相关论文: A sparse regression approach for populating dark m…
We use TNG and EAGLE hydrodynamic simulations to investigate the central galaxy - dark matter halo relations that are needed for a halo-based empirical model of star formation in galaxies. Using a linear dimension reduction algorithm and a…
The generalized linear model (GLM) plays a key role in regression analyses. In high-dimensional data, the sparse GLM has been used but it is not robust against outliers. Recently, the robust methods have been proposed for the specific…
The increase in the observed volume in cosmological surveys imposes various challenges on simulation preparations. Firstly, the volume of the simulations required increases proportionally to the observations. However, large-volume…
Accurate knowledge of the morphology of halos and its evolution are key constraints on the galaxy formation model as well as a determinant parameter of the strong-lensing phenomenon. Using the cosmological hydrodynamic simulation, the…
Distinguishing active galaxies from star-forming galaxies is essential for understanding galaxy evolution. Diagnostic methods like the BPT (Baldwin, Phillips, and Terlevich) diagram use optical emission-line ratios to separate galaxies.…
We search for parameters defined from photometric images to quantify the ex situ stellar mass fraction of galaxies. We created mock images using galaxies in the cosmological hydrodynamical simulations TNG100, EAGLE, and TNG50 at redshift…
To operate effectively in the real world, agents should be able to act from high-dimensional raw sensory input such as images and achieve diverse goals across long time-horizons. Current deep reinforcement and imitation learning methods can…
We explore the mass content of galaxies residing in galaxy clusters at z=0 in the EAGLE hydrodynamical simulation as well as the galaxies' mass build-up through cosmic time. We use a galaxy catalogue generated with the HBT+ algorithm, which…
In this work, we expand and test the capabilities of our recently developed super-resolution (SR) model to generate high-resolution (HR) realizations of the full phase-space matter distribution, including both displacement and velocity,…
Reliable extraction of cosmological information from clustering measurements of galaxy surveys requires estimation of the error covariance matrices of observables. The accuracy of covariance matrices is limited by our ability to generate…
We present a new cosmological probe for galaxy clusters, the halo sparsity. This characterises halos in terms of the ratio of halo masses measured at two different radii and carries cosmological information encoded in the halo mass profile.…
Galactic conformity is the phenomenon in which a galaxy of a certain physical property is correlated with its neighbors of the same property, implying a possible causal relationship. The observed auto correlations of emission line galaxies…
A key ingredient for semi-analytic models (SAMs) of galaxy formation is the mass assembly history of haloes, encoded in a tree structure. The most commonly used method to construct halo merger histories is based on the outcomes of…
Recent studies emphasize that an empirical relation between the stellar mass of galaxies and the mass of their host dark matter subhaloes can predict the clustering of galaxies and its evolution with cosmic time. In this paper we study the…
We present improved modelling of the redshift-space distortions of galaxy clustering that arise from peculiar velocities. We create mock galaxy catalogues in the framework of the halo model, using data from the Bolshoi project. These mock…
We investigate how a property of a galaxy correlates most tightly with a property of its host dark matter halo, using state-of-the-art hydrodynamical simulations of galaxy formation EAGLE, Illustris, and IllustrisTNG. Unlike most of the…
Context: Understanding the evolution of the dark matter halos of galaxies after they become part of a cluster is essential for understanding the evolution of these satellite galaxies. Aims: We investigate the potential of galaxy-galaxy…
SubHalo Abundance Matching (SHAM) is an empirical method for constructing galaxy catalogues based on high-resolution $N$-body simulations. We apply SHAM on the UNIT simulation to simulate SDSS BOSS/eBOSS Luminous Red Galaxies (LRGs) within…
We present an artificial neural network design in which past and present-day properties of dark matter halos and their local environment are used to predict time-resolved star formation histories and stellar metallicity histories of central…
We simulate the assembly of a massive rich cluster and the formation of its constituent galaxies in a flat, low-density universe. Our most accurate model follows the collapse, the star-formation history and the orbital motion of all…