1 research outputs found
Dark Matter Subhalos, Strong Lensing and Machine Learning
We investigate the possibility of applying machine learning techniques to
images of strongly lensed galaxies to detect a low mass cut-off in the spectrum
of dark matter sub-halos within the lens system. We generate lensed images of
systems containing substructure in seven different categories corresponding to
lower mass cut-offs ranging from down to . We use
convolutional neural networks to perform a multi-classification sorting of
these images and see that the algorithm is able to correctly identify the lower
mass cut-off within an order of magnitude to better than 93% accuracy.Comment: 20 page