Inferring the Dark from the Observable: Estimating Halo Masses Using Galaxy Properties
Abstract
The formation and evolution of galaxies are interconnected with that of their host halos. Given this closely related evolutionary history, it should follow that galaxy properties are correlated with their host halo mass. Previous works have shown that star formation rates of galaxies in cluster halos differ systematically from those in field halos, suggesting that host halo mass plays a significant role in the history of galaxy evolution. Here, we examine the correlations between observable galaxy properties - such as stellar mass, star formation rate, half-stellar radius, r−band magnitude, and color - and the underlying host halo mass of galaxies. Central galaxy observables are used to probe host halo mass, while satellite galaxy properties are used to estimate subhalo mass. We perform this analysis using random forest, ordinary least squares (OLS), and symbolic regression. Random forest regression can assess the relative significance of different observable galaxy properties, while OLS and symbolic regression can quantify their relationship with the host halo mass. Our results show that gas mass is generally the most significant property in central galaxies of all halo mass ranges, followed by stellar mass and observed r−band magnitude. Adding parameters such as the colour and magnitude of galaxies improves host halo mass estimations compared to standard stellar-to-halo mass relations. These results show that halo mass likely has a multi-dimensional dependence on galaxy properties and open the avenue of finding a simple way to constrain halo mass based on what is directly observable in galaxy surveys. Finding the observables that have the strongest correlation with halo mass can also motivate future surveys on which areas to concentrate in detail.
Related
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BibTeX
@misc{chen2026inferring,
title = {{Inferring the Dark from the Observable: Estimating Halo Masses Using Galaxy Properties}},
author = {Alice Chen and Syeda Lammim Ahad},
howpublished = {arXiv},
year = {2026},
month = aug,
doi = {10.48550/arxiv.2608.19154},
eprint = {2608.19154},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2608.19154},
}
RIS
TY - UNPB
TI - Inferring the Dark from the Observable: Estimating Halo Masses Using Galaxy Properties
AU - Alice Chen
AU - Syeda Lammim Ahad
PY - 2026
DA - 2026/08/30
PB - arXiv
DO - 10.48550/arxiv.2608.19154
UR - https://arxiv.org/abs/2608.19154
AB - The formation and evolution of galaxies are interconnected with that of their host halos. Given this closely related evolutionary history, it should follow that galaxy properties are correlated with their host halo mass. Previous works have shown that star formation rates of galaxies in cluster halos differ systematically from those in field halos, suggesting that host halo mass plays a significant role in the history of galaxy evolution. Here, we examine the correlations between observable galaxy properties - such as stellar mass, star formation rate, half-stellar radius, r−band magnitude, and color - and the underlying host halo mass of galaxies. Central galaxy observables are used to probe host halo mass, while satellite galaxy properties are used to estimate subhalo mass. We perform this analysis using random forest, ordinary least squares (OLS), and symbolic regression. Random forest regression can assess the relative significance of different observable galaxy properties, while OLS and symbolic regression can quantify their relationship with the host halo mass. Our results show that gas mass is generally the most significant property in central galaxies of all halo mass ranges, followed by stellar mass and observed r−band magnitude. Adding parameters such as the colour and magnitude of galaxies improves host halo mass estimations compared to standard stellar-to-halo mass relations. These results show that halo mass likely has a multi-dimensional dependence on galaxy properties and open the avenue of finding a simple way to constrain halo mass based on what is directly observable in galaxy surveys. Finding the observables that have the strongest correlation with halo mass can also motivate future surveys on which areas to concentrate in detail.
ER -