校正透射光谱中的恒星污染：同步监测在GJ 1214 b上的应用
Correcting stellar contamination in transmission spectroscopy with contemporaneous monitoring: Application to GJ 1214 b
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中文总结 AI 辅助
本研究针对JWST观测GJ 1214 b时恒星污染问题，提出StarSim反演与UnSPOTTER神经网络两种校正方法，经同步监测验证两者一致，能有效降低污染影响，提升系外行星大气表征精度。
中文摘要 AI 辅助
透射光谱已成为表征凌日系外行星大气的重要工具。然而，恒星表面不均匀性会污染透射光谱，对詹姆斯·韦布空间望远镜（JWST）等高精度观测构成重大挑战。我们开发并应用了校正恒星污染的方法，以提高系外行星大气表征的准确性。我们围绕JWST对GJ 1214 b的观测，获取了协调的多波段测光和高分辨率光谱，并应用了两种框架：（i）StarSim反演，它从监测数据中推断恒星活动参数并将其传播到校正中；（ii）UnSPOTTER，其中在StarSim模拟上训练的神经网络学习从监测数据到校正的映射。两种框架在不确定度内一致，表明GJ 1214的JWST观测发生在有利的旋转相位，恒星污染较低。对于UnSPOTTER，推断的校正可在JWST波长范围内约束在约15 ppm，这意味着校正后残差具有相同量级。如果同一系统在活动极大期附近被观测，预测的污染将呈现强色散性并影响大气反演，这凸显了协调监测和稳健活动校正技术的重要性。这两种方法互补但作用不同。反演产生物理上可解释的参数和表面图，而UnSPOTTER对表面构型简并性进行边缘化，并在其经过验证的模拟域内提供更紧凑的预测校正。我们的流程可推广到其他活动恒星：通过在JWST访问期间进行多波段和多技术监测，它可以为调度提供活动预报和活动校正。
英文摘要
Transmission spectroscopy has emerged as an essential tool for characterising the atmospheres of transiting exoplanets. However, stellar surface inhomogeneities contaminate transmission spectra, posing a major challenge to high-precision observations such as those from the James Webb Space Telescope (JWST). We develop and apply methods to correct for stellar contamination, improving the accuracy of exoplanet atmospheric characterisation. We obtained coordinated multi-band photometry and high-resolution spectroscopy around JWST observations of GJ 1214 b and applied two frameworks: (i) a StarSim inversion, which infers stellar activity parameters from the monitoring data and propagates them to corrections; and (ii) UnSPOTTER, in which neural networks trained on StarSim simulations learn the mapping from monitoring data to corrections. Both frameworks agree within uncertainties and indicate that the JWST observations of GJ 1214 occurred at a favourable rotation phase with low stellar contamination. For UnSPOTTER, the inferred corrections can be constrained at approximately 15 ppm across the JWST wavelength range, implying post-correction residuals of the same order. If the same system were observed near activity maximum, the predicted contamination would be strongly chromatic and affect atmospheric retrievals, highlighting the importance of coordinated monitoring and robust activity correction techniques. The two approaches are complementary but serve different roles. The inversion yields physically interpretable parameters and surface maps, whereas UnSPOTTER marginalises over surface-configuration degeneracies and provides tighter predictive corrections within its validated simulation domain. Our pipeline can be generalised to other active stars: with multi-band and multi-technique monitoring around JWST visits, it can provide activity forecasts for scheduling and activity corrections.
发表机构
- Institut d’Estudis Espacials de Catalunya (IEEC)（加泰罗尼亚空间研究所）
- Institut de Ciències de l’Espai (ICE, CSIC)（太空科学研究所）
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