相关论文: Populating Large N-body Simulations with LRGs Usin…

We train graph neural networks to perform field-level likelihood-free inference using galaxy catalogs from state-of-the-art hydrodynamic simulations of the CAMELS project. Our models are rotational, translational, and permutation invariant…

Large photometric surveys will image billions of galaxies, but we currently lack quick, reliable automated ways to infer their physical properties like morphology, stellar mass, and star formation rates. Simulations provide galaxy images…

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…

An important open question today is the understanding of the relevance that dark matter (DM) halo substructure may have for DM searches. In the standard cosmological framework, subhalos are predicted to be largely abundant inside larger…

Luminous red galaxies (LRGs) and blue star-forming emission-line galaxies (ELGs) are key tracers of large-scale structure used by cosmological surveys. Theoretical predictions for such data are often done via simplistic models for the…

The combination of galaxy-galaxy lensing (GGL) and galaxy clustering is a powerful probe of low redshift matter clustering, especially if it is extended to the non-linear regime. To this end, we extend the N-body and halo occupation…

We present an efficient estimator for higher-order galaxy clustering using small groups of nearby galaxies, or multiplets. Using the Luminous Red Galaxy (LRG) sample from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2, we…

We study properties of dark matter halos in a variety of models which include Dark Energy (DE). We consider both DE due to a scalar field self--interacting through Ratra-Peebles or SUGRA potentials, and DE with constant negative w=p\rho…

The presence of additional relativistic particles at the time of recombination can be inferred through their contribution to $\Delta N_{\rm eff}$. If these species have a finite but low mass (Light Massive Relics - LiMRs), they act as a hot…

The evidence in favor of a dark energy component dominating the Universe, and driving its presently accelerated expansion, has progressively grown during the last decade of cosmological observations. If this dark energy is given by a…

In this paper, we present the Discovery simulations: a new pair of high-resolution N-body simulations motivated by the DESI Y1 BAO cosmological constraints on dark energy. The Discovery simulations were run with identical initial…

We study the effects of applying observational techniques to derive the properties of simulated galaxies, with the aim of making an unbiased comparison between observations and simulations. For our study, we used fifteen galaxies simulated…

The recently discovered discrepancy between galaxy mass measurements from weak lensing and predictions from abundance matching questions our understanding of cosmology, or of the galaxy-halo connection, or of both. We re-examined this…

We use 85 pairs of high resolution LCDM cosmological simulations from the NIHAO project to investigate why in dwarf galaxies neutral hydrogen (HI) linewidths measured at 50% of the peak flux W_50 /2 (from the hydrodynamical simulations)…

For modern large-scale structure survey techniques it has become standard practice to test data analysis pipelines on large suites of mock simulations, a task which is currently prohibitively expensive for full N-body simulations. Instead…

In a previous paper, we described a new method for including detailed information about substructure in semi-analytic models of halo formation based on merger trees. In this paper, we compare the predictions of our model with results from…

We present a data-driven dimensionality reduction method that is well-suited for physics-based data representing hyperbolic wave propagation. The method utilizes a specialized neural network architecture called low rank neural…

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…

A physical understanding of galaxy formation and evolution benefits from an understanding of the connections between galaxies, their host dark matter halos, and their environments. In particular, interactions with more-massive neighbors can…

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…