论文标题

pyfit3d和pypipe3d-积分场光谱数据分析管道的新版本

pyFIT3D and pyPipe3D -- The new version of the Integral Field Spectroscopy data analysis pipeline

论文作者

Lacerda, Eduardo A. D., Sánchez, S. F., Mejía-Narváez, A., Camps-Fariña, A., Espinosa-Ponce, C., Barrera-Ballesteros, J. K., Ibarra-Medel, H., Lugo-Aranda, A. Z.

论文摘要

我们提出了一个新版本的FIT3D和PIPE3D代码,两个包裹可得出恒星种群的性能,并分别从光谱和积分场光谱数据中获得电离发射线。 The new codes have been fully transcribed to Python from the original Perl and C versions, modifying the algorithms when needed to make use of the unique capabilities of this language with the main goals of (1) respecting as much as possible the original philosophy of the algorithms, (2) maintaining a full compatibility with the original version in terms of the format of the required input and produced output files, and (3) improving the efficiency and accuracy of这些算法和求解已知(新发现的)错误。完整的软件包是自由分发的,并在线提供可用的存储库。 PYFIT3D和PYPIPE3D经过全面测试,并通过最新的IFS数据调查和汇编(例如Califa,漫画,Sami和有趣的++)进行了测试,并面临模拟。我们在这里描述代码,其新实现,基于模拟恢复参数的准确性以及在特定数据集上实现的展示。

We present a new version of the FIT3D and Pipe3D codes, two packages to derive properties of the stellar populations and the ionized emission lines from optical spectroscopy and integral field spectroscopy data respectively. The new codes have been fully transcribed to Python from the original Perl and C versions, modifying the algorithms when needed to make use of the unique capabilities of this language with the main goals of (1) respecting as much as possible the original philosophy of the algorithms, (2) maintaining a full compatibility with the original version in terms of the format of the required input and produced output files, and (3) improving the efficiency and accuracy of the algorithms, and solving known (and newly discovered) bugs. The complete package is freely distributed, with an available repository online. pyFIT3D and pyPipe3D are fully tested with data of the most recent IFS data surveys and compilations (e.g. CALIFA, MaNGA, SAMI and AMUSING++), and confronted with simulations. We describe here the code, its new implementation, its accuracy in recovering the parameters based on simulations, and a showcase of its implementation on a particular dataset.

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