipeline's performance
matches that of the standard Kepler PDC-MAP data products using standard noise
metrics, and demonstrate its ability to preserve astrophysical signals using
injection tests with simulated stellar rotation and planetary transit signals.
Although it is not identical, the ARC2 pipeline can thus be used as an open
source alternative to PDC-MAP, whenever the ability to model the impact of the
systematics removal process on other kinds of signal is important.
