Related papers: Modeling assembly bias with machine learning and s…
We investigate various phenomenological schemes for the rapid generation of 3D mock galaxy catalogues with a given power spectrum and bispectrum. We apply the fast bispectrum estimator \MODALLSS{} to these mock galaxy catalogues and compare…
In this work, we demonstrate how differentiable stochastic sampling techniques developed in the context of deep Reinforcement Learning can be used to perform efficient parameter inference over stochastic, simulation-based, forward models.…
We present a calibration of halo assembly bias using the Separate Universe technique. Specifically, we measure the response of halo abundances at fixed mass and concentration to the presence of an infinite-wavelength initial perturbation.…
We investigate the signatures left by massive neutrinos on the spatial distribution of neutral hydrogen (HI) in the post-reionization era by running hydrodynamic simulations that include massive neutrinos as additional collisionless…
The large-scale linear halo bias encodes the relation between the clustering of dark-matter (DM) halos and that of the underlying matter density field. Although the primary dependence of bias on halo mass is well understood in the context…
We propose a heuristic model that displays the main features of realistic theories for galaxy bias. We show that the low-order clustering statistics of the dark-matter distribution depend almost entirely on the locations and density…
We study the role of the local tidal environment in determining the assembly bias of dark matter haloes. Previous results suggest that the anisotropy of a halo's environment (i.e, whether it lies in a filament or in a more isotropic region)…
Mock catalogues are a crucial tool in the analysis of galaxy surveys data, both for the accurate computation of covariance matrices, and for the optimisation of analysis methodology and validation of data sets. In this paper, we present a…
High-number-density tracers of large-scale structure, such as the HI-rich galaxies measured by 21 cm intensity mapping, have low sampling noise, making them particularly promising as cosmological probes. At large scales, this sampling noise…
Observations of the neutral Hydrogen (\HI ) 21-cm signal hold the potential of allowing us to map out the cosmological large scale structures (LSS) across the entire post-reionization era ($z \leq 6$). Several experiments are planned to map…
Intensity mapping of neutral hydrogen (HI) is a promising observational probe of cosmology and large-scale structure. We present wide field simulations of HI intensity maps based on N-body simulations of a $2.6\, {\rm Gpc / h}$ box with…
We develop a machine learning (ML) framework to populate large dark matter-only simulations with baryonic galaxies. Our ML framework takes input halo properties including halo mass, environment, spin, and recent growth history, and outputs…
One of the main predictions of excursion set theory is that the clustering of dark matter haloes only depends on halo mass. However, it has been long established that the clustering of haloes also depends on other properties, including…
We study halo assembly bias for cluster-sized halos. Previous work has found little evidence for correlations between large-scale bias and halo mass assembly history for simulated cluster-sized halos, in contrast to the significant…
The halo assembly bias, a phenomenon referring to dependencies of the large-scale bias of a dark matter halo other than its mass, is a fundamental property of the standard cosmological model. First discovered in 2005 from the Millennium Run…
We use the TNG300 magneto-hydrodynamic simulation and mock catalogues built using subhalo abundance matching (SHAM) to study the origin of the redshift evolution of the halo occupation distribution (HOD). We analyse stellar-mass selected…
Understanding how galaxies trace the underlying matter density field is essential for characterizing the influence of the large-scale structure on galaxy formation, being therefore a key ingredient in observational cosmology. This…
We present precise measurements of the assembly bias of dark matter halos, i.e. the dependence of halo bias on other properties than the mass, using curved "separate universe" N-body simulations which effectively incorporate an…
We investigate the potential of machine learning (ML) methods to model small-scale galaxy clustering for constraining Halo Occupation Distribution (HOD) parameters. Our analysis reveals that while many ML algorithms report good statistical…
Empirical methods for connecting galaxies to their dark matter halos have become essential for interpreting measurements of the spatial statistics of galaxies. In this work, we present a novel approach for parameterizing the degree of…