Inferring planet occurrence rates from radial velocities

TL;DR

This paper presents a novel statistical method to estimate planet occurrence rates from radial velocity data, improving efficiency and accuracy by eliminating the need for traditional detection threshold methods.

Contribution

The paper introduces an importance sampling-based approach that combines posterior samples from multiple stars to infer occurrence rates without injection-recovery tests.

Findings

The method produces unbiased occurrence rate estimates.

It increases precision with more stellar data.

Validated on simulated datasets.

Abstract

We introduce a new method to infer the posterior distribution for planet occurrence rates from radial-velocity (RV) observations. The approach combines posterior samples from the analysis of individual RV datasets of several stars, using importance sampling to reweight them appropriately. This eliminates the need for injection-recovery tests to compute detection limits and avoids the explicit definition of a detection threshold. We validate the method on simulated RV datasets and show that it yields unbiased estimates of the occurrence rate in different regions, with increasing precision as more stars are included in the analysis.