Comparison of different exoplanet mass detection limit methods using a sample of main-sequence intermediate-type stars

TL;DR

This paper introduces new methods for determining exoplanet mass detection limits from radial velocity data, demonstrating their robustness and improved performance over existing techniques across a sample of active main-sequence stars.

Contribution

The paper presents novel correlation-based and local power analysis methods for more accurate detection limits in stellar radial velocity data.

Findings

Two new methods outperform traditional RMS-based approaches.

The methods are robust across various stellar activity levels.

Detection limits are effectively computed for periods between 2 and 1000 days.

Abstract

The radial velocity (RV) technique is a powerful tool for detecting extrasolar planets and deriving mass detection limits that are useful for constraining planet pulsations and formation models. Detection limit methods must take into account the temporal distribution of power of various origins in the stellar signal. These methods must also be able to be applied to large samples of stellar RV time series We describe new methods for providing detection limits. We compute the detection limits for a sample of ten main sequence stars, which are of G-F-A type, in general active, and/or with detected planets, and various properties. We use them to compare the performances of these methods with those of two other methods used in the litterature. We obtained detection limits in the 2-1000 day period range for ten stars. Two of the proposed methods, based on the correlation between periodograms and the power in the periodogram of the RV time series in specific period ranges, are robust and represent a significant improvement compared to a method based on the root mean square of the RV signal. We conclude that two of the new methods (correlation-based method and local power analysis, i.e. LPA, method) provide robust detection limits, which are better than those provided by methods that do not take into account the temporal sampling.