RV exoplanets and stellar activity

虽然径向速度（RV）方法在十多年来一直主导着系外行星的发现领域，但近年来，它在某种程度上被开普勒任务等天基凌日观测的丰富结果所掩盖。然而，rv仍然是在附近恒星的温带轨道上搜索低质量行星的强大工具，是表征任何过境行星的关键组成部分，也是探测行星系统外部部分的直接成像方法的直接补充（而且便宜得多）。如今，RV摄谱仪的精度通常能达到m/s以下，而天体物理噪声源，特别是恒星活动，限制了它们对温带轨道上的低质量行星的灵敏度。为了克服这个问题，我们正在开发创新的方法来提取和模拟房车，并使用最先进的贝叶斯机器学习技术来区分恒星和行星信号。具体而言，将恒星光谱直接建模为高斯过程（GP）的多个观测值，在不同的休息波长取样，并优化历元之间的波长位移以及GP的参数。然后将得到的相对rv与各种恒星活动指标同时进行分析，以解开活动和行星信号。这些工具仍需要进一步开发，但已经产生了非常有希望的结果。这个博士项目将包括进一步开发和测试这些方法，并将它们应用于RV调查的新数据，以及K2和TESS卫星发现的新凌日行星的RV跟踪。它可以为CHEOPS任务提供支持，并将最终帮助优化PLATO任务的后续工作，以及对未来RV光谱仪（如INT/HARPS3， VLT/ESPRESSO和E-ELT/HIRES）的数据进行分析。这个项目属于STFC的关键科学问题：B：恒星和行星系统是如何发展的，生命是我们星球独有的吗？它将涉及与一些领导RV搜索系外行星的小组合作，包括剑桥大学的D.奎洛兹教授小组，以及与将GPs应用于系外行星数据集的专家合作，包括D.福尔曼-麦基博士（Flatiron研究所计算天体物理中心）。

While the radial velocity (RV) method dominated the field of exoplanet discovery for over a decade, in recent years it has been somewhat overshadowed by the wealth of results from space-based transit surveys such as the Kepler mission. However, RVs remain a powerful tool to search for low-mass planets in temperate orbits around nearby stars, a crucial component of the characterisation of any transiting planet, and a direct (and much cheaper) complement to direct imaging methods which probe the outer parts of planetary systems. Nowadays, RV spectrographs routinely reach sub-m/s precision, and it is astrophysical noise sources, particularly stellar activity, that limit their sensitivity to low-mass planets on temperate orbits. To overcome this, we are developing innovative methods to extract and model RVs and distinguish between stellar and planetary signals, using state-of-the art Bayesian machine learning techniques. Specifically, the stellar spectra are modelled directly as multiple observations of a Gaussian process (GP) sampled at slightly different rest wavelengths, and the wavelength shifts between epoch are optimized together with the parameters of the GP. The resulting relative RVs are then analysed simultaneously with various stellar activity indicators to disentangle activity and planetary signals.These tools still need further development, but are already giving very promising results. This PhD project will consist in developing and testing these methods further, and applying them to new data from RV surveys, as well as RV follow-up of new transiting planets discovered by the K2 and TESS satellites. It may provide support to the CHEOPS mission and will ultimately help optimized the follow-up of the PLATO mission, as well as the analysis of data from future RV spectrographs such as INT/HARPS3, VLT/ESPRESSO and E-ELT/HIRES.This project falls within the STFC key science question: B: How do stars and planetary systems develop and is life unique to our planet? It will involve collaborations with a number of groups leading RV searches for exoplanets, including Prof D. Queloz's group at the University of Cambridge, as well as with experts in the application of GPs to exoplanet datasets, including Dr D. Foreman-Mackey (Center for Computational Astrophysics, Flatiron Institute).