Related papers: Organised Randoms: Learning and correcting for sys…
The DEEP2 project will obtain redshifts for ~60,000 galaxies between z~0.7-1.5 in a comoving volume of 7 10^6 Mpc/h^3 for an LCDM universe. The survey will map four separate 2 by 0.5 degree strips of the sky. To study the expected…
Globular clusters (GCs) are sensitive tracers of galaxy assembly histories but interpreting the information they encode is challenging because mergers are thought to promote both the formation and disruption of GCs. We use simulations with…
We investigate the effects of potential sources of systematic error on the angular and photometric redshift, z_phot, distributions of a sample of redshift 0.4 < z < 0.7 massive galaxies whose selection matches that of the Baryon Oscillation…
We present the joint modelling of weak-lensing and count measurements of the galaxy clusters detected with the AMICO code, in the fourth data release of the Kilo Degree Survey (KiDS-1000). The analysed sample comprises about 8000 clusters,…
This paper demonstrates a novel and efficient unsupervised clustering method with the combination of a Self-Organising Map (SOM) and a convolutional autoencoder. The rapidly increasing volume of radio-astronomical data has increased demand…
Galaxy populations show bimodality in a variety of properties: stellar mass, colour, specific star-formation rate, size, and S\'ersic index. These parameters are our feature space. We use an existing sample of 7556 galaxies from the Galaxy…
The weak gravitational lensing distortion of distant galaxy images (defined as sources) probes the projected large-scale matter distribution in the Universe. To improve quality in the 3D mass mapping using 3D-lensing, we combine the lensing…
Using N-body simulations and galaxy formation models, we study the galaxy stellar mass correlation and the two-point auto-correlation. The simulations are run with cosmological parameters from the WMAP first, third and seven year results,…
Context: The huge and still rapidly growing amount of galaxies in modern sky surveys raises the need of an automated and objective classification method. Unsupervised learning algorithms are of particular interest, since they discover…
Galaxy redshift surveys are subject to incompleteness and inhomogeneous sampling due to the various constraints inherent to spectroscopic observations. This can introduce systematic errors on the summary statistics of interest, which need…
We develop a novel data-driven method for generating synthetic optical observations of galaxy clusters. In cluster weak lensing, the interplay between analysis choices and systematic effects related to source galaxy selection, shape…
Context. Weak gravitational lensing offers a powerful method to investigate the projected matter density distribution within galaxy clusters, granting crucial insights into the broader landscape of dark matter on cluster scales. Aims. In…
The angular distribution of galaxies encodes a wealth of information about large scale structure. Ultimately, the Sloan Digital Sky Survey (SDSS) will record the angular positions of order 10^8 galaxies in five bands, adding significantly…
As the next generation of large galaxy surveys come online, it is becoming increasingly important to develop and understand the machine learning tools that analyze big astronomical data. Neural networks are powerful and capable of probing…
We propose that observations of super-massive galaxies contain cosmological constraining power similar to conventional cluster cosmology, and we provide promising indications that the associated systematic errors are comparably easier to…
I review here past and present research on clusters and groups of galaxies within the Sloan Digital Sky Survey (SDSS). In particular, I discuss the C4 algorithm which is designed to search for clusters within a 7-dimensional data-space,…
We present an optimisation method for the assignment of photometric galaxies into a chosen set of redshift bins. This is achieved by combining simulated annealing, an optimisation algorithm inspired by solid-state physics, with an…
In this work we present the galaxy clustering measurements of the two DES lens galaxy samples: a magnitude-limited sample optimized for the measurement of cosmological parameters, MagLim, and a sample of luminous red galaxies selected with…
We present a modern machine learning approach for cluster dynamical mass measurements that is a factor of two improvement over using a conventional scaling relation. Different methods are tested against a mock cluster catalog constructed…
We present an investigation into the effects of survey systematics such as varying depth, point spread function (PSF) size, and extinction on the galaxy selection and correlation in photometric, multi-epoch, wide area surveys. We take the…