AI 中文总结
研究旨在解决天文图像数据处理软件缺乏通用性问题，核心方法是利用astropy等Python包编写phoptic管道，贡献是实现通用灵活的测光处理，提升信噪比，且在多核CPU上高度可扩展。
AI 中文摘要
公开可用的测光管道使非专家也能进行天文数据处理，减少人为误差并实现可重复处理。但许多定制软件基于特定仪器编写，缺乏通用性。为此，我们推出了用Python编写的开源测光管道phoptic。它最初专为墨西哥圣佩德罗马蒂尔国家天文台2.1米望远镜上的三相机系统OPTICAM设计，现在已成为通用管道。其核心利用astropy Python包及其附属包，使用photutils进行背景估计、源检测和孔径测光，还实现了最佳测光，将信噪比提高约10%。我们描述了phoptic的功能，讨论了其默认行为，并通过处理来自HiPERCAM、MEXMAN、OPTICAM和ULTRACAM仪器的数据展示了其灵活接口，还评估了性能，表明它在多核CPU上具有高度可扩展性。
英文摘要
Publicly-available photometry pipelines make astronomical data reduction accessible to non-experts, reduce the margin for human error, and enable reproducible reduction. In many cases, bespoke reduction software is written on a per-instrument basis; this results in rigid pipelines that cannot be straightforwardly applied to data from other instruments. To alleviate this problem, we present phoptic, an open source photometry pipeline written in Python. phoptic began as a dedicated pipeline for the the OPtical TIming CAMera (OPTICAM), a triple-camera system mounted on the 2.1~m telescope at the Observatorio Astronomico Nacional in San Pedro Martir, Mexico. However, phoptic now serves as a generic photometry pipeline with a simple interface to reduce data from other instruments. At its core, phoptic leverages the astropy Python package, and affiliated packages thereof, to provide a flexible, modern, and interoperable reduction pipeline. In particular, phoptic uses photutils for background estimation, source detection, and performing aperture photometry. Additionally, phoptic implements optimal photometry, improving the signal-to-noise ratio over aperture photometry by up to $\sim 10$ per cent. We describe phoptic's functionality, discuss its default behaviour, and demonstrate its flexible interface by reducing data from the HiPERCAM, MEXMAN, OPTICAM, and ULTRACAM instruments. We also review the performance of phoptic, and show that it is highly scalable on multi-core CPUs.
Comments27 pages, 21 figures, accepted for publication in RASTI
