Enhancing the signal-to-noise ratio of solar-like targets

TL;DR

This paper applies curvelet filtering and partial signal reconstruction to CoRoT solar-like targets to improve the detection of acoustic modes by enhancing the signal-to-noise ratio in their oscillation spectra.

Contribution

It introduces a novel application of curvelet filtering and partial reconstruction techniques to improve mode detection in solar-like oscillation data from CoRoT.

Findings

Enhanced the visibility of acoustic mode ridges in Echelle diagrams.

Improved the signal-to-noise ratio of oscillation signals.

Provided a method to better analyze p modes in noisy data.

Abstract

The analysis of the first solar-like targets done by CoRoT has shown that the oscillation amplitudes are about 25% below the theoretical amplitudes while the convective backgrounds are up to three times higher than in the solar case (Michel et al. 2008). In such conditions, the comb-like structure of the acoustic modes has smaller signal-to-noise ratios than initially expected complicating the characterization of individual modes. In the present work we apply the curvelet filtering to the solar-like targets already observed by CoRoT as well as a partial reconstruction of the signal from the obtained spacing of the comb-like structure of the acoustic modes. It enables us to enhance the signal-to-noise ratio of the ridges in the Echelle diagrams. Finally, we study how the analysis of the p modes can be improved.