绘制恒星表面I：旋转光变曲线问题中的简并
Mapping stellar surfaces I: Degeneracies in the rotational light curve problem
摘要：
多亏了开普勒和TESS这样的任务，我们现在可以获得成千上万的高精度，快节奏和长基线恒星光度观测。原则上，这些光变曲线编码了大量关于恒星变化的信息，特别是关于恒星表面的星点分布和其他特征。不幸的是，从旋转光变曲线推断恒星表面性质的问题是众所周知的不适定，因为它往往不承认一个唯一的解决方案。因此，关于斑点的数量、大小、对比度和位置的推断可以非常强烈地依赖于模型、正则化方案或先验的假设。本文的目标是双重的：（1）探索影响恒星光变曲线“反演”问题的各种简并性，以及它们对在未解决的光度测量下从恒星表面可以和不可以学到的东西的影响;以及（2）激励同时对许多恒星的光变曲线进行系综分析，作为文献中采用的常见先验的强大数据驱动替代方案。我们进一步推导出新的结果的零空间上的恒星倾角和临边暗化的依赖性，并表明，单波段光度测量不能唯一地约束数量，如总的斑点覆盖率，而不使用强先验。这是一系列论文中的第一篇，致力于开发用于分析恒星光变曲线和光谱时间序列的新算法和工具，其明确目标是实现对其表面特性的统计鲁棒性推断。
英文摘要：
Thanks to missions like Kepler and TESS, we now have access to tens of thousands of high precision, fast cadence, and long baseline stellar photometric observations. In principle, these light curves encode a vast amount of information about stellar variability and, in particular, about the distribution of starspots and other features on their surfaces. Unfortunately, the problem of inferring stellar surface properties from a rotational light curve is famously ill-posed, as it often does not admit a unique solution. Inference about the number, size, contrast, and location of spots can therefore depend very strongly on the assumptions of the model, the regularization scheme, or the prior. The goal of this paper is twofold: (1) to explore the various degeneracies affecting the stellar light curve "inversion" problem and their effect on what can and cannot be learned from a stellar surface given unresolved photometric measurements; and (2) to motivate ensemble analyses of the light curves of many stars at once as a powerful data-driven alternative to common priors adopted in the literature. We further derive novel results on the dependence of the null space on stellar inclination and limb darkening and show that single-band photometric measurements cannot uniquely constrain quantities like the total spot coverage without the use of strong priors. This is the first in a series of papers devoted to the development of novel algorithms and tools for the analysis of stellar light curves and spectral time series, with the explicit goal of enabling statistically robust inference about their surface properties.
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。
