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Register a new userComparing radial velocities of atmospheric lines with radiosonde measurements
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P. Figueira
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The precision of radial velocity (RV) measurements depends on the precision attained on the wavelength calibration. One of the available options is using atmospheric lines as a natural, freely available wavelength reference. Figueira et al. (2010) measured the RV of O2 lines using HARPS and showed that the scatter was only of ~10 m/s over a timescale of 6 yr. Using a simple but physically motivated empirical model, they demonstrated a precision of 2 m/s, roughly twice the average photon noise contribution. In this paper we take advantage of a unique opportunity to confirm the sensitivity of the telluric absorption lines RV to different atmospheric and observing conditions: by means of contemporaneous in-situ wind measurements by radiosondes. The RV model fitting yielded similar results to that of Figueira et al. (2010), with lower wind magnitude values and varied wind direction. The probes confirmed the average low wind magnitude and suggested that the average wind direction is a function of time as well. The two approaches deliver the same results in what concerns wind magnitude and agree on wind direction when fitting is done in segments of a couple of hours. Statistical tests show that the model provides a good description of the data on all timescales, being always preferable to not fitting any atmospheric variation. The smaller the timescale on which the fitting can be performed (down to a couple of hours), the better the description of the real physical parameters. We conclude then that the two methods deliver compatible results, down to better than 5 m/s and less than twice the estimated photon noise contribution on O2 lines RV measurement. However, we cannot rule out that parameters alpha and gamma (dependence on airmass and zero-point, respectively) have a dependence on time or exhibit some cross-talk with other parameters (abridged).
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The radial-velocity (RV) method is one of the most successful in the detection of exoplanets, but is hindered by the intrinsic RV variations of the star, which can easily mimic or hide true planetary signals. kima is a package for the detection and characterization of exoplanets using RV data. It fits a sum of Keplerian curves to a timeseries of RV measurements and calculates the evidence for models with a fixed number Np of Keplerian signals, or after marginalising over Np. Moreover, kima can use a GP with a quasi-periodic kernel as a noise model, to deal with activity-induced signals. The hyperparameters of the GP are inferred together with the orbital parameters. The code is written in C++, but includes a helper Python package, pykima, which facilitates the analysis of the results.
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