http://arxiv.org/abs/1812.08549
Here we present juliet, a versatile tool for the analysis of transits, radial-velocities, or both. juliet is built over many available tools for the modelling of transits, radial-velocities and stochastic processes (here modelled as Gaussian Processes; GPs) in order to deliver a tool/wrapper which can be used for the analysis of transit photometry and radial-velocity measurements from multiple instruments at the same time, using nested sampling algorithms which allows it to not only perform a thorough sampling of the parameter space, but also to perform model comparison via bayesian evidences. In addition, juliet allows to fit transiting and non-transiting multi-planetary systems, and to fit GPs which might share hyperparameters between the photometry and radial-velocities simultaneously (e.g., stellar rotation periods), which might be useful for disentangling stellar activity in radial-velocity measurements. Nested Sampling, Importance Nested Sampling and Dynamic Nested Sampling is performed with publicly available codes which in turn give juliet multi-threading options, allowing it to scale the computing time of complicated multi-dimensional problems. We make juliet publicly available via GitHub.
N. Espinoza, D. Kossakowski and R. Brahm
Fri, 21 Dec 18
72/72
Comments: Submitted to MNRAS; comments are very welcome. Code (plus documentation) available at this https URL
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