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Astronomy & astrophysics

Publication date: 2010-09-01
Volume: 520 11
Publisher: Edp sciences s a

Author:

Hekker, S
Barban, C ; Baudin, F ; De Ridder, Joris ; Kallinger, T ; Morel, T ; Chaplin, WJ ; Elsworth, Y

Keywords:

stars: late-type, stars: oscillations, methods: observational, techniques: photometric, solar p modes, colors, stars, disk, Science & Technology, Physical Sciences, Astronomy & Astrophysics, SOLAR P MODES, COLORS, STARS, DISK, astro-ph.SR, 0201 Astronomical and Space Sciences, 5101 Astronomical sciences, 5107 Particle and high energy physics, 5109 Space sciences

Abstract:

Context. Long timeseries of data increase the frequency resolution in the power spectrum. This allows for resolving stochastically excited modes with long mode lifetimes, as well as features that are close together in frequency. The CoRoT fields observed during the initial run and second long run partly overlap, and stars in this overlapping field observed in both runs are used to create timeseries with a longer timespan than available from the individual runs. Aims: We aim to measure the mode lifetimes of red giants and compare them with theoretical predictions. We also investigate the dependence of the mode lifetimes on frequency and the degree of the oscillation modes. Methods: We perform simulations to investigate the influence of the gap in the data between the initial and second long run, the total length of the run and the signal-to-noise ratio on the measured mode lifetime. This provides us with a correction factor to apply to the mode lifetimes measured from a maximum likelihood fit to the oscillation frequencies. Results: We find that the length of the timeseries, the signal-to-noise ratio and possible gaps do have a non-negligible effect on the measurements of the mode lifetime of stochastically excited oscillation modes, but we can correct for it. For the four stars for which we can perform a fit of the oscillation frequencies, we find that the mode lifetimes depend on frequency and on degree of the mode, which quantitatively agrees with theoretical predictions.