Related papers: Cosmology with one galaxy?
Recent works have discovered a relatively tight correlation between $\Omega_{\rm m}$ and properties of individual simulated galaxies. Because of this, it has been shown that constraints on $\Omega_{\rm m}$ can be placed using the properties…
Cosmological simulations like CAMELS and IllustrisTNG characterize hundreds of thousands of galaxies using various internal properties. Previous studies have demonstrated that machine learning can be used to infer the cosmological parameter…
We present the first cosmological constraints using only the observed photometry of galaxies. Villaescusa-Navarro et al. (2022; arXiv:2201.02202) recently demonstrated that the internal physical properties of a single simulated galaxy…
Standard cosmological analyses typically treat galaxy formation and cosmological parameter inference as decoupled problems, relying on population-level statistics such as clustering, lensing, or halo abundances. However, classical studies…
We study the impact of warm dark matter mass on the internal properties of individual galaxies using a large suite of 1,024 state-of-the-art cosmological hydrodynamic simulations from the DREAMS project. We take individual galaxies'…
Recent work has pointed out the potential existence of a tight relation between the cosmological parameter $\Omega_{\rm m}$, at fixed $\Omega_{\rm b}$, and the properties of individual galaxies in state-of-the-art cosmological hydrodynamic…
Understanding galaxy properties may be the key to unlocking some of the most intriguing mysteries of modern cosmology. Recent work relied on machine learning to extract cosmological constraints on $\Omega_\mathrm{m}$ using only one galaxy.…
The balance of evidence indicates that individual galaxies and groups or clusters of galaxies are embedded in enormous distributions of cold, weakly interacting dark matter. These dark matter 'halos' provide the scaffolding for all luminous…
Astrophysical processes such as feedback from supernovae and active galactic nuclei modify the properties and spatial distribution of dark matter, gas, and galaxies in a poorly understood way. This uncertainty is one of the main theoretical…
We present in this paper a new three-dimensional galaxy classification system designed to account for the diversity of galaxy properties in the nearby universe. To construct this system we statistically analyse a sample of >22,000 galaxies…
From a set of 3D cosmological simulations which incorporate a self-consistent model of the star-gas interactions, we have been able to obtain a statistically significant sample of galaxy-type halos with observational properties, like colors…
Despite containing about a half of the total matter in the Universe, at most wavelengths the filamentary structure of the cosmic web is difficult to observe. In this work, we use large unigrid cosmological simulations to investigate how the…
Galaxies reside within dark matter halos, but their properties are influenced not only by their halo properties but also by the surrounding environment. We construct an interpretable neural network framework to characterize the surrounding…
The standard cold dark matter plus cosmological constant model predicts that galaxies form within dark-matter haloes, and that low-mass galaxies are more dark-matter dominated than massive ones. The unexpected discovery of two low-mass…
It has been recently shown that a powerful way to constrain cosmological parameters from galaxy redshift surveys is to train graph neural networks to perform field-level likelihood-free inference without imposing cuts on scale. In…
The intrinsic properties of galaxies are influenced by their environments, underscoring the environment's critical role in galaxy formation and evolution. Traditionally, these environments are categorized into four fixed classifications:…
We seek to understand the relationship between galaxy properties and their local environment, which calls for a proper formulation of the notion of environment. We analyse the GIMIC suite of cosmological hydrodynamical simulations within…
The diversity of galaxy morphologies and their relations with galaxy and halo properties is fundamental to understanding galaxy formation. Cosmological simulations of representative volumes can help disentangle the origin of observed…
Recent analyses of cosmological hydrodynamic simulations from CAMELS have shown that machine learning models can predict the parameter describing the total matter content of the universe, $\Omega_{\rm m}$, from the features of a single…
Many approaches to obtaining cosmological constraints rely on the connection between galaxies and dark matter. However, the distribution of galaxies is dependent on their formation and evolution as well as the cosmological model, and galaxy…