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KOBEsim: improving RV detection through efficient scheduling

Name: KOBEsim: improving RV detection through efficient scheduling
Keywords: Exoplanets, KOBE, CARMENES, Radial Velocity, Bayesian Statistics

descriptionPublicationkeyboard_double_arrow_right Conference object , Other literature type 01 Sep 2022Publisher:Zenodo

Authors: Balsalobre-Ruza, Olga; Lillo-Box, Jorge; Berihuete, Ángel; the KOBE team;

doi: 10.5281/zenodo.7041397 , 10.5281/zenodo.7041398

KOBEsim: improving RV detection through efficient scheduling

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Abstract

The KOBEsim algorithm is a Bayesian-based strategy for the detection of planets in radial velocity (RV) surveys written in Python. It is developed within the KOBE (K-dwarfs Orbited By habitable Exoplanets) experiment, aiming at maximizing the detection of rocky exoplanets potentially habitable orbiting K-dwarfs. After gathering the first data, KOBEsim targets the predominant orbital period and finds the optimum next observing date to maximize the efficiency of confirming or discarding that signal. This new approach has demonstrated to improve nearly 50 % the detection efficiency in comparison with a conventional strategy of monotonic cadence.

Related Organizations

Spanish National Research Council
Spain
Centro de Astrobiología
Spain
National Institute for Aerospace Technology
Spain
University of Cádiz
Spain

Keywords

Exoplanets, KOBE, CARMENES, Radial Velocity, Bayesian Statistics

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