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Context: The detection and identification of oscillation modes (in terms of their $ell$, $m$ and successive $n$) is a great challenge for present and future asteroseismic space missions. The peak tagging is an important step in the analysis of these data to provide estimations of stellar oscillation mode parameters, i.e., frequencies, rotation rates, and further studies on the stellar structure. Aims: To increase the signal-to-noise ratio of the asteroseismic spectra computed from time series representative of MOST and CoRoT observations (30- and 150-day observations). Methods: We apply the curvelet transform -- a recent image processing technique which looks for curved patterns -- to echelle diagrams built using asteroseismic power spectra. In this diagram the eigenfrequencies appear as smooth continuous ridges. To test the method we use Monte Carlo simulations of several sun-like stars with different combinations of rotation rates, rotation-axis inclination and signal-to-noise ratios. Results: The filtered diagrams enhance the contrast between the ridges of the modes and the background allowing a better tagging of the modes and a better extraction of some stellar parameters. Monte Carlo simulations have also shown that the region where modes can be detected is enlarged at lower and higher frequencies compared to the raw spectra. Even more, the extraction of the mean rotational splitting from modes at low frequency can be done more easily than using the raw spectrum.
The differentially rotating outer layers of stars are thought to play a role in driving their magnetic activity, but the underlying mechanisms that generate and sustain differential rotation are poorly understood. We report the measurement of latitud
In previous work we identified six Sun-like stars observed by Kepler with exceptionally clear asteroseismic signatures of rotation. Here, we show that five of these stars exhibit surface variability suitable for measuring rotation. In order to furthe
The advent of Gaia, capable of measuring stellar wobbles caused by orbiting planets, raised an interest to the astrometric detection of exoplanets. Another source of such wobbles (often also called jitter) is stellar magnetic activity. A quantitative
The advent of space-based observatories such as CoRoT and Kepler has enabled the testing of our understanding of stellar evolution on thousands of stars. Evolutionary models typically require five input parameters, the mass, initial Helium abundance,
Asteroseismology, as a tool to use the indirect information contained in stellar oscillations to probe the stellar interiors, is an active field of research presently. Stellar age, as a fundamental property of star apart from its mass, is most diffic