A team of scientists led from Carnegie Mellon University (CMU) has trained artificial intelligence (AI) on data from simulated clusters of galaxies, in which the composition of all the components is known. This AI went on to predict a mass for the real-world Coma Cluster of galaxies that agrees with those from earlier, more human-labor-intensive attempts. The result offers the possibility of faster, more accurate assessment of the masses of galaxy clusters.
The post Artificial Intelligence Learns to Judge Mass of Galaxy Clusters appeared first on HPCwire.
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