AMPEL工作流用于LSST：模块化且可复现的实时光度分类
AMPEL workflows for LSST: Modular and reproducible real-time photometric classification
AI总结：
本文介绍AMPEL工具集及其三个通道（SNGuess、FollowMe、FinalBet），用于LSST实时光度分类，基于ELAsTiCC模拟验证，实现高效、可复现的瞬变源发现、无偏样本选择及分类，支持FAIR原则。
AI中文摘要：
现代时域天文调查产生高吞吐量的数据流，这需要用于处理和分析的工具。这对于充分利用维拉·鲁宾天文台（VRO）警报流的项目至关重要，因为在所有瞬变源中，只有一小部分会获得光谱标签。在此背景下，AMPEL工具集可作为一个代码到数据的平台，用于开发高效、可复现且灵活的工作流，以支持实时天文应用。\n我们在此介绍三个不同的AMPEL通道，旨在突出警报流的不同用途：快速发现婴儿期瞬变源（SNGuess）、为后续观测提供无偏瞬变样本（FollowMe）以及提供最终瞬变分类（FinalBet）。这些管道已包含对优化使用VRO警报至关重要的机制占位符：结合不同分类器、包含宿主星系信息、群体先验以及采样非高斯光度红移分布。基于ELAsTiCC模拟，所有三个通道已在高水平上运行：SNGuess正确标记了99%的年轻超新星，FollowMe展示了如何在宇宙学探针背景下为光谱后续观测选择无偏警报子集，而FinalBet包含先验以实现对超过约80%的河外瞬变源的成功分类。\n这里展示的完全功能化的工作流均为公开可用，可作为任何希望针对其特定VRO科学项目优化管道的团队的起点。AMPEL的设计允许按照FAIR原则进行：软件和结果均可轻松共享，结果可复现。代码到数据的环境确保以这种方式开发的模型可直接应用于由AMPEL解析的实时LSST数据流。
英文摘要：
Modern time-domain astronomical surveys produce high throughput data streams which require tools for processing and analysis. This will be critical for programs making full use of the alert stream from the Vera Rubin Observatory (VRO), where spectroscopic labels will only be available for a small subset of all transients. In this context, the AMPEL toolset can work as a code-to-data platform for the development of efficient, reproducible and flexible workflows for real-time astronomical application. We here introduce three different AMPEL channels constructed to highlight different uses of alert streams: to rapidly find infant transients (SNGuess), to provide unbiased transient samples for follow-up (FollowMe) and to deliver final transient classifications (FinalBet). These pipelines already contain placeholders for mechanisms which will be essential for the optimal usage of VRO alerts: combining different classifiers, including host galaxy information, population priors and sampling non-gaussian photometric redshift distributions. Based on the ELAsTiCC simulation, all three channels are already working at a high level: SNGuess correctly tags 99% of all young supernovae, FollowMe illustrates how an unbiased subset of alerts can be selected for spectroscopic follow-up in the context of cosmological probes and FinalBet includes priors to achieve successful classifications for >~80% of all extragalactic transients. The fully functional workflows presented here are all public and can be used as starting points for any group wishing to optimize pipelines for their specific VRO science programs. AMPEL is designed to allow this to be done in accordance with FAIR principles: both software and results can be easily shared and results reproduced. The code-to-data environment ensures that models developed this way can be directly applied to the real-time LSST stream parsed by AMPEL.
