MAHGIC: A Model Adapter for the Halo-Galaxy Inter-Connection

TL;DR

This paper introduces MAHGIC, a model that links galaxy properties to dark matter halos using PCA and GBDT, enabling the creation of realistic galaxy mock catalogs from dark matter only simulations.

Contribution

The paper presents a novel, flexible, and interpretable model that connects galaxy and halo histories, trained on hydrodynamic simulations, for application to large dark matter only simulations.

Findings

Model accurately reproduces galaxy properties in DMO simulations.

Uses PCA and GBDT for dimensionality reduction and transformation.

Enables creation of realistic galaxy mock catalogs from dark matter simulations.

Abstract

We develop a model to establish the interconnection between galaxies and their dark matter halos. We use Principal Component Analysis (PCA) to reduce the dimensionality of both the mass assembly histories of halos/subhalos and the star formation histories of galaxies, and Gradient Boosted Decision Trees (GBDT) to transform halo/subhalo properties into galaxy properties. We use two sets of hydrodynamic simulations to motivate our model architecture and to train the transformation. We then apply the two sets of trained models to dark matter only (DMO) simulations to show that the transformation is reliable and statistically accurate. The model trained by a high-resolution hydrodynamic simulation, or by a set of such simulations implementing the same physics of galaxy formation, can thus be applied to large DMO simulations to make "mock" copies of the hydrodynamic simulation. The model is both flexible and interpretable, which paves the way for future applications in which we will constrain the model using observations at different redshifts simultaneously and explore how galaxies form and evolve in dark matter halos empirically.