deeplenstronomy：强引力透镜的数据集模拟包
deeplenstronomy: A dataset simulation package for strong gravitational lensing
摘要：
在光学成像调查数据集中自动搜索强引力透镜通常采用机器学习和深度学习方法。这些技术需要比目前发现的更多的示例系统来训练算法，这产生了对作为训练数据集补充的模拟图像的需要。这项工作介绍并总结了deeplenstronomy，这是一个开源的Python包，可以对天文系统的图像进行高效，大规模和可再现的模拟。一整套单元测试、文档和示例笔记本可以在https://deepskies.github.io/deeplenstronomy/上找到。
英文摘要：
Automated searches for strong gravitational lensing in optical imaging survey datasets often employ machine learning and deep learning approaches. These techniques require more example systems to train the algorithms than have presently been discovered, which creates a need for simulated images as training dataset supplements. This work introduces and summarizes deeplenstronomy, an open-source Python package that enables efficient, large-scale, and reproducible simulation of images of astronomical systems. A full suite of unit tests, documentation, and example notebooks are available at https://deepskies.github.io/deeplenstronomy/ .
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。
