Related papers: Finding universal relations in subhalo properties …
The abundance and demographics of dark matter substructure is important for many areas in astrophysics and cosmological $N$-body simulations have been the primary tool used to investigate them. However, it has recently become clear that the…
We explore the dependence of the subhalo mass function on the spectral index n of the linear matter power spectrum using scale-free Einstein-de Sitter simulations with n=-1 and n=-2.5. We carefully consider finite volume effects that may…
The abundance of dark matter haloes is one of the key probes of the growth of structure and expansion history of the Universe. Theoretical predictions for this quantity usually assume that, when expressed in a certain form, it depends only…
Predicting the spatial distribution of objects as a function of cosmology is an essential ingredient for the exploitation of future galaxy surveys. In this paper we show that a specially-designed suite of gravity-only simulations together…
We investigate the expressive power of deep residual neural networks idealized as continuous dynamical systems through control theory. Specifically, we consider two properties that arise from supervised learning, namely universal…
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 measure the mass function of dark matter halos in a large set of collisionless cosmological simulations of flat LCDM cosmology and investigate its evolution at z<~2. Halos are identified as isolated density peaks, and their masses are…
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 $\rm{M}_{\rm{halo}}$…
We use large cosmological N-body simulations to study the subhalo population in galaxy group sized halos. In particular, we look for fossil group candidates with typical masses ~10-25% of Virgo cluster but with an order of magnitude less…
We show that deep neural networks trained across diverse tasks exhibit remarkably similar low-dimensional parametric subspaces. We provide the first large-scale empirical evidence that demonstrates that neural networks systematically…
In a previous paper, we described a new method for including detailed information about substructure in semi-analytic models of dark matter halo formation based on merger trees. In this paper, we present the basic predictions of our full…
Next-generation surveys will provide photometric and spectroscopic data of millions to billions of galaxies with unprecedented precision. This offers a unique chance to improve our understanding of the galaxy evolution and the unresolved…
Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely…
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…
The identification of substructures within halos in cosmological hydrodynamical simulations is a fundamental step to identify the simulated counterparts of real objects, namely galaxies. For this reason, substructure finders play a crucial…
We present a theoretical formalism by which the global and the local mass functions of dark matter substructures (dark subhalos) can be analytically estimated. The global subhalo mass function is defined to give the total number density of…
Machine learning has been widely applied to clearly defined problems of astronomy and astrophysics. However, deep learning and its conceptual differences to classical machine learning have been largely overlooked in these fields. The broad…
We have developed a simple yet surprisingly accurate analytic scheme for tracking the dynamical evolution of substructure within larger dark halos. The scheme incorporates the effects of dynamical friction, tidal mass loss and tidal heating…
This is the first of a series of three Papers devoted to the study of halo substructure in hierarchical cosmologies by means of the CUSP formalism. In the present Paper we derive the properties of subhaloes and diffuse dark matter (dDM)…
We have identified over 2000 well resolved cluster halos, and also their associated bound subhalos, from the output of a 1024^3 particle cosmological N-body simulation (of box size 320 h^-1 Mpc and softening length 3.2 h^-1 kpc). This has…