Related papers: A sparse regression approach for populating dark m…
The difference in shape between the observed galaxy stellar mass function and the predicted dark matter halo mass function is generally explained primarily by feedback processes. Feedback can shape the stellar-halo mass (SHM) relation by…
We place constraints on the matter density of the Universe and the amplitude of clustering using measurements of the galaxy two-point correlation function from the Sloan Digital Sky Survey (SDSS). We generate model predictions for different…
We investigate the connection between galaxies, dark matter halos, and their large-scale environments at $z=0$ with Illustris TNG300 hydrodynamic simulation data. We predict stellar masses from subhalo properties to test two types of…
The number density of galaxy clusters across mass and redshift has been established as a powerful cosmological probe. Cosmological analyses with galaxy clusters traditionally employ scaling relations. However, many challenges arise from…
We present a novel methodology to improve predictions of galaxy formation histories by incorporating semi-stochastic corrections to account for short-timescale variability. Our paper addresses limitations in existing models that capture…
Cumulative number density matching of galaxies is a method to observationally connect descendent galaxies to their typical main progenitors at higher redshifts and thereby to assess the evolution of galaxy properties. The accuracy of this…
We present a new method for inferring galaxy star formation histories (SFH) using machine learning methods coupled with two cosmological hydrodynamic simulations. We train Convolutional Neural Networks to learn the relationship between…
The stellar-mass--halo-mass (SMHM) relation is central to our understanding of galaxy formation and the nature of dark matter. However, its normalisation, slope, and scatter are highly uncertain at dwarf galaxy scales. In this paper, we…
Semi-analytical models (SAMs) are currently the best way to understand the formation of galaxies within the cosmic dark-matter structures. While they fairly well reproduce the local stellar mass functions, correlation functions and…
Subhalo abundance matching (SHAM) has played an important role in improving our understanding of how galaxies populate their host dark matter halos. In essence, the SHAM framework is to find a dark matter halo property that best correlates…
The information extracted from large galaxy surveys with the likes of DES, DESI, Euclid, LSST, SKA, and WFIRST will be greatly enhanced if the resultant galaxy catalogues can be cross-correlated with one another. Predicting the nature of…
We present a novel approach to extracting dwarf galaxies from photometric data to measure their average halo mass profile with weak lensing. We characterise their stellar mass and redshift distributions with a spectroscopic calibration…
In this study, a novel machine learning algorithm is presented for disaggregation of satellite soil moisture (SM) based on self-regularized regressive models (SRRM) using high-resolution correlated information from auxiliary sources. It…
We consider the problem of dense depth prediction from a sparse set of depth measurements and a single RGB image. Since depth estimation from monocular images alone is inherently ambiguous and unreliable, to attain a higher level of…
A forward modelling approach provides simple, fast and realistic simulations of galaxy surveys, without a complex underlying model. For this purpose, galaxy clustering needs to be simulated accurately, both for the usage of clustering as…
Linear mixed models (LMMs), which incorporate fixed and random effects, are key tools for analyzing heterogeneous data, such as in personalized medicine. Nowadays, this type of data is increasingly wide, sometimes containing thousands of…
High-resolution cosmological hydrodynamic simulations are currently limited to relatively small volumes due to their computational expense. However, much larger volumes are required to probe rare, overdense environments, and measure…
To maximize the amount of information extracted from cosmological datasets, simulations that accurately represent these observations are necessary. However, traditional simulations that evolve particles under gravity by estimating…
Galaxy-galaxy lensing is a powerful probe of the relation between galaxies and dark matter halos, but its theoretical interpretation requires a careful modeling of various contributions, such as the contribution from central and satellite…
Shape estimates that quantify the halo anisotropic mass distribution are valuable parameters that provide information on their assembly process and evolution. Measurements of the mean shapes for a sample of cluster-sized halos can be used…