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arXiv · astro-ph/0012224

Variability in ultra cool dwarfs: evidence for the evolution of surface features

Abstract

We present photometric light curves for a sample of 21 ultra cool M and L dwarfs in the field and in the young open clusters sigma Orionis and the Pleiades. Evidence for variability with RMS amplitudes (in the I band) of 0.01 to 0.055 magnitudes on timescales of 0.4 to 100 hours is discovered in half of these objects. Power spectral analysis using the CLEAN algorithm was performed to search for evidence of periodic variability. Some objects show strong periodicities at around a few hours, which could be due to rotational modulation of the light curve by surface features. However, several objects do not have any significant periodicities to explain their variability. The vsini values of a similar population of objects makes it very likely that our time sampling was sensitive to the expected range of rotation periods, and simulations show that we would have detected these if they were caused by long-lived surface features. We argue that this absence of periodicity is due to the evolution of the brightness, and presumably also the physical size, of surface features on timescales of a few to a few tens of hours. This is supported in the case of 2M1145 for which two light curves have been obtained one year apart and show no common periodicity. The surface features could plausibly be photospheric dust clouds or magnetically-induced spots. The recently observed decline in chromospheric activity for late type M and L dwarfs hints towards the former explanation for at least our later-type objects. Furthermore, our sample suggests that variability to be more common in objects later than M9, indicating that the variability may be related to dust formation. One light curve shows a brief, but significant, dip, which could be a short-lived feature or possibly an eclipse by a companion. (abridged)

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C. A. L. Bailer-Jones, R. Mundt. 2000-12-11. Variability in ultra cool dwarfs: evidence for the evolution of surface features. https://doi.org/10.1051/0004-6361%3A20000416

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