November 27, 2023 to December 1, 2023
Dual node
Europe/Paris timezone

Finding Observable Environmental Measures of Halo Properties using Neural Networks

Dec 1, 2023, 3:36 PM
Dual node

Dual node

IAP (Paris) & CCA/Flatiron (New York) IAP 98bis Boulevard Arago 75014 Paris FRANCE CCA/Flatiron 5th Avenue New York (NY) USA
Flash talk New York Contributed talks


Haley Bowden (University of Arizona)


Simulations have revealed correlations between the properties of dark matter halos and their environment, made visible by the galaxies which inherit these connections through their host halos. We define a measure of the environment based on the location and observable properties of a galaxy’s nearest neighbors in order to capture the broad information content available in the environment. We then use a neural network to learn the connection between the multi-dimensional space defined by the observable properties of galaxies and the properties of their host halos using mock galaxy-catalogs from UNIVERSEMACHINE. The trained networks will: 1) reveal new connections between galaxy, halo, and environment; 2) serve as a powerful tool for placing galaxies into halos in future cosmological simulations; and 3) be a framework for inferring the properties of real halos from next-generation survey data, allowing for direct comparison between observational statistics and theory. We will first show the results of estimating the masses of halos and sub-halos. This will be followed by preliminary results on halo properties beyond mass, including satellite membership and concentration.

Primary author

Haley Bowden (University of Arizona)


Dr Andrew Hearin (Argonne National Laboratory) Prof. Peter Behroozi (University of Arizona)

Presentation materials