The Exoplanet Census: A General Method, Applied to Kepler
Andrew N. Youdin (Harvard-Smithsonian Center for Astrophysics)

TL;DR
This paper introduces a flexible maximum likelihood method to model the distribution of exoplanets from survey data, applied to Kepler, revealing trends in planet size and period that support theories of planetary formation and evolution.
Contribution
It presents a novel, general approach to fit the planetary distribution function to survey data, accommodating multiple planets per star and various properties, with application to Kepler data.
Findings
Estimated 0.7 to 1.4 planets per star in the sample.
Size distribution steepens for larger planets at longer periods.
Shorter periods show a steep size distribution for small planets.
Abstract
We develop a general method to fit the planetary distribution function (PLDF) to exoplanet survey data. This maximum likelihood method accommodates more than one planet per star and any number of planet or target star properties. Application to \Kepler data relies on estimates of the efficiency of discovering transits around Solar type stars by Howard et al. (2011). These estimates are shown to agree with theoretical predictions for an ideal transit survey. Using announced \Kepler planet candidates, we fit the PLDF as a joint powerlaw in planet radius, down to 0.5 R_Eart, and orbital period, up to 50 days. The estimated number of planets per star in this sample is ~ 0.7 --- 1.4, where the broad range covers systematic uncertainties in the detection efficiency. To analyze trends in the PLDF we consider four planet samples, divided between shorter and longer periods at 7 days and between…
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