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arXiv 2203.07481astro-ph.SRastro-ph.EP
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利用自旋周期约束双星的潮汐品质因数

Constraining Tidal Quality Factor using Spin Period in Eclipsing Binaries

Ruskin Patel, Kaloyan Penev

摘要:

潮汐作用下双星的演化极大地影响了系统的观测特性。随着开普勒和TESS等任务发现大量近距离热木星系统和食双星,了解潮汐对其形成和观测性质的影响程度已变得至关重要。在双星系统中,有效的潮汐耗散可以导致恒星的自旋上升或下降,以及/或自旋-轨道同步,这取决于恒星和轨道之间的角动量交换。我们结合开普勒任务的食双星系统与恒星和轨道参数,在文献中创建一个目录的41食双星适合分析潮汐耗散。经验上,潮汐耗散的效率使用修改的潮汐品质因数($Q_{\star}^{'}$)参数化。我们发现$Q_{\star}^{'}$上的限制使用所观察到的旋转周期的主星在食双星系统。我们详细计算了潮汐、恒星演化和恒星角动量损失对磁风的综合影响下双星系统的演化,并进行了马尔可夫链蒙特卡罗模拟以解释观测数据中的不确定性。我们的分析表明,$\log_{10}{Q^{'}_{\star}}=7.818\pm0.035$可以重现我们的样本中几乎所有系统中观察到的初级星自旋。

英文摘要:

Evolution of binary objects under the influence of tides drastically affects the expected observational properties of the system. With the discovery of a large number of close-in hot Jupiter systems and eclipsing binaries from missions such as Kepler and TESS, it has become imperative to understand the extent of tidal influence on their formation and observed properties. In the case of binary systems, an efficient tidal dissipation can lead to either spin up or spin down of the stars and/or spin-orbit synchronization, depending upon the exchange of angular momentum between the star and the orbit. We combine the eclipsing binary systems from the Kepler mission with stellar and orbital parameters available in the literature to create a catalog of 41 eclipsing binaries suitable for analysis of tidal dissipation. Empirically, the efficiency of tidal dissipation is parameterized using a modified Tidal Quality Factor($Q_{\star}^{'}$). We find constraints on $Q_{\star}^{'}$ using the observed rotation period of the primary star in the eclipsing binary systems. We calculate detailed evolutions of binary systems under the combined influence of tides, stellar evolution, and loss of stellar angular momentum to magnetic winds, and perform Markov Chain Monte Carlo simulations to account for the uncertainties in the observed data. Our analysis shows that $\log_{10}{Q^{'}_{\star}}=7.818\pm0.035$ can reproduce the observed primary star spin in almost all systems in our sample.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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