Strong gravitational lensing is a promising probe of the substructure of dark matter to better understand its underlying nature. Deep learning methods have the potential to accurately identify images containing substructure, and differentiate WIMP particle dark matter from other well motivated models, including vortex substructure of dark matter condensates and superfluids.
This project will focus on further development of the simulations used in the DeepLense pipeline which utilize the package lenstronomy. The focus of this project will be to help improve and facilitate the creation of data for applications with various ML approaches in this project.
Total project length: 175/350 hours.
Python and some previous experience with physics or astronomy.
Please use this link to access the test for this project.
Please DO NOT contact mentors directly by email. Instead, please email firstname.lastname@example.org with Project Title and include your CV and test results. The relevant mentors will then get in touch with you.