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A Peculiar Use of AI: Predicting Cosmic Velocities with Neural Networks

2 Jun 2021, 16:00 UTC
A Peculiar Use of AI: Predicting Cosmic Velocities with Neural Networks
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Editor’s note: Astrobites is a graduate-student-run organization that digests astrophysical literature for undergraduate students. As part of the partnership between the AAS and astrobites, we occasionally repost astrobites content here at AAS Nova. We hope you enjoy this post from astrobites; the original can be viewed at astrobites.org.
Title: Cosmic Velocity Field Reconstruction Using AI
Authors: Ziyong Wu et al.
First Author’s Institution: Sun Yat-Sen University, China
Status: Published in ApJ
Going with the (Hubble) Flow?
Hubble’s law is a beautifully simple statement: a galaxy caught in the Hubble flow, moving with the expansion of the universe, should be traveling away from us at a speed proportional to its distance. Unfortunately, however, this velocity–distance relation is too good to be true: due to the pesky influence of gravity, Hubble’s law is invalid in the vast majority of cases. In general, a galaxy’s net motion can be attributed to a combination of the Hubble flow, the galaxy’s motion within its galaxy cluster or group, and the motion of the cluster or group itself. We collectively refer to these deviations from the Hubble flow as “peculiar motions” or “peculiar velocities.”
While the presence of peculiar motions spoils the simplicity of Hubble’s law, ...

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