deeplenstronomy: A dataset simulation package for strong gravitational lensing
Abstract
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/ .
- Publication:
-
The Journal of Open Source Software
- Pub Date:
- February 2021
- DOI:
- 10.21105/joss.02854
- arXiv:
- arXiv:2102.02830
- Bibcode:
- 2021JOSS....6.2854M
- Keywords:
-
- Python;
- simulation;
- Jupyter Notebook;
- Batchfile;
- strong lensing;
- astronomy;
- Astrophysics - Instrumentation and Methods for Astrophysics;
- Astrophysics - Cosmology and Nongalactic Astrophysics;
- General Relativity and Quantum Cosmology
- E-Print:
- Published in the Journal of Open Source Software