相关论文: Cosmic velocity, density and halo mass function: I…

We analyze the properties of dark matter halos in the cold-plus-warm dark matter cosmologies (CWDM). We study their dependence on the fraction and velocity dispersion of the warm particle, keeping the free-streaming scale fixed. To this end…

Cosmological surveys aim at answering fundamental questions about our Universe, including the nature of dark matter or the reason of unexpected accelerated expansion of the Universe. In order to answer these questions, two important…

We present an approximation for the average density profile of dark matter haloes in the LambdaCDM cosmological model, which is accurate to within 10--15% even for large radial distances from 0.05R_{vir} up to 10R_{vir} for halo masses…

We present the results of a series of cosmological $N$-body simulations of a Vector Dark Energy (VDE) model, performed using a suitably modified version of the publicly available \texttt{GADGET}-2 code. The setups of our simulations were…

In Hot or Warm Dark Matter universes the density fluctuations at early times contain very little power below a characteristic wavelength related inversely to the particle mass. We study how discreteness noise influences the growth of…

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…

Matter evolved under influence of gravity from minuscule density fluctuations. Non-perturbative structure formed hierarchically over all scales, and developed non-Gaussian features in the Universe, known as the Cosmic Web. To fully…

Based on recent advancements in using machine learning for classical density functional theory for systems with one-dimensional, planar inhomogeneities, we propose a machine learning model for application in two dimensions (2D) akin to…

$\Lambda$CDM-model predicts an excess of dark halos compared to the observations. The excess is seen from the estimates of the virialized mass inside the Local Supercluster and its surroundings. It is shown that account for cosmological…

In this article, we employ a machine learning (ML) approach for the estimations of four fundamental parameters, namely, the Hubble constant ($H_0$), matter ($\Omega_{0m}$), curvature ($\Omega_{0k}$) and vacuum ($\Omega_{0\Lambda}$)…

The characteristic prediction of the Cold Dark Matter (CDM) model of cosmological structure formation is that the Universe should contain a wealth of small-scale structure -- low-mass dark matter haloes and subhaloes. However, galaxy…

We develop a machine learning approach to reconstructing the cosmological initial conditions from late-time dark matter halo number density fields in redshift space, with the goal of improving sensitivity to cosmological parameters, and in…

We use N-body simulations to investigate the structure of dark halos in the standard Cold Dark Matter cosmogony. Halos are excised from simulations of cosmologically representative regions and are resimulated individually at high…

Based on a set of cosmological N-body simulations we analyze properties of the dark matter haloes (DM) in a galaxy mass range ($10^{11} - 10^{13} h^{-1}M_{\odot}$) in modified $\lcdm$ cosmology with additional dynamically screened scalar…

The non-linear, scale-dependent bias in the mass distribution of galaxies and the underlying dark matter is a key systematic affecting the extraction of cosmological parameters from galaxy clustering. Using 95 million halos from the…

Accurately predicting structural properties of dark matter halos is one of the fundamental goals of modern cosmology. We use the new suite of MultiDark cosmological simulations to study the evolution of dark matter halo density profiles,…

We present a general method to compute the nonlinear matter power spectrum for dark energy and modified gravity scenarios with percent-level accuracy. By adopting the halo model and nonlinear perturbation theory, we predict the reaction of…

Dark matter self-interactions may have the capability to solve or at least mitigate small-scale problems of the cosmological standard model, Lambda Cold Dark Matter. There are a variety of self-interacting dark matter models that lead to…

We present some preliminary results from a series of extremely large, high-resolution N-body simulations of the formation of early nonlinear structures. We find that the high-z halo mass function is inconsistent with the Sheth-Tormen mass…

Machine learning has the potential to improve the reconstruction of the dark matter profile of galaxies with respect to traditional methods, like rotation curves. We demonstrate on the simulation suite Illustris-TNG that a steerable…