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arXiv 2603.04519astro-ph.EPastro-ph.IMastro-ph.SR
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NASA的Pandora小卫星任务:模拟恒星光球异质性及其校正的影响

NASA's Pandora SmallSat Mission: Simulating the Impact of Stellar Photospheric Heterogeneity and Its Correction

Massachusetts Institute of Technology(麻省理工学院);NASA Goddard Space Flight Center(NASA戈达德太空飞行中心);The University of Arizona(亚利桑那大学);Lawrence Livermore National Laboratory(劳伦斯利弗莫尔国家实验室);Arizona State University(亚利桑那州立大学)
Benjamin V. Rackham, Aishwarya R. Iyer, Dániel Apai, Peter McGill, Yoav Rotman, Knicole D. Colón, Brett M. Morris, Emily A. Gilbert, Elisa V. Quintana, Jessie L… 展开作者

Benjamin V. Rackham, Aishwarya R. Iyer, Dániel Apai, Peter McGill, Yoav Rotman, Knicole D. Colón, Brett M. Morris, Emily A. Gilbert, Elisa V. Quintana, Jessie L. Dotson, Thomas Barclay, Pete Supsinskas, Jordan Karburn, Christina Hedges, Jason F. Rowe, David R. Ciardi, Jessie L. Christiansen, Trevor O. Foote, Thomas P. Greene, Kelsey Hoffman, Rae Holcomb, Aurora Y. Kesseli, Veselin B. Kostov, Nikole K. Lewis, James P. Mason, Gregory Mosby, Susan E. Mullally, Joshua E. Schlieder, Megan Weiner Mansfield, Luis Welbanks, Allison Youngblood

AI总结:

本文通过Pandora小卫星任务模拟,研究恒星光球异质性对系外行星传输光谱学的影响,展示其通过可见光光度计和近红外光谱学同时观测,校正恒星污染的能力。

摘要:

恒星光球异质性是影响系外行星传输光谱学的主要天体物理系统误差。NASA的Pandora小卫星任务旨在通过同时观测系外行星宿主恒星的可见光光度计和近红外光谱学来解决这一挑战。本文提出了一项端到端的模拟研究,量化了Pandora推断恒星光球性质并利用非凌星观测校正恒星污染的能力。我们构建了八个代表性的恒星活动场景,生成了160个模拟Pandora数据集,包含时间依赖的恒星光谱、仪器响应和噪声。在准确的模型下,Pandora光谱光度计的贝叶斯检索能够以典型不确定性约为30K的精度恢复光球温度。包含两个光谱成分(即平静光球和暗斑)的模型在95%的情况下被强烈偏好;当真实的暗斑填充因子低于约0.3%的检测阈值时,单成分模型更受青睐。我们将真实的和推断的恒星参数传播,以计算真实、推断和残差污染信号,基于物理动机的暗斑几何形状。对于简单的暗斑分布,污染信号从10²-10³ppm减少到约10ppm,低于Pandora预期的传输光谱学精度(30-100ppm)。对于更复杂的暗斑分布,几何退化限制了确定性校正,导致残差污染在10³ppm水平,必须通过额外的约束,如暗斑穿越事件和联合恒星-行星传输光谱检索来缓解。这些结果定义了可以通过恒星观测单独校正恒星污染的区域,并展示了Pandora恒星观测如何识别需要额外信息的案例。

英文摘要:

Stellar photospheric heterogeneity is a dominant astrophysical systematic impacting exoplanet transmission spectroscopy. NASA's Pandora SmallSat Mission is designed to address this challenge through contemporaneous visible photometry and NIR spectroscopy of exoplanet host stars. Here we present an end-to-end simulation study quantifying Pandora's ability to infer stellar photospheric properties and correct stellar contamination using out-of-transit observations. We construct eight representative stellar activity scenarios and generate 160 simulated Pandora datasets, incorporating time-dependent stellar spectra, instrument response, and noise. Given accurate models, Bayesian retrievals of Pandora spectrophotometry recover photospheric temperatures with typical uncertainties of ${\approx}30$ K, with no significant bias. Models with two spectral components (i.e., quiescent photosphere and spots) are strongly favored in 95% of cases; one-component models are preferred when true spot filling factors fall below a detection threshold of ${\approx}0.3$%. We propagate the true and inferred stellar parameters to compute true, inferred, and residual contamination signals under physically motivated spot geometries. For simple spot distributions, contamination signals of $10^2{-}10^3$ ppm are reduced to ${\lesssim}10$ ppm, well below Pandora's expected transmission spectroscopy precision (30$-$100 ppm). For more complex spot distributions, geometric degeneracies limit deterministic corrections, leaving residual contamination at the $10^3$ ppm level that must be mitigated using additional constraints, such as spot-crossing events and joint stellar-planetary retrievals of transmission spectra. These results define regimes in which stellar contamination can be corrected from stellar observations alone and show how Pandora stellar observations can identify cases where additional information is required.

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。

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