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Revisiting K2-233 spectroscopic time-series with multidimensional Gaussian processes

Abstract:
Detecting planetary signatures in radial velocity time-series of young stars is challenging due to their inherently strong stellar activity. However, it is possible to learn information about the properties of the stellar signal by using activity indicators measured from the same stellar spectra used to extract radial velocities. In this manuscript, we present a reanalysis of spectroscopic High Accuracy Radial Velocity Planet Searcher data of the young star K2-233, which hosts three transiting planets. We perform a multidimensional Gaussian process regression on the radial velocity and the activity indicators to characterize the planetary Doppler signals. We demonstrate, for the first time on a real data set, that the use of a multidimensional Gaussian process can boost the precision with which we measure the planetary signals compared to a one-dimensional Gaussian process applied to the radial velocities alone. We measure the semi-amplitudes of K2-233 b, c, and d as 1.31+0.81−0.74, 1.81+0.71−0.67, and 2.72+0.66−0.70 m s−1, which translate into planetary masses of 2.4+1.5−1.3, 4.6+1.8−1.7, and 10.3+2.4−2.6 M⊕, respectively. These new mass measurements make K2-233 d a valuable target for transmission spectroscopy observations with JWST. K2-233 is the only young system with two detected inner planets below the radius valley and a third outer planet above it. This makes it an excellent target to perform comparative studies, to inform our theories of planet evolution, formation, migration, and atmospheric evolution.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/mnras/stad1139

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Role:
Author


Publisher:
Oxford University Press
Journal:
Monthly Notices of the Royal Astronomical Society More from this journal
Volume:
522
Issue:
3
Pages:
3458-3471
Publication date:
2023-04-18
Acceptance date:
2023-04-07
DOI:
EISSN:
1365-2966
ISSN:
0035-8711


Language:
English
Keywords:
Pubs id:
1350249
Local pid:
pubs:1350249
Deposit date:
2023-06-27

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