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K2SC (K2 Systematics Correction) models instrumental systematics and astrophysical variability in light curves from the K2 mission. It enables the user to remove both position-dependent systematics and time-dependent variability (e.g., for transit searches) or to remove systematics while preserving variability (for variability studies). K2SC automatically computes estimates of the period, amplitude and evolution timescale of the variability for periodic variables and can be run on ASCII and FITS light curve files. Written in Python, this pipeline requires NumPy, SciPy, MPI4Py, Astropy (ascl:1304.002), and George (ascl:1511.015).
K2PS is an Oxford K2 planet search pipeline. Written in Python, it searches for transit-like signals from the k2sc-detrended light curves.
GProtation measures stellar rotation periods with Gaussian processes.
This code is no longer being maintained. Please consider using celerite (ascl:1709.008) or exoplanet (ascl:1910.005) instead.
nuance uses linear models and Gaussian processes to simultaneously search for planetary transits while modeling correlated noises (e.g., stellar variability). The code computes the likelihood of a transit being present in some correlated noise without disentangling the two; it searches the transit signal while simultaneously modeling correlated noise, assuming that the light curve can be modeled as a Gaussian process. nuance detects single or periodic transits and can find transits in light curves from multiple instruments, whether space-based or ground-based; it can also run in parallel on CPUs or GPUs.