Features of Gaia DR3 Spectroscopic Binaries I. Tidal circularization of Main-Sequence Stars
Auteurs : Dolev Bashi, Tsevi Mazeh, Simchon Faigler
Résumé : Previous studies pointed out that many observed samples of short-period binaries display a cutoff period, $P_{\rm cut}$, such that almost all binaries with periods shorter than $P_{\rm cut}$ have circular orbits. This feature is probably due to long-term circularization processes induced by tidal interaction between the two stars of each binary. It seemed as if coeval main-sequence (MS) samples of open clusters display $P_{\rm cut}$ that depends on the sample age. Using the unprecedentedly large sample of MS spectroscopic orbits recently released by $\textit{Gaia}$ we have found that the $P_{\rm cut}$ does not depend on the stellar age but, instead, varies with stellar temperature, decreasing linearly from $6.5$ day at $T_{\rm eff}\sim 5700$ K to $\sim 2.5$ day at $6800$ K. $P_{\rm cut}$ was derived by a new algorithm that relied on clear upper envelopes displayed in the period-eccentricity diagrams. Our $P_{\rm cut}$ determines both the border between the circular and eccentric binaries and the location of the upper envelope. The results are inconsistent with the theory which assumes circularization occurs during the stellar MS phase, a theory that was adopted by many studies. The circularization has probably taken place at the pre-main-sequence phase, as suggested already in 1989 by Zahn and Bouchet, and later by Khaluillin and Khaluillina in 2011. Our results suggest that the weak dependence of $P_{\rm cut}$ on the cluster age is not significant, and/or might be due to the different temperatures of the samples. If indeed true, this has far-reaching implications for the theory of binary and exoplanet circularization, synchronization, and alignment.
Explorez l'arbre d'article
Cliquez sur les nœuds de l'arborescence pour être redirigé vers un article donné et accéder à leurs résumés et assistant virtuel
Recherchez des articles similaires (en version bêta)
En cliquant sur le bouton ci-dessus, notre algorithme analysera tous les articles de notre base de données pour trouver le plus proche en fonction du contenu des articles complets et pas seulement des métadonnées. Veuillez noter que cela ne fonctionne que pour les articles pour lesquels nous avons généré des résumés et que vous pouvez le réexécuter de temps en temps pour obtenir un résultat plus précis pendant que notre base de données s'agrandit.