Unmasking Stellar Variability: Hierarchical Bayesian methods for characterization of low-mass planets with EPRV spectroscopy

系外行星是围绕太阳以外的恒星运行的行星。探测系外行星的一种方法是寻找由于任何轨道行星的引力作用而引起的恒星摆动。恒星的运动导致观测到的星光颜色发生变化。类地系外行星发出的信号非常小，可能被恒星的其他变化所掩盖或混淆。在寻找系外行星的信号时，这个挑战是有问题的。研究人员将通过分析星光来描述由于恒星变化而发生的变化。这些结果将提供一种新的方法来区分岩石行星和恒星变异性的信号。如果成功，这些新方法将有助于探测潜在的类地行星。这项研究通过促进科学进步和开发寻找行星的新方法，符合我们的国家利益。提高行星探测的可靠性有可能增加公众对科学的信任。所开发的方法和工具将供大学水平课程的研究人员和教师使用。由于低质量系外行星在恒星光谱时间序列上产生的信号非常小，因此探测低质量系外行星具有挑战性。另一个问题是，恒星活动对光谱的影响还没有得到充分的了解，可能会隐藏或模仿行星信号。近年来，由于新型极精密径向速度（EPRV）光谱仪的光谱质量的提高，光谱研究取得了一定的进展。这些仪器的稳定性、分辨率和/或波长覆盖范围的提高，为解决恒星活动在掩盖行星信号方面所起的深远影响提供了新的机会，或者更糟的是，模仿行星信号可能导致错误的系外行星探测。光谱线形状的变化包含了恒星活动的相关信息，这与解开由低质量系外行星引起的恒星活动的真实多普勒频移的影响有关。研究人员的目标是开发统计方法，专门提高检测小多普勒频移和线形变化的能力，从而提高对恒星活动对光谱影响的理解。研究人员将开发对单个谱线特性进行稳健估计的方法，这些谱线特性将用于建立非行星径向速度信号的高级统计模型。这些方法将使用两台EPRV光谱仪观测到的恒星光谱进行测试，以评估方法在不同光谱仪上的一致性。学生研究助理将从代表性不足的少数民族中招聘，并将开发公众参与材料。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Exoplanets are planets that orbit stars other than the Sun. One approach for detecting exoplanets looks for a wobble of a star due to the gravitational pull of any orbiting planets. The motion of the star causes changes in the observed color of starlight. The signal of Earth-like exoplanets is very small and can be obscured by or confused with other variations in the star. This challenge is problematic when seeking the signal of an exoplanet. The investigators will characterize the changes that occur due to variations in the star by analyzing starlight. The results will provide a new approach to differentiate the signals of rocky planets from stellar variability. If successful, these new methods will contribute to the detection of potentially Earth-like planets. This research serves our national interest by promoting the progress of science and developing new methods for finding planets. Increasing the reliability of planet detections has the potential to increase public trust in science. The methods and tools developed will be available for researchers and teachers of college-level courses.The detection of low-mass exoplanets is challenging due to the very small signal that low-mass exoplanets induce on the time series of stellar spectra. Another issue is that the effects of stellar activity on the spectra are not sufficiently understood and may hide or mimic a planetary signal. In recent years, progress has been made thanks to the improvements in quality of spectra from new extreme precision radial velocity (EPRV) spectrometers. The increased stability, resolution and/or wavelength coverage of these instruments provides new opportunities for addressing the profound effect that stellar activity plays in obscuring planetary signals or, perhaps worse, mimicking a planetary signal which can lead to false exoplanet detections. Changes in the shapes of spectral lines contain information about stellar activity relevant for disentangling the effects of stellar activity from true Doppler shifts due to low-mass exoplanets. The investigators aim to develop statistical methods that specifically enhance the ability to detect small Doppler shifts and line shape changes, so as to improve the understanding of the effects of stellar activity on spectra. The investigators will develop methods for robust estimation of individual spectral line properties that will be used to build an advanced statistical model for non-planetary radial velocity signals. The methods will be tested using spectra from stars observed by two EPRV spectrometers in order to evaluate the consistency of the methods across different spectrographs. Student research assistants will be recruited from underrepresented minorities and public engagement material will be developed.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.