Related papers: Predicting Halo Formation Time Using Machine Learn…
One of the key factors influencing galaxy clustering in the nonlinear regime is galaxy assembly bias, which describes the dependence of galaxy clustering on halo properties beyond halo mass. We study this effect by analyzing galaxy samples…
We use a large $N$-body simulation to study the relation of the structural properties of dark matter halos to their assembly history and environment. The complexity of individual halo assembly histories can be well described by a small…
We study the dependence of the cross-correlation between galaxies and galaxy groups on group properties. Confirming previous results, we find that the correlation strength is stronger for more massive groups, in good agreement with the…
Upcoming 21cm surveys will map the spatial distribution of cosmic neutral hydrogen (HI) over unprecedented volumes. Mock catalogues are needed to fully exploit the potential of these surveys. Standard techniques employed to create these…
We examine the age-dependence of dark matter halo clustering in an unprecedented accuracy using a set of 7 high-resolution cosmological simulations each with $N=1024^3$ particles. We measure the bias parameters for halos over a large mass…
We extend the Halo Occupation Distribution (HOD) framework to generate mock galaxy catalogs exhibiting varying levels of "galactic conformity", which has emerged as a potentially powerful probe of environmental effects in galaxy evolution.…
We explore the relation between the structure and mass accretion histories of dark matter halos using a suite of cosmological simulations. We confirm that the formation time, defined as the time when the virial mass of the main progenitor…
Cosmological models in which dark matter consists of cold elementary particles predict that the dark halo population should extend to masses many orders of magnitude below those at which galaxies can form. Here we report a cosmological…
We use an extremely large volume ($2.4h^{-3}{\rm Gpc}^{3}$), high resolution N-body simulation to measure the higher order clustering of dark matter haloes as a function of mass and internal structure. As a result of the large simulation…
All galaxies are thought to reside within large halos of dark matter, whose properties can only be determined from indirect observations. The formation and assembly of galaxies is determined from the interplay between these dark matter…
We explore the phenomenon commonly known as halo assembly bias, whereby dark matter halos of the same mass are found to be more or less clustered when a second halo property is considered, for halos in the mass range $3.7 \times 10^{11} \;…
We investigate the ability of machine learning to infer the virial mass ($M_{\rm vir}$) and the scale radius ($r_{\rm s}$) of galaxy clusters from their observables. Using the Uchuu--UniverseMachine galaxy catalog at $z=0.093$, we generate…
We use the universal mass accretion history recently reported for simulations of halo formation in the cold dark matter model (CDM) to analyze the formation and growth of a single halo. We derive the time-dependent density profile three…
A generic prediction of hierarchical gravitational clustering models is that the distribution of halo formation times should depend relatively strongly on halo mass, massive haloes forming more recently, and depend only weakly, if at all,…
Halo assembly bias is a phenomenon whereby the clustering of dark matter halos is dependent on halo properties, such as age, at fixed mass. Understanding the origin of assembly bias is important for interpreting the clustering of galaxies…
We study the use of parallax microlensing to separate the effects of the mass function of dark massive halo objects (MHOs or `machos') on the one hand and their spatial distribution and kinematics on the other. This disentanglement is…
A method of deriving and using merging history trees of dark matter galaxy haloes directly from pure gravity N-body simulations is presented. This combines the full non-linearity of N-body simulations with the flexibility of the…
We present the novel wide & deep neural network GalaxyNet, which connects the properties of galaxies and dark matter haloes, and is directly trained on observed galaxy statistics using reinforcement learning. The most important halo…
We use the Halo Model to explore the implications of assuming that galaxy luminosities in groups are randomly drawn from an underlying luminosity function. We show that even the simplest of such order statistics models -- one in which this…
We study the evolution of the halo-halo correlation function and bias in a LCDM model using very high-resolution N-body simulations. The high force and mass resolution allows dark matter (DM) halos to survive in the tidal fields in…