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 pipeline that combines state-of-the art of deep learning models with strong lensing simulations initially based on PyAutoLens for strong gravitational lens modeling.
Python, C++, and some previous experience in Machine Learning.
Please DO NOT contact mentors directly by email, and instead please send project inquiries to MLSFT-GSOC@cern.ch with Project Title in the subject and relevant mentors will get in touch with you.