RT journal article
T1 KOBEsim: A Bayesian observing strategy algorithm for planet detection in radial velocity blind-search surveys
A1 Berihuete Macías, Ángel
A1 Balsalobre Ruza, Olga
A1 Lillo-Box, Jorge
A1 Silva, A.M.
A1 Santos, N.C.
A1 Castro-González, Amadeo
A1 Faria, J.P.
A1 Huelamo, Nuria
A1 Barrado Navascués, David
A1 Demangeon, O. D. S.
A1 Marfil, Emilio
A1 Aceituno, J.
A1 Adibekyan, V.
A1 Azzaro, M.
A1 Barros, S. C. C.
A1 Bergond, G.
A1 Galadí Enríquez, D.
A1 Pedraz, S.
A1 Santerne, Alexandre
A2 Estadística e Investigación Operativa
K1 Methods: statistical
K1 Planets and satellites: detection
K1 Stars: solar-type
K1 Techniques: radial velocities
AB Context. Ground-based observing time is precious in the era of exoplanet follow-up and characterization, especially in high-precision radial velocity instruments. Blind-search radial velocity surveys thus require a dedicated observational strategy in order to optimize the observing time, which is particularly crucial for the detection of small rocky worlds at large orbital periods. Aims. We developed an algorithm with the purpose of improving the efficiency of radial velocity observations in the context of exoplanet searches, and we applied it to the K-dwarfs Orbited By habitable Exoplanets experiment. Our aim is to accelerate exoplanet confirmations or, alternatively, reject false signals as early as possible in order to save telescope time and increase the efficiency of both blind-search surveys and follow-up of transiting candidates. Methods. Once a minimum initial number of radial velocity datapoints is reached in such a way that a periodicity starts to emerge according to generalized Lomb-Scargle periodograms, that period is targeted with the proposed algorithm, named KOBEsim. The algorithm selects the next observing date that maximizes the Bayesian evidence for this periodicity in comparison with a model with no Keplerian orbits. Results. By means of simulated data, we proved that the algorithm accelerates the exoplanet detection, needing 29-33% fewer observations and a 41-47% smaller time span of the full dataset for low-mass planets (mp < 10 M⊕) in comparison with a conventional monotonic cadence strategy. For 20 M⊕ planets we found a 16% enhancement in the number of datapoints. We also tested KOBEsim with real data for a particular KOBE target and for the confirmed planet HD 102365 b. These two tests demonstrate that the strategy is capable of speeding up the detection by up to a factor of 2 (i.e., reducing both the time span and number of observations by half).
PB EDP Sciences
SN 0004-6361
YR 2022
FD 2022-12-23
LK http://hdl.handle.net/10498/29644
UL http://hdl.handle.net/10498/29644
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 11-nov-2026