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Stellar activity in open clusters

Published online by Cambridge University Press:  23 December 2024

A. Görgei Open the ORCID record for A. Görgei [Opens in a new window] ,
K. Vida Open the ORCID record for K. Vida [Opens in a new window] ,
B. Seli  and
L. Kriskovics
A. Görgei*
Affiliation:
Konkoly Observatory, HUN-REN Research Centre for Astronomy and Earth Sciences, Budapest, Hungary CSFK, MTA Centre of Excellence, Budapest, Hungary Eötvös Loránd University, Budapest, Hungary
K. Vida
Affiliation:
Konkoly Observatory, HUN-REN Research Centre for Astronomy and Earth Sciences, Budapest, Hungary CSFK, MTA Centre of Excellence, Budapest, Hungary
B. Seli
Affiliation:
Konkoly Observatory, HUN-REN Research Centre for Astronomy and Earth Sciences, Budapest, Hungary CSFK, MTA Centre of Excellence, Budapest, Hungary Eötvös Loránd University, Budapest, Hungary
L. Kriskovics
Affiliation:
Konkoly Observatory, HUN-REN Research Centre for Astronomy and Earth Sciences, Budapest, Hungary CSFK, MTA Centre of Excellence, Budapest, Hungary
*
email: gorgei.anna@csfk.org
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Abstract

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Stellar activity depends on multiple parameters one of which is the age of the star. The members of open clusters are good targets to observe the activity at a given age of the stars since their ages are more precisely determined than that of field stars. Choosing multiple clusters, each with different age, gives us insight to the change in activity during the lifetime of stars. With the analysis of these stars we can also refine the parameters of gyrochronology (Barnes 2003), which is a method for estimating the age of low-mass, main sequence stars from their rotation periods.

Keywords

Stars: activityrotationmethods: data analysistechniques: photometry
Type
Contributed Paper
Information
Proceedings of the International Astronomical Union , Volume 19 , Symposium S365: Dynamics of Solar and Stellar Convection Zones and Atmospheres , December 2023 , pp. 436 - 440
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Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of International Astronomical Union

References

Barnes, S. A. 2003, On the Rotational Evolution of Solar- and Late-Type Stars, Its Magnetic Origins, and the Possibility of Stellar Gyrochronology. Astrophys. J., 586(1), 464–479.CrossRefGoogle Scholar
Creevey, O. L., Sordo, R., Pailler, F., Frémat, Y., Heiter, U., Thévenin, F., Andrae, R., & Fouesneau, M. e. a. 2023, Gaia Data Release 3. Astrophysical parameters inference system (Apsis). I. Methods and content overview. A&A, 674, A26.Google Scholar
Douglas, S. T., Curtis, J. L., Agüeros, M. A., Cargile, P. A., Brewer, J. M., Meibom, S., & Jansen, T. 2019, K2 Rotation Periods for Low-mass Hyads and a Quantitative Comparison of the Distribution of Slow Rotators in the Hyades and Praesepe. Astrophys. J., 879(2), 100.CrossRefGoogle Scholar
Collaboration, Gaia, Prusti, T., & de Bruijne, J. H. J. e. a. 2016, The Gaia mission. A&A, 595, A1.Google Scholar
Collaboration, Gaia, Vallenari, A., Brown, A. G. A., Prusti, T., & de Bruijne, J. H. J. e. a. 2023, Gaia Data Release 3. Summary of the content and survey properties. A&A, 674, A1.Google Scholar
McInnes, L., Healy, J., & Astels, S. 2017, hdbscan: Hierarchical density based clustering. The Journal of Open Source Software, 2(11).CrossRefGoogle Scholar
Núñez, A., Agüeros, M. A., Curtis, J. L., Covey, K. R., Douglas, S. T., Chu, S. R., DeLaurentiis, S., Wang, M., & Drake, J. J. 2023, The Factory and the Beehive. V. Chromospheric and Coronal Activity and Its Dependence on Rotation in Praesepe and the Hyades. arXiv e-prints,, arXiv:2311.18690.Google Scholar
Ricker, G. R., Winn, J. N., & Vanderspek, R. e. a. 2015, Transiting Exoplanet Survey Satellite (TESS). Journal of Astronomical Telescopes, Instruments, and Systems, 1, 014003.CrossRefGoogle Scholar
VanderPlas, J. T. 2018, Understanding the Lomb-Scargle Periodogram. Astrophysical Journal Supplement Series, 236(1), 16.CrossRefGoogle Scholar
Vida, K., Bódi, A., Szklenár, T., & Seli, B. 2021, Finding flares in Kepler and TESS data with recurrent deep neural networks. Astron. Astrophys., 652, A107.CrossRefGoogle Scholar