Signals embedded in the radial velocity noise

TL;DR

This paper demonstrates how Bayesian data analysis techniques can effectively detect low-amplitude signals in noisy astronomical data, potentially revealing habitable planets.

Contribution

It provides an overview of Bayesian methods and applies them to real HARPS-TERRA velocity data for HD 40307, showcasing their practical utility.

Findings

Bayesian techniques improve detection of low-amplitude signals

Application to HD 40307 data identifies potential habitable planet signals

Bayesian methods outperform traditional frequentist approaches in noisy data

Abstract

Bayesian data analysis techniques, together with suitable statistical models, can be used to obtain much more information from noisy data than the traditional frequentist methods. For instance, when searching for periodic signals in noisy data, the Bayesian techniques can be used to define exact detection criteria for low-amplitude signals - the most interesting signals that might correspond to habitable planets. We present an overview of Bayesian techniques and present detailed analyses of the HARPS-TERRA velocities of HD 40307, a nearby star observed to host a candidate habitable planet, to demonstrate in practice the applicability of Bayes' rule to astronomical data.