Inferring planet occurrence rates from radial velocities

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 re-weight 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.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-12-18
DOI
https://doi.org/10.1051/0004-6361/202557774/pdf
Primary Topic
Stellar, planetary, and galactic studies
Type
article
Field-Weighted Citation Impact
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article

Inferring planet occurrence rates from radial velocities

Springer Link (Chiba Institute of Technology)
Stellar, planetary, and galactic studies
article

Inferring planet occurrence rates from radial velocities

article en

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 re-weight 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.

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 35%
Stellar, planetary, and galactic studies
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Inferring planet occurrence rates from radial velocities · Springer Link (Chiba Institute of Technology) (2025) | TGRS Research Map | TGRS