Published July 23, 2021 | Version v1
Poster Open

Extracting rotation rates on 27-d TESS-like light curves downgrading Kepler data

  • 1. AIM, CEA, CNRS, Univ. Paris-Saclay, Univ. Paris Diderot, Sorbonne Paris Cité, F-91191 Gif-sur-Yvette, France
  • 2. Instituto de Astrofísica de Canarias, 38205, La Laguna, Tenerife, Spain
  • 3. Universidad de La Laguna, 38206 La Laguna, Tenerife, Spain
  • 4. Department of Physics, University of Warwick, Coventry, CV4 7AL, UK

Contributors

  • 1. Planetary Science Institute

Description

Evolution of surface magnetic features in the star, such as stellar spots or faculae, can leave a signature in the lightcurves. These features allow us to study the surface rotation period, Prot, of stars. However, the length of the observations is an important limiting factor to determine reliable Prot. Indeed, it is commonly accepted that it is necessary to observe for a period longer than 2-3 times Prot in order to properly determine it. But even when stars are observed for this long (more easily reachable for fast-rotating stars), the observation may happen during a minimum of magnetic activity, which can hamper the Prot detection. It is then challenging to assess the reliability of the extracted Prot as well as the probability of detecting it given the 27-day observation length for the majority of TESS targets. Starting from 55,275 stars with reliable Prot observed by Kepler (Santos et al. 2019 & 2021, Breton et al. 2021), 2,500,000 light curves were created to mimic TESS 27-d observations. In this work preliminary results obtained on a sub-sample of 9,275 stars giving 431,087 independent subseries of 27 d are presented. Realistic limits on the longest reliable Prot depending on the method used as well as the associated probabilities for completeness and reliability of the results are given.

Files

Rotation_subseries_RAGarcia.pdf

Files (12.6 MB)

Name Size Download all
md5:c2ea03d068f7f88d8fde070e35969713
12.6 MB Preview Download

Additional details

References

  • Borucki, W. J., Koch, D., Basri, G., et al. 2010, Sci, 327, 977
  • Breton, S. N., Santos, A. R. G., Bugnet, L., et al. 2021, A&A, 647, A125
  • Ceillier, T., van Saders, J., García, R. A., et al. 2016, MNRAS, 456, 119
  • García, R. A., Ceillier, T., Salabert, D., et al. 2014, A&A, 572, A34
  • García, R. A., Hekker, S., Stello, D., et al. 2011, MNRAS, 414, L6
  • García, R. A., Mathur, S., Pires, S., et al., 2014, A&A, 568, 10
  • Mathur, S., García, R.A., Régulo, S., et al., 2010, A&A 511, A46
  • McQuillan, A., Mazeh, T., & Aigrain, S. 2013, ApJ, 775, L11
  • McQuillan, A., Mazeh, T., & Aigrain, S. 2014, ApJS, 211, 24
  • Ricker, G. R., Winn, J. N., Vanderspek, R., et al. 2014, Proc SPIE, 9143, 914320
  • Santos, A. R. G., García, R. A., Mathur, S., et al. 2019, ApJS, 244, 21
  • Santos, A. R. G., Breton, S.N., Mathur, S., García, R.A., 2021, ApJS, 255, 17
  • Torrence & Compo 1998, Bulletin of the American Meteorological Society, 79, 61