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The formation of structure in the Universe at large scales is dominated by gravity, with baryonic physics becoming significant at $\sim{\rm Mpc}$ scales. To capture the impact of baryonic physics, cosmological simulations must model gas…
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…
This work explores the relationships between galaxy sizes and related observable galaxy properties in a large volume cosmological hydrodynamical simulation. The objectives of this work are to both develop a better understanding of the…
We present a new machine learning model for estimating photometric redshifts with improved accuracy for galaxies in Pan-STARRS1 data release 1. Depending on the estimation range of redshifts, this model based on neural networks can handle…
The future astronomical imaging surveys are set to provide precise constraints on cosmological parameters, such as dark energy. However, production of synthetic data for these surveys, to test and validate analysis methods, suffers from a…
Hydrodynamical simulations of galaxy formation and evolution attempt to fully model the physics that shapes galaxies. The agreement between the morphology of simulated and real galaxies, and the way the morphological types are distributed…
Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics…
We review theoretical approaches to the study of galaxy formation, with emphasis on the role of hydrodynamic simulations in modeling the high redshift galaxy population. We present new predictions for the abundance of star-forming galaxies…
Modeling and simulation of complex fluid flows with dynamics that span multiple spatio-temporal scales is a fundamental challenge in many scientific and engineering domains. Full-scale resolving simulations for systems such as highly…
We introduce the AGORA project, a comprehensive numerical study of well-resolved galaxies within the LCDM cosmology. Cosmological hydrodynamic simulations with force resolutions of ~100 proper pc or better will be run with a variety of code…
Galaxy-scale strong lenses in galaxy clusters provide a unique tool to investigate their inner mass distribution and the sub-halo density profiles in the low-mass regime, which can be compared with the predictions from cosmological…
Feedback effects generated by supernovae (SNe) and active galactic nuclei (AGNs) are pivotal in shaping the evolution of galaxies and their present-day structures. However, our understanding of the specific mechanisms operating at galactic…
Weak gravitational lensing maps compactly encode the evolution of cosmic large-scale structure and are a key tool for cosmological analyses. Performing inference directly at the map level allows flexible choices of statistics and can…
By opening up new avenues to statistically constrain astrophysics and cosmology with large-scale structure observations, the line intensity mapping (LIM) technique calls for novel tools for efficient forward modeling and inference. Implicit…
Hydrodynamical simulations play a fundamental role in modern cosmological research, serving as a crucial bridge between theoretical predictions and observational data. However, due to their computational intensity, these simulations are…
Understanding the evolution of galaxies provides crucial insights into a broad range of aspects in astrophysics, including structure formation and growth, the nature of dark energy and dark matter, baryonic physics, and more. It is,…
It is important for Large Language Models (LLMs) to be aware of the boundary of their knowledge, distinguishing queries they can confidently answer from those that lie beyond their capabilities. Such awareness enables models to perform…
We present predictions for the galaxy-galaxy lensing profile from the EAGLE hydrodynamical cosmological simulation at redshift z=0.18, in the spatial range 0.02 < R/(Mpc/h) < 2, and for five logarithmically equi-spaced stellar mass bins in…
Galaxies co-evolve with their host dark matter halos. Models of the galaxy-halo connection, calibrated using cosmological hydrodynamic simulations, can be used to populate dark matter halo catalogs with galaxies. We present a new method for…
Cosmic voids are the largest and most underdense structures in the Universe. Their properties have been shown to encode precious information about the laws and constituents of the Universe. We show that machine learning techniques can…