MAGPy: a tool for Gaussian process regression and its application to planet detection

I present MAGPy, a new soon-to-be-public Gaussian process (GP) regression pipeline with affine-invariant Markov Chain Monte Carlo (MCMC) parameter space searching algorithm. The pipeline was developed for planetary detection, but it is flexible enough to be used for any GP regression analysis. We also present the detection of a sub-Neptune and a sub-Saturn planet orbiting the high-proper motion K-dwarf TOI-2134.

{"references": ["Lagrange A. M., Desort M., Meunier N., 2010, A&A, 512, A38", "Meunier N., Desort M., Lagrange A. M., 2010, A&A, 512, A39", "Haywood R. D., et al., 2014, MNRAS, 443, 2517", "Cosentino R., et al., 2012, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series Vol. 8446, p. 84461V"]}

The complete analysis is currently in process and its paper in prep. The poster presents the preliminary results obtained before July 2022.

Related Organizations

University of Exeter
United Kingdom

Keywords

HARPS-N, radial velocity, data reduction, Gaussian process, planet detection

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