Related papers: How the Galaxy-Halo Connection Depends on Large-Sc…
We introduce a novel technique for constraining cosmological parameters and galaxy assembly bias using non-linear redshift-space clustering of galaxies. We scale cosmological N-body simulations and insert galaxies with the SubHalo Abundance…
Generative deep learning methods built upon Convolutional Neural Networks (CNNs) provide a great tool for predicting non-linear structure in cosmology. In this work we predict high resolution dark matter halos from large scale, low…
The halo masses $M_{halo}$ of low surface brightness (LSB) galaxies are critical measurements for understanding their formation processes. One promising method to estimate a galaxy's $M_{halo}$ is to exploit the empirical scaling relation…
We study the impact of warm dark matter (WDM) particle mass on galaxy properties using 1,024 state-of-the-art cosmological hydrodynamical simulations from the DREAMS project. We begin by using a Multilayer Perceptron (MLP) coupled with a…
We use the IllustrisTNG300-ODM simulation to investigate the spin bias of low-mass halos and its connection to the strong clustering of ultra-diffuse galaxies (UDGs) reported by Zhang et al. (2025). By comparing two halo spin…
Testing the standard cosmological model ($\Lambda$CDM) at small scales is challenging. Galaxies that inhabit low-mass dark matter halos provide an ideal test bed for dark matter models by linking observational properties of galaxies at…
As the environment harbouring the majority of galaxies, filaments are thought to play a key role in the co-evolution of galaxies and the cosmic web. In this first part of a series to understand the link between galaxies and filaments…
Strong gravitational lensing offers a powerful probe of the detailed distribution of matter in lenses, while magnifying and bringing faint background sources into view. Observed strong lensing by massive galaxy clusters, which are often in…
Properties of galaxies like their absolute magnitude and their stellar mass content are correlated. These correlations are tighter for close pairs of galaxies, which is called galactic conformity. In hierarchical structure formation…
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…
Motivated by previous findings that the magnitude gap between certain satellite galaxy and the central galaxy can be used to improve the estimation of halo mass, we carry out a systematic study of the information content of different member…
Models of the galaxy-halo connection are needed to understand both galaxy clusters and large scale structure. To make said models, we need a robust method that assigns galaxies to halos and matches the observed and simulated stellar-halo…
We use explainable neural networks to connect the evolutionary history of dark matter halos with their density profiles. The network captures independent factors of variation in the density profiles within a low-dimensional representation,…
The matter environment of galaxies is connected to the physics of galaxy formation and evolution. Utilising galaxy-galaxy-galaxy lensing as a direct probe, we map out the distribution of correlated surface mass-density around galaxy pairs…
The circum-galactic medium (CGM) can feasibly be mapped by multiwavelength surveys covering broad swaths of the sky. With multiple large datasets becoming available in the near future, we develop a likelihood-free Deep Learning technique…
Using N-body+hydro simulations we study relations between the local environments of galaxies on 0.5 Mpc scale and properties of the luminous components of galaxies. Our numerical simulations include effects of star formation and supernova…
Cosmological constraints derived from galaxy clusters rely on accurate predictions of cluster observable properties, in which feedback from active galactic nuclei (AGN) is a critical component. In order to model the physical effects due to…
We present a simple, self-consistent model to predict the maximum masses of giant molecular clouds (GMCs), stellar clusters and high-redshift clumps as a function of the galactic environment. Recent works have proposed that these maximum…
Galaxy-galaxy lensing is a powerful probe of the connection between galaxies and their host dark matter halos, which is important both for galaxy evolution and cosmology. We extend the measurement and modeling of the galaxy-galaxy lensing…
Understanding the physical connection between cluster galaxies and massive haloes is key to mitigating systematic uncertainties in next-generation cluster cosmology. We develop a novel method to infer the level of conformity between the…