The rotational evolution of low-mass stars

冷恒星演化场景中的一个重要方面是它们的自转。已经开发的理论模型对自转如何随着质量和年龄的变化做出了明确和可检验的预测。然而，一些物理效应已经被添加到模型中，而不是真正知道它们是否必要，或者是否可以通过观测测试。这与差异旋转与固体模型、磁盘(或行星)锁定以及磁饱和等因素有关。通过非常精确地测量恒星自转，没有混叠和其他非唯一性，例如影响了先前数据的v sin i，作为恒星质量/颜色和恒星年龄的函数，这些观测将简单地消除模型的回旋余地，并从经验上指定恒星的自转演化。因此，这些观察结果将具有超越任何理论模型测试的用处。事实上，我们的调查可能会导致对模型中不必要的东西进行重新评估。因此，我们建议通过精确的时间序列CCD光度测量来确定附近12个疏散星系团中年龄在50-1.5Gyr之间的低质量(中F、G、K和早期M型)恒星的大量自转周期(≥1,000)。在这项名为Stella Open星团调查的调查结束时，我们将毫不含糊地知道FGKM恒星的主序旋转演化随年龄的变化。然后可以使用观测确定的依赖关系的细节来理解全局依赖关系。然后，理论模型将被剥离到最基本的部分，然后重建以符合观察结果，消除多余的影响，并确定新的依赖关系。

An important aspect in the evolutionary scenario of cool stars is their rotation. Theoretical models already developed make definite and testable predictions of how rotation changes with mass and age. However, a number of physical effects have been added into the models without really knowing if they are necessary, or can be tested observationally. This relates, among other things, to differential rotation vs. solid body models, disk-(or planet)-locking, and magnetic saturation. By measuring stellar rotation very precisely, without aliasing and other non-uniquenesses like, e.g., v sin i that have infected prior data, as a function of stellar mass/color and as a function of stellar age, these observations will simply remove wiggle-room for the models, and specify the rotational evolution of stars empirically. The observations therefore will have a usefulness beyond the testing of any theoretical models. In fact, our survey might lead to a re-evaluation of what is (un-)necessary in the models.We therefore propose to determine, from precise time-series CCD photometry, a large number (≥1,000) of rotation periods for low-mass (mid F, G, K, and early M-type) stars in 12 nearby open clusters with ages between 50 Myr and 1.5 Gyr. At the end of this survey, called the STELLA Open Cluster survey, we will know unambiguously, the main-sequence rotational evolution of FGKM stars as a function of age. The details of the observationally determined dependencies can then be used to understand the global dependencies. The theoretical models would then be stripped down to the bare essentials, and then rebuilt to comply with observations, removing superfluous effects and identifying new dependencies.