Galaxy cluster mass estimation with deep learning and hydrodynamical simulations

Event Start:
2020-06-01T15:00:00
Event End:
2020-06-01T15:30:00
Event Information:

We evaluate the ability of Convolutional Neural Networks (CNNs) to predict
galaxy cluster masses in the BAHAMAS hydrodynamical simulations. We train
four separate single-channel networks using: stellar mass, soft X-ray
flux, bolometric X-ray flux, and the Compton y parameter as observational
tracers, respectively.  Our training set consists of ~6400 synthetic
cluster images generated from the simulation, while an additional ~1600
images form a test set.  We also train a "multi-channel" CNN by combining

Event Location:
Connect via zoom
Speaker:
Zi'ang Yan (UBC)
Related Upcoming Events:
Astronomy Colloquia
Add to Calendar Event Start: 2020-06-01T15:00:00 Event End: 2020-06-01T15:30:00 Galaxy cluster mass estimation with deep learning and hydrodynamical simulations Event Information: We evaluate the ability of Convolutional Neural Networks (CNNs) to predict galaxy cluster masses in the BAHAMAS hydrodynamical simulations. We train four separate single-channel networks using: stellar mass, soft X-ray flux, bolometric X-ray flux, and the Compton y parameter as observational tracers, respectively.  Our training set consists of ~6400 synthetic cluster images generated from the simulation, while an additional ~1600 images form a test set.  We also train a "multi-channel" CNN by combining Event Location: Connect via zoom
Source URL: https://phas.ubc.ca/galaxy-cluster-mass-estimation-deep-learning-and-hydrodynamical-simulations