利用 Kepler 和基于模拟的推断约束系外行星种群参数
Constraining exoplanet population parameters with Kepler and simulation-based inference
- Universitat de Barcelona (IEEC-UB)（巴塞罗那大学）
- Reial Acadèmia de Ciències i Arts de Barcelona (RACAB)（巴塞罗那皇家科学与艺术学院）
机构由 AI 辅助整理，请以论文原文为准。
中文总结 AI 辅助
本文提出一个快速系外行星模拟器，结合 SBI 和 Kepler 数据约束 44 个种群参数，初步给出发生率及关键参数约束，并改进未来任务预测。
中文摘要 AI 辅助
在银河系系外行星种群研究这一快速发展的领域背景下，我们提出一个系外行星模拟器，能够在几秒内为数百万颗恒星生成合成种群（Padois et al., 2025）。我们的框架将观测到的系外行星探测结果与最新的行星形成模型相结合，纳入了宿主恒星属性与行星发生率、轨道周期分布以及其他关键人口特征之间的依赖关系。然而，许多模型参数仍不确定且依赖于模型本身。为约束其中一些最关键的参数，我们将模拟器与基于模拟的推断（SBI）相结合：我们定义了 44 个自由参数，用于描述不同类型行星的种群（发生率、质量-周期分布、质量-半径关系等），从宽泛的先验分布中采样运行数百万次模拟，模拟这些行星被 Kepler 探测到的可能性，并训练一种机器学习算法来学习输入参数与由此产生的“观测到的”合成种群之间的关系。然后，通过将模型输出与真实观测进行比较来推断最佳拟合参数，为此我们采用 Kepler 已确认行星目录作为参考数据集，因为它提供了来自单一设施的最大同质样本。我们展示了行星发生率作为恒星质量和金属丰度函数、跨不同行星类型的初步结果，以及对若干关键模拟参数（如轨道周期分布和行星系统内倾角弥散）的约束。这些经过优化的参数使我们能够改进对即将开展的系外行星探测任务（包括 PLATO、Roman 和 HAYDN）的产量预测。
英文摘要
In the context of the rapidly growing field of galactic exoplanet population studies, we present an exoplanet simulator capable of generating synthetic populations for millions of stars in a few seconds (Padois et al., 2025). Our framework combines observed exoplanet detections with the latest planetary formation models, incorporating dependencies between host star properties and planet occurrence rates, orbital period distributions, and other key demographic features. However, many model parameters remain uncertain and model-dependent. To constrain some of the most critical ones, we couple our simulator with simulation-based inference (SBI): we define a set of 44 free parameters describing the population of different planet types (occurrence rates, mass-period distribution, mass-radius relation, etc.), run millions of simulations sampling from broad prior distributions, simulate their detectability by Kepler, and train a machine-learning algorithm to learn the relationships between input parameters and the resulting "observed" synthetic populations. The best-fit parameters are then inferred by comparing model outputs to real observations, for which we adopt the Kepler confirmed planet catalogue as our reference dataset, since it provides the largest homogeneous sample from a single facility. We present preliminary results for the planet occurrence rate as a function of stellar mass and metallicity, across different planet types, along with constraints on several key simulation parameters such as the orbital period distribution and the inclination dispersion within planetary systems. These refined parameters enable us to refine our yield predictions for upcoming exoplanet detection missions, including PLATO, Roman, and HAYDN.
