Estimation of singly transiting K2 planet periods with Gaia parallaxes

Abstract

When a planet is only observed to transit once, direct measurement of its period is impossible. It is possible, however, to constrain the periods of single transiters, and this is desirable as they are likely to represent the cold and far extremes of the planet population observed by any particular survey. Improving the accuracy with which the period of single transiters can be constrained is therefore critical to enhance the longperiod planet yield of surveys. Here, we combine Gaia parallaxes with stellar models and broad-band photometry to estimate the stellar densities of K2 planet host stars, then use that stellar density information to model individual planet transits and infer the posterior period distribution. We show that the densities we infer are reliable by comparing with densities derived through asteroseismology, and apply our method to 27 validation planets of known (directly measured) period, treating each transit as if it were the only one, as well as to 12 true single transiters. When we treat eccentricity as a free parameter, we achieve a fractional period uncertainty over the true single transits of 94 +87 −58 %, and when we fix e = 0, we achieve fractional period uncertainty 15 +30 −6 %, a roughly threefold improvement over typical period uncertainties of previous studies.

The Magellan/PFS Exoplanet Search: A 55-day period dense Neptune transiting the bright ($V=8.6$) star HD 95338

“…We estimate (a/R )= 58.06 +1.39 −2.48 from the transit seen in the TESS lightcurve. Then, using equations ( 1) and (2) from from Sandford et al (2019) we get an estimate for an orbital period of 47±9 days for the single transit observed by TESS being consistent within the uncertainties to the period of the signal found in the radial velocity data.…”

“…Recent work by Sandford et al (2019) have shown the use of single-transit lightcurves to estimate orbital periods based on precise parallaxes from Gaia. While their work focused on K2 data, we can apply the same methodology to our TESS lightcurve, since we also know the transit depth, and we can calculate the scaled semi-major axis and stellar density from the combination of the ARIADNE results and the high resolution spectra.…”

“…While their work focused on K2 data, we can apply the same methodology to our TESS lightcurve, since we also know the transit depth, and we can calculate the scaled semi-major axis and stellar density from the combination of the ARIADNE results and the high resolution spectra. We recall equations 1 and 2 from Sandford et al (2019):…”

ACCESS: Tentative Detection of H2O in the Ground-based Optical Transmission Spectrum of the Low-density Hot Saturn HATS-5b

“…We use a prior on the stellar density obtained in our spectroscopic analysis described above in our fits. However, following Sandford et al (2019), we multiply the stellar density uncertainty obtained there by two in our prior, in order to account for empirically determined underestimations of the uncertainty in that work. We tried both circular and eccentric fits but found via the log-evidences that both models are indistinguishable by the data-we find the eccentricity of the system to be e < 0.05 with a probability of 99% given the data.…”

A dense mini-Neptune orbiting the bright young star HD 18599

“…Additionally, EMPEROR has incorporated a linear stellar activity correlation model following the description in Anglada-Escudé et al (2016). EMPEROR also allows for the modeling of the stellar density, which has been shown to improve parameter estimation as it deals with the degeneracy between the radius ratio and the impact parameter (Sandford et al 2019;Vines et al 2019). The algorithm assumes a Gaussian generative model and thus both the RV jitter and photometric white noise are added in quadrature to their respective observational uncertainties.…”