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Cosmological surveys aim at answering fundamental questions about our Universe, including the nature of dark matter or the reason of unexpected accelerated expansion of the Universe. In order to answer these questions, two important…
Maps of cosmic structure produced by galaxy surveys are one of the key tools for answering fundamental questions about the Universe. Accurate theoretical predictions for these quantities are needed to maximize the scientific return of these…
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…
We develop a model to establish the interconnection between galaxies and their dark matter halos. We use Principal Component Analysis (PCA) to reduce the dimensionality of both the mass assembly histories of halos/subhalos and the star…
Cosmological simulations play an important role in the interpretation of astronomical data, in particular in comparing observed data to our theoretical expectations. However, to compare data with these simulations, the simulations in…
Cosmologists at the Institute of Computational Cosmology, Durham University, have developed a state of the art model of galaxy formation known as Galform, intended to contribute to our understanding of the formation, growth and subsequent…
The new generation of upcoming deep photometric and spectroscopic surveys will allow us to measure the astrophysical properties of faint galaxies in massive clusters. This would demand to produce simulations of galaxy clusters with better…
Cosmological hydrodynamical simulations, while the current state-of-the art methodology for generating theoretical predictions for the large scale structures of the Universe, are among the most expensive simulation tools, requiring upwards…
While cosmological dark matter-only simulations relying solely on gravitational effects are comparably fast to compute, baryonic properties in simulated galaxies require complex hydrodynamic simulations that are computationally costly to…
We extend a machine learning (ML) framework presented previously to model galaxy formation and evolution in a hierarchical universe using N-body + hydrodynamical simulations. In this work, we show that ML is a promising technique to study…
We present the first systematic study of multi-domain map-to-map translation in galaxy formation simulations, leveraging deep generative models to predict diverse galactic properties. Using high-resolution magneto-hydrodynamical simulation…
Models of galaxy formation ultimately aim at reproducing the _observed_ properties of galaxies. We report on work in progress to predict luminosities, colours and morphologies of field objects of various masses through N-body + Smoothed…
We present a multi-modal foundation model for astrophysical galaxy data, designed to map between simulation- and observation-based galactic features. Our encoder-only transformer flexibly ingests scalar quantities (e.g., redshifts, galaxy…
We present a novel graph-based machine learning classifier for identifying the dark matter cosmic web environments of galaxies. Large galaxy surveys offer comprehensive statistical views of how galaxy properties are shaped by large-scale…
We develop a transformer-based conditional generative model for discrete point objects and their properties. We use it to build a model for populating cosmological simulations with gravitationally collapsed structures called dark matter…
The current status of numerical simulations of galaxy formation is reviewed. After a short description of the main numerical simulation techniques, three sample applications illustrate how numerical simulations have provided deeper insight…
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…
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…
Next-generation galaxy surveys promise unprecedented precision in testing gravity at cosmological scales. However, realising this potential requires accurately modelling the non-linear cosmic web. We address this challenge by exploring…
Over the last decades, cosmological simulations of galaxy formation have been instrumental for advancing our understanding of structure and galaxy formation in the Universe. These simulations follow the non-linear evolution of galaxies…