NLTE Stellar Population Synthesis of Globular Clusters Using Synthetic Integrated Light Spectra. II. Expanded Photometry and Sensitivity of Near-IR Spectral Features to Cluster Age and Metallicity
The Astronomical Journal American Astronomical Society 157:1 (2019) 10
pyaneti: a fast and powerful software suite for multiplanet radial velocity and transit fitting
Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) 482:1 (2019) 1017-1030
A practical guide to the analysis of non-response and attrition in longitudinal research using a real data example
International Journal of Behavioral Development SAGE Publications 43:1 (2019) 24-34
K2-295 b and K2-237 b: Two Transiting Hot Jupiters
ACTA ASTRONOMICA 69:2 (2019) 135-158
Simulating radial velocity observations of trappist-1 with SPIRou
Monthly notices of the Royal Astronomical Society 488 5144
Abstract:
We simulate a radial velocity (RV) follow-up of the TRAPPIST-1 system, a faithful representative of M dwarfs hosting transiting Earth-sized exoplanets to be observed with SPIRou in the months to come. We generate an RV curve containing the signature of the seven transiting TRAPPIST-1 planets and a realistic stellar activity curve statistically compatible with the light curve obtained with the K2 mission. We find a ±5 m s-1 stellar activity signal comparable in amplitude with the planet signal. Using various sampling schemes and white noise levels, we create time-series from which we estimate the masses of the seven planets. We find that the precision on the mass estimates is dominated by (i) the white noise level for planets c, f, and e and (ii) the stellar activity signal for planets b, d, and h. In particular, the activity signal completely outshines the RV signatures of planets d and h that remain undetected regardless of the RV curve sampling and level of white noise in the data set. We find that an RV follow-up of TRAPPIST-1 using SPIRou alone would likely result in an insufficient coverage of the rapidly evolving activity signal of the star, especially with bright-time observations only, making statistical methods such as Gaussian Process Regression hardly capable of firmly detecting planet f and accurately recovering the mass of planet g. In contrast, we show that using bi-site observations with good longitudinal complementary would allow for a more accurate filtering of the stellar activity RV signal.