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arXiv 2501.08992astro-ph.EPastro-ph.SR
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系外行星宿主星潮汐耗散的经验约束

Empirical Constraints on Tidal Dissipation in Exoplanet Host Stars

Sarah C. Millholland, Morgan MacLeod, Felicia Xiao

AI总结:

本研究提出一种基于潮汐衰减时间分布稳态特征的经验方法,约束了短周期系外行星宿主星潮汐品质因子的大小与频率依赖性,结果支持潮汐共振锁理论。

摘要:

短周期系外行星的轨道由潮汐耗散塑造,但这些潮汐相互作用的机制及相关效率的约束十分有限。我们通过一种新的经验技术,对短周期系外行星宿主星的潮汐品质因子给出了可靠约束。该方法基于分析潮汐衰减时间的族群分布结构,潮汐衰减时间定义为行星因恒星潮汐作用螺旋坠入宿主星的剩余时间。通过简单的合成行星族群模拟与解析理论,我们证明衰减时间分布存在一个近似幂律形式的稳态部分。这一稳态特征在观测到的短周期行星族群的衰减时间分布中清晰可见。我们借此约束了恒星潮汐品质因子的大小与频率依赖性,证明其必然随行星轨道周期急剧下降。具体而言,在$Q_{\u22c6}' = Q_0 (P/2 \u00a0\rm days)^\u03b1$的形式下,我们得到$10^{5.5} \u2a7d Q_0 \u2a7d 10^7$且$-4.33 \u2a7d \u03b1\u2a7d -2$。我们的结果与潮汐共振锁的预测最为吻合,该理论中行星与宿主星内潮汐激发的重力模处于共振锁定状态。

英文摘要:

The orbits of short-period exoplanets are sculpted by tidal dissipation. However, the mechanisms and associated efficiencies of these tidal interactions are poorly constrained. We present robust constraints on the tidal quality factors of short-period exoplanetary host stars through the usage of a novel empirical technique. The method is based on analyzing structures in the population-level distribution of tidal decay times, defined as the time remaining before a planet spirals into its host star due to stellar tides. Using simple synthetic planet population simulations and analytic theory, we show that there exists a steady-state portion of the decay time distribution with an approximately power-law form. This steady-state feature is clearly evident in the decay time distribution of the observed short-period planet population. We use this to constrain both the magnitude and frequency dependence of the stellar tidal quality factor and show that it must decrease sharply with planetary orbital period. Specifically, with $Q_{\star}' = Q_0 (P/2 \ \mathrm{days})^α$, we find $10^{5.5} \lesssim Q_0 \lesssim 10^7$ and $-4.33 \lesssim α\lesssim -2$. Our results are most consistent with predictions from tidal resonance locking, in which the planets are locked into resonance with a tidally excited gravity mode in their host stars.

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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