PhoPS：面向勘测时代天文学的自动测光流水线
PhoPS: An automated photometric pipeline for survey-era astronomy
AI总结：
针对现代天文勘测的海量数据需求，研究人员开发了开源自动测光天体测量流水线 PhoPS，通过动态 Gaia DR3 索引与 RANSAC 零点模型提升精度，适用于小行星光变等天文研究。
AI中文摘要：
现代天文勘测会产生海量成像数据，以及高精度的天体测量和测光参考星表，因此需要自动、鲁棒且不依赖设备的归算流水线。我们提出 PhoPS（点源测光与天体测量），这是一款开源 Python 流水线，可对恒星和太阳系运动天体进行全自动天体测量校准与测光归算。PhoPS 会动态生成传播至观测历元的本地 Gaia DR3 天体测量索引文件，无需预先安装索引集合，同时提升了天体测量精度。测光校准采用基于随机抽样一致性（RANSAC）线性回归的场相关零点模型，以校正渐晕、探测器不均匀性等空间系统误差。天体测量性能通过 1 m TUG100 望远镜获取的 840 幅图像中的 141672 个匹配测量值进行评估，历元传播将截尾 N 加权总 RMS 残差从 0.284 角秒降至 0.241 角秒，提升了 15.0%。测光不确定度模型通过 203 颗参考星和 92980 个测量值进行验证，归一化残差中心接近零，但其宽度与星等相关：亮星（10 ≤ G < 13）的 sigma 值为 2.069，中等亮度恒星（13 ≤ G < 16）为 1.129，暗星（16 ≤ G < 18）为 0.698，表明亮星的不确定度被低估，暗星的不确定度偏保守。PhoPS 为天文图像自动归算提供了轻量、跨平台的解决方案，非常适合小行星光变曲线分析、恒星变异性研究以及观测系统误差诊断。
英文摘要：
Modern astronomical surveys produce large volumes of imaging data together with highly accurate astrometric and photometric reference catalogues, creating a need for automated, robust, and instrument-independent reduction pipelines. We present PhoPS (Photometry and Astrometry of Point Sources), an open-source Python pipeline for fully automated astrometric calibration and photometric reduction of stellar and moving Solar System targets. PhoPS dynamically generates local Gaia DR3 astrometric index files propagated to the observation epoch, eliminating the need for pre-installed index collections while improving astrometric accuracy. Photometric calibration uses a field-dependent zero-point model based on Random Sample Consensus (RANSAC) linear regression to account for spatial systematics such as vignetting and detector non-uniformities. Astrometric performance was evaluated using 141672 matched measurements from 840 images obtained with the 1 m TUG100 telescope. Epoch propagation reduced the clipped N-weighted total RMS residual from 0.284 arcsec to 0.241 arcsec, a 15.0% improvement. The photometric uncertainty model was validated using 203 reference stars and 92980 measurements. Normalized residuals are centered near zero, but their widths are magnitude dependent, with sigma values of 2.069 for bright stars (10 <= G < 13), 1.129 for intermediate-brightness stars (13 <= G < 16), and 0.698 for faint stars (16 <= G < 18), indicating underestimated uncertainties for the brightest stars and conservative uncertainties for the faintest stars. PhoPS provides a lightweight, cross-platform solution for automated astronomical image reduction and is well suited to asteroid light-curve analysis, stellar variability studies, and the diagnosis of observational systematics.
