Improved signal detection algorithms for unevenly sampled data. Six signals in the radial velocity data for GJ876

摘要

The hunt for Earth analogue planets orbiting Sun-like stars has forced theintroduction of novel methods to detect signals at, or below, the level of theintrinsic noise of the observations. We present a new global periodogram methodthat returns more information than the classic Lomb-Scargle periodogram methodfor radial velocity signal detection. Our method uses the Minimum Mean SquaredError as a framework to determine the optimal number of genuine signals presentin a radial velocity timeseries using a global search algorithm, meaning we candiscard noise spikes from the data before follow-up analysis. This method alsoallows us to determine the phase and amplitude of the signals we detect,meaning we can track these quantities as a function of time to test if thesignals are stationary or non-stationary. We apply our method to the radialvelocity data for GJ876 as a test system to highlight how the phase informationcan be used to select against non-stationary sources of detected signals inradial velocity data, such as rotational modulation of star spots. Analysis ofthis system yields two new statistically significant signals in the combinedKeck and HARPS velocities with periods of 10 and 15 days. Although a planetwith a period of 15 days would relate to a Laplace resonant chain configurationwith three of the other planets (8:4:2:1), we stress that follow-up dynamicalanalyses are needed to test the reliability of such a six planet system.