Related papers: Cosmological constraints from HSC survey first-yea…
We present cosmological constraints from the analysis of angular power spectra of cosmic shear maps based on data from the first three years of observations by the Dark Energy Survey (DES Y3). Our measurements are based on the…
We utilize the galaxy shape catalogue from the first-year data release of the Subaru Hyper Suprime-cam Survey (HSC) to study the dark matter content of galaxy groups in the Universe using weak lensing. We use galaxy groups from the Galaxy…
We explore the cosmological constraints from cosmic shear using a new way of modelling the non-linear matter correlation functions. The new formalism extends the method of Angulo & White (2010), which manipulates outputs of $N$-body…
The future 21 cm intensity mapping observations constitute a promising way to trace the matter distribution of the Universe and probe cosmology. Here we assess its capability for cosmological constraints using as a case study the BINGO…
We propose a light-weight deep convolutional neural network (CNN) to estimate the cosmological parameters from simulated 3-dimensional dark matter distributions with high accuracy. The training set is based on 465 realizations of a cubic…
Inspired by a new compilation of strong lensing systems, which consist of 204 points in the redshift range $0.0625< z_{l} < 0.958$ for the lens and $0.196< z_{s} < 3.595$ for the source, we constrain three models that generate a late cosmic…
This work, together with its companion paper, Secco and Samuroff et al. (2021), presents the Dark Energy Survey Year 3 cosmic shear measurements and cosmological constraints based on an analysis of over 100 million source galaxies. With the…
Galaxy-scale strong gravitational lenses are valuable objects for a variety of astrophysical and cosmological applications. Strong lensing galaxies are rare, so efficient search methods, such as convolutional neural networks, are often used…
We present two galaxy shape catalogues from the Dark Energy Survey Year 1 data set, covering 1500 square degrees with a median redshift of $0.59$. The catalogues cover two main fields: Stripe 82, and an area overlapping the South Pole…
We perform a cosmic shear analysis of HSC survey first-year data (HSC-Y1) using Complete Orthogonal Sets of E/B-Integrals (COSEBIs) to derive cosmological constraints. We compute E/B-mode COSEBIs from cosmic shear two-point correlation…
We apply a novel model based on convolutional neural networks (CNNs) to identify gravitationally-lensed galaxies in multi-band imaging of the Hyper Suprime Cam Subaru Strategic Program (HSC-SSP) Survey. The trained model is applied to a…
We compute the constraints on a ``standard'' 10 parameter cold dark matter (CDM) model from the most recent CMB and data and other observations, exploring 30 million discrete models and two continuous parameters. Our parameters are the…
We demonstrate the potential of Deep Learning methods for measurements of cosmological parameters from density fields, focusing on the extraction of non-Gaussian information. We consider weak lensing mass maps as our dataset. We aim for our…
We present results of weak lensing cluster counts obtained from 11 sq.deg SuprimeCam data. Although the area is much smaller than previous work dealing with weak lensing peak statistics, the number density of galaxies usable for weak…
We use a suite of simulated images based on Year 1 of the Dark Energy Survey to explore the impact of galaxy neighbours on shape measurement and shear cosmology. The hoopoe image simulations include realistic blending, galaxy positions, and…
We measure the clustering of DES Year 1 galaxies that are intended to be combined with weak lensing samples in order to produce precise cosmological constraints from the joint analysis of large-scale structure and lensing correlations.…
Focusing on the well motivated aperture mass statistics $\Map$, we study the possibility of constraining cosmological parameters using future space based SNAP class weak lensing missions. Using completely analytical results we construct the…
We perform an analysis of two-point galaxy clustering and galaxy bias using Subaru Hyper-Suprime Cam (HSC) data taken jointly by the Subaru Strategic Program and the University of Hawaii in the COSMOS field. The depth of the data is similar…
Data-driven approaches using deep learning are emerging as powerful techniques to extract non-Gaussian information from cosmological large-scale structure. This work presents the first simulation-based inference (SBI) pipeline that combines…
Number counts of galaxies are re-analyzed using a semi-analytic model (SAM) of galaxy formation based on the hierarchical clustering scenario. Faint galaxies in the Subaru Deep Field (SDF) and the Hubble Deep Field (HDF) are compared with…