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arXiv 2106.05976astro-ph.COastro-ph.GAastro-ph.IM
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lenstronomy II:一个引力透镜软件生态系统

lenstronomy II: A gravitational lensing software ecosystem

Simon Birrer, Anowar J. Shajib, Daniel Gilman, Aymeric Galan, Jelle Aalbers, Martin Millon, Robert Morgan, Giulia Pagano, Ji Won Park, Luca Teodori, Nicolas Tes… 展开作者

Simon Birrer, Anowar J. Shajib, Daniel Gilman, Aymeric Galan, Jelle Aalbers, Martin Millon, Robert Morgan, Giulia Pagano, Ji Won Park, Luca Teodori, Nicolas Tessore, Madison Ueland, Lyne Van de Vyvere, Sebastian Wagner-Carena, Ewoud Wempe, Lilan Yang, Xuheng Ding, Thomas Schmidt, Dominique Sluse, Ming Zhang, Adam Amara

摘要:

lenstronomy是一个Astropy附属的Python包,用于引力透镜模拟和分析。lenstronomy由Birrer和Amara(2018)引入,基于Birrer等人的线性基集方法。(2015年)。从那时起,用户和开发人员的lenstronomy基础大幅增长,该软件已成为一个组成部分,广泛的最近的分析,如测量哈勃常数与时间延迟强透镜或约束性质的暗物质从解决和未解决的小尺度透镜失真统计。模块化设计使社区能够采用创新的新方法,并在lenstronomy API之上开发具有更具体目标的增强型软件和包装器。通过社区的参与和参与,lenstronomy已经成为一个附属软件包生态系统的基础,扩展了软件的原始范围,并以开源和可复制的方式在强大的引力透镜社区的最前沿证明了其鲁棒性和适用性。

英文摘要:

lenstronomy is an Astropy-affiliated Python package for gravitational lensing simulations and analyses. lenstronomy was introduced by Birrer and Amara (2018) and is based on the linear basis set approach by Birrer et a. (2015). The user and developer base of lenstronomy has substantially grown since then, and the software has become an integral part of a wide range of recent analyses, such as measuring the Hubble constant with time-delay strong lensing or constraining the nature of dark matter from resolved and unresolved small scale lensing distortion statistics. The modular design has allowed the community to incorporate innovative new methods, as well as to develop enhanced software and wrappers with more specific aims on top of the lenstronomy API. Through community engagement and involvement, lenstronomy has become a foundation of an ecosystem of affiliated packages extending the original scope of the software and proving its robustness and applicability at the forefront of the strong gravitational lensing community in an open source and reproducible manner.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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