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The intrinsic alignment of galaxies with the large-scale density field is an important astrophysical contaminant in upcoming weak lensing surveys. We present detailed measurements of the galaxy intrinsic alignments and associated…
Weak gravitational lensing (WL) peak statistics capture cosmic non-linear structures and can provide additional cosmological information complementary to cosmic shear two-point correlation analyses. They have been applied to different WL…
The intrinsic alignment (IA) of galaxies acts as a systematic effect in weak lensing measurements and tends to introduce biases. It mimics the gravitational lensing signal which makes it difficult to distinguish it from the true…
Galaxy clusters trace the most massive dark matter haloes, whose shapes and orientations reflect the imprint of the cosmic large-scale tidal field. This paper introduces the Subhalo-based Halo Alignment and Projected Ellipticity (SHAPE)…
Developing analysis pipelines based on statistics beyond two-point functions is critical for extracting a maximal amount of cosmological information from current and upcoming weak lensing surveys. In this paper, we study the impact of the…
Weak gravitational lensing is now established as a powerful method to measure mass fluctuations in the universe. It relies on the measurement of small coherent distortions of the images of background galaxies. Even low-level correlations in…
We explore the capability of deep learning to classify cosmic structures. In cosmological simulations, cosmic volumes are segmented into voids, sheets, filaments and knots, according to the distribution and kinematics of dark matter (DM),…
Generative models aim to learn the distribution of observed data by generating new instances. With the advent of neural networks, deep generative models, including variational autoencoders (VAEs), generative adversarial networks (GANs), and…
Fast and accurate simulations of the non-linear evolution of the cosmic density field are a major component of many cosmological analyses, but the computational time and storage required to run them can be exceedingly large. For this…
We use galaxies from the IllustrisTNG, MassiveBlack-II and Illustris hydrodynamic simulations to investigate the behaviour of large scale galaxy intrinsic alignments. Our analysis spans four redshift slices over the approximate range of…
Emission line galaxies (ELGs), more generally star-forming galaxies, are valuable tracers of large-scale structure and therefore main targets of upcoming wide-area spectroscopic galaxy surveys. We propose a fixed-aperture shape estimator 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…
The intrinsic alignment (IA) of galaxy shapes probes the underlying gravitational tidal field, thus offering cosmological information complementary to galaxy clustering. In this paper, we perform a Fisher forecast to assess the benefit of…
We report results for the alignments of galaxies in the EAGLE and cosmo-OWLS simulations as a function of galaxy separation and halo mass. The combination of these hydro-cosmological simulations enables us to span four orders of magnitude…
Evaluation of gravitational theories by means of cosmological data suffers from the fact that galaxies are biased tracers of dark matter. Current bias models focus primarily on high-density regions, whereas low-density regions carry…
Current and upcoming imaging galaxy surveys are pushing galaxy samples to higher and higher redshifts. This push will be more pronounced for lens galaxies, for which we only need to measure galaxy positions, not shapes. As a result, we will…
Coherent alignments of galaxy shapes, often called "intrinsic alignments" (IA), are the most significant source of astrophysical uncertainty in weak lensing measurements. We develop the tidal alignment model of IA and demonstrate its…
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,…
This paper demonstrates that the stellar masses of galaxies in the Galaxy and Mass Assembly (GAMA) survey, originally derived via stellar population synthesis modelling, can be accurately predicted using only their absolute magnitudes and…
Deep generative models have shown immense potential in generating unseen data that has properties of real data. These models learn complex data-generating distributions starting from a smaller set of latent dimensions. However, generative…