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An Empirical Model For Intrinsic Alignments: Insights From Cosmological Simulations by Van Alfen, Nicholas; Campbell, Duncan; Blazek, Jonathan; Leonard, C. Danielle; Lanusse, Francois; Hearin, Andrew; Mandelbaum, Rachel; Collaboration, The LSST Dark Energy Science is a scholarly article available to read on EtoBox.

What is An Empirical Model For Intrinsic Alignments: Insights From Cosmological Simulations about?

We extend current models of the halo occupation distribution (HOD) to include a flexible, empirical framework for the forward modeling of the intrinsic alignment (IA) of galaxies. A primary goal of this work is to produce mock galaxy catalogs for the purpose of validating existing models and methods for the mitigation of IA in weak lensing measurements. This technique can also be used to produce new, simulation-based predictions for IA and galaxy clustering. Our model is probabilistically formulated, and rests upon the assumption that the orientations of galaxies exhibit a correlation with their host dark matter (sub)halo orientation or with their position within the halo. We examine the necessary components and phenomenology of such a model by considering the alignments between (sub)halos in a cosmological dark matter only simulation. We then validate this model for a realistic galaxy population in a set of simulations in the IllustrisTNG suite. We create an HOD mock with TNG-like correlations using our method, constraining the associated IA model parameters, with the $\chi^2_{\rm dof}$ between our model's correlations and those of Illustris matching as closely as 1.4 and 1.1 for

Author

Van Alfen, Nicholas; Campbell, Duncan; Blazek, Jonathan; Leonard, C. Danielle; Lanusse, Francois; Hearin, Andrew; Mandelbaum, Rachel; Collaboration, The LSST Dark Energy Science

Published

2023

Language

EN