Radial Velocity Data Analysis with Compressed Sensing Techniques

TL;DR

This paper introduces a fast, all-at-once radial velocity data analysis method using compressed sensing within Gaussian processes, reducing aliasing and simplifying detection of exoplanets.

Contribution

It develops a novel compressed sensing approach compatible with Gaussian processes, enabling efficient simultaneous multi-planet searches in radial velocity data.

Findings

Method produces fewer aliasing peaks than traditional periodograms

Successfully applied to multiple star systems with results matching previous analyses

Detected potential early signals of planets in historical data

Abstract

We present a novel approach for analysing radial velocity data that combines two features: all the planets are searched at once and the algorithm is fast. This is achieved by utilizing compressed sensing techniques, which are modified to be compatible with the Gaussian processes framework. The resulting tool can be used like a Lomb-Scargle periodogram and has the same aspect but with much fewer peaks due to aliasing. The method is applied to five systems with published radial velocity data sets: HD 69830, HD 10180, 55 Cnc, GJ 876 and a simulated very active star. The results are fully compatible with previous analysis, though obtained more straightforwardly. We further show that 55 Cnc e and f could have been respectively detected and suspected in early measurements from the Lick observatory and Hobby-Eberly Telescope available in 2004, and that frequencies due to dynamical interactions in GJ 876 can be seen.