用于引力透镜事件贝叶斯分析的BAGLE Python包
The BAGLE Python Package for Bayesian Analysis of Gravitational Lensing Events
AI总结：
BAGLE包用于引力透镜事件的贝叶斯分析，通过建模和联合拟合光度和视差数据，帮助识别孤立恒星级黑洞。
摘要：
我们介绍了开源的Python包BAGLE（引力透镜事件的贝叶斯分析），它能够对光度和视差数据集进行建模和联合拟合。我们描述了模型参数化，并给出了包含点光源、点透镜或有限源、点透镜几何结构的微透镜事件的方程，无论是否考虑由于地球或卫星绕太阳运动引起的微透镜视差。还推导了不同坐标参考框架之间的转换。我们将我们的模型光曲线与其它论文和微透镜建模软件的光曲线进行比较，发现有良好的一致性，尽管在有限源模型中存在约1%的差异，这在即将由空间设施观测时可以检测到。我们还使用BAGLE来展示改变透镜质量、透镜距离和混合同源通量比例对光度光变曲线和视差轨迹的影响，以准备即将到来的Gaia数据发布和罗马空间望远镜及其银河系晕时域调查（GBTDS）的发射。特别是，我们表明罗马GBTDS将能够检测到持续时间比地面观测少一倍的事件的显著微透镜视差信号。此外，持续时间超过100天的长持续时间事件将产生微透镜视差不确定性小于0.01的罗马数据，这将有助于确认孤立的恒星级黑洞，这些黑洞可以使用BAGLE进行光度和视差建模以实现精确的质量确定。BAGLE是一个开源代码，鼓励社区开发。
英文摘要：
We present the open-source Python package, BAGLE (Bayesian Analysis of Gravitational Lensing Events), which enables modeling and joint fitting of photometric and astrometric data sets. We describe the model parameterizations and present the equations for microlensing events containing either a point-source, point-lens or a finite-source, point-lens geometry both with and without microlensing parallax due to the motion of the Earth or a satellite around the Sun. Conversions between different coordinate reference frames are also derived. We compare our model light curves to those from other papers and microlens modeling software, finding good agreement, although with some differences in finite-source models at a ~1% level detectable with upcoming observations from space-based facilities. We also use BAGLE to demonstrate the impact of changing lens mass, lens distance, and blended source flux fraction on photometric lightcurves and astrometric trajectories in preparation for upcoming Gaia data releases and the launch of the Nancy Grace Roman Space Telescope and its Galactic Bulge Time Domain Survey (GBTDS). In particular, we show that Roman GBTDS will detect significant microlensing parallax signals for events that are 2x shorter in duration than from ground-based surveys. Additionally, long-duration events with durations of $\t_{E,\odot} >$ 100 days will yield microlensing parallax uncertainties of $σ_{π_E} <$ 0.01 with Roman, enabling confident identification of isolated stellar-mass black holes that can be modeled both astrometrically and photometrically with BAGLE for precise mass determinations. BAGLE is an open-source code and community development is encouraged.
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