Related papers: The scatter in the galaxy-halo connection: a machi…
We present a machine learning (ML) approach for the prediction of galaxies' dark matter halo masses that achieves an improved performance over conventional methods. We train three ML algorithms (\texttt{XGBoost}, Random Forests, and neural…
The halo model (HM) describes the inhomogeneous universe as a collection of halos. The full nonlinear power spectrum of the universe is well approximated by the HM, whose prediction can be easily computed without lengthy numerical…
We predict the stellar mass -- halo mass (SMHM) relationship for dwarf galaxies, using simulated galaxies with peak halo masses of M$_{\rm peak} = 10^{11}$ M$_{\odot}$ down into the ultra-faint dwarf range to M$_{\rm peak} =$ 10$^7$…
Galaxies grow and evolve in dark matter halos. Because dark matter is not visible, galaxies' halo masses ($\rm{M}_{\rm{halo}}$) must be inferred indirectly. We present a graph neural network (GNN) model for predicting $\rm{M}_{\rm{halo}}$…
In the present work we study the statistics of haloes, which in the halo model determines the distribution of galaxies. Haloes are known to be biased tracer of dark matter, and at large scales it is usually assumed there is no intrinsic…
We investigate a series of galaxy properties computed using the merger trees and environmental histories from dark matter only cosmological simulations, using a semi-recurrent neural network producing self-consistent predictions of galaxy…
Several measurements of QSO-galaxy correlations have reported signals much larger than predictions of magnification by large-scale structure. We find that the expected signal depends stronly on the properties of the foreground galaxy…
We study the biasing relation between dark-matter halos or galaxies and the underlying mass distribution, using cosmological $N$-body simulations in which galaxies are modelled via semi-analytic recipes. The nonlinear, stochastic biasing is…
We present a novel methodology to improve predictions of galaxy formation histories by incorporating semi-stochastic corrections to account for short-timescale variability. Our paper addresses limitations in existing models that capture…
The stellar-to-halo mass relation (SHMR) is a fundamental relationship between galaxies and their host dark matter haloes. In this study, we examine the scatter in this relation for primary galaxies in the semi-analytic L-Galaxies model and…
We present a Bayesian hierarchical inference formalism to study the relation between the properties of dark matter halos and those of their central galaxies using weak gravitational lensing. Unlike traditional methods, this technique does…
Galaxy assembly bias, the correlation between galaxy properties and halo properties at fixed halo mass, could be an important ingredient in halo-based modelling of galaxy clustering. We investigate the central galaxy assembly bias by…
Intrinsic alignments of galaxies are a significant astrophysical systematic affecting cosmological constraints from weak gravitational lensing. Obtaining numerical predictions from hydrodynamical simulations of expected survey volumes is…
Galaxies reside within dark matter halos, but their properties are influenced not only by their halo properties but also by the surrounding environment. We construct an interpretable neural network framework to characterize the surrounding…
We demonstrate how the properties of a galaxy depend on the mass of its host dark matter subhalo, using two independent models of galaxy formation. For the cases of stellar mass and black hole mass, the median property value displays a…
The clustering of galaxies in ongoing and upcoming galaxy surveys contains a wealth of cosmological information, but extracting this information is a non-trivial task since galaxies and their host haloes are stochastic tracers of the matter…
The empirical HOD model of Wang et al. 2006 fits, by construction, both the stellar mass function and correlation function of galaxies in the local Universe. In contrast, the semi-analytical models of De Lucia & Blazoit 2007 (DLB07) and Guo…
Using data from TNG300-2, we train a neural network (NN) to recreate the stellar mass ($M^*$) and star formation rate (SFR) of central galaxies in a dark-matter-only simulation. We consider 12 input properties from the halo and sub-halo…
Understanding the connections between galaxy stellar mass, star formation rate, and dark matter halo mass represents a key goal of the theory of galaxy formation. Cosmological simulations that include hydrodynamics, physical treatments of…
Marked statistics allow sensitive tests of how galaxy properties correlate with environment, as well as of how correlations between galaxy properties are affected by environment. A halo-model description of marked correlations is developed,…