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Wide-field cosmological surveys provide hundreds of thousands of spectroscopically confirmed galaxy groups and clusters, valuable for tracing baryonic matter distribution. However, controlling systematics in identifying host dark matter…
We study the clustering of galaxies detected at $i<22.5$ in the Science Verification observations of the Dark Energy Survey (DES). Two-point correlation functions are measured using $2.3\times 10^6$ galaxies over a contiguous 116 deg$^2$…
Aims. We intend to compile a new galaxy group and cluster sample of the latest available SDSS data, adding several parameter for the purpose of studying the supercluster network, galaxy and group evolution, and their connection to the…
We present and implement a probabilistic (Bayesian) method for producing catalogs from images of stellar fields. The method is capable of inferring the number of sources N in the image and can also handle the challenges introduced by noise,…
I compare the mass values obtained with data taken from the Arcminute Microkelvin Imager (AMI) radio interferometer system and from the Planck satellite. The former of these uses a Bayesian analysis pipeline that parameterises a cluster in…
We present a catalogue of galaxy groups and clusters selected using a friends-of-friends algorithm with a dynamic linking length from the 2dF-SDSS and QSO (2SLAQ) luminous red galaxy survey. The linking parameters for the code are chosen…
A new approach to the study of the large-scale stellar cluster distribution in the Galaxy based on two-point correlation techniques is presented. The basic formalism for this method is outlined and its applications are then investigated by…
We derive and implement a full Bayesian large scale structure inference method aiming at precision recovery of the cosmological power spectrum from galaxy redshift surveys. Our approach improves over previous Bayesian methods by performing…
We present Classification of Cluster GAlaxy MEmbers (C$^2$-GaMe), a classification algorithm based on a suite of machine learning models that differentiates galaxies into orbiting, infalling, and background (interloper) populations, using…
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…
Accurately characterizing the redshift distributions of galaxies is essential for analysing deep photometric surveys and testing cosmological models. We present a technique to simultaneously infer redshift distributions and individual…
Future cosmological galaxy surveys such as the Large Synoptic Survey Telescope (LSST) will photometrically observe very large numbers of galaxies. Without spectroscopy, the redshifts required for the analysis of these data will need to be…
Ongoing and future spectroscopic surveys will measure numerous galaxy redshifts within tens of thousands of galaxy clusters. However, the sampling within these clusters will be low, 15 < N < 50 per cluster. With such data, it will be…
We report the discovery of a cluster of galaxies via its weak gravitational lensing effect on background galaxies, the first spectroscopically confirmed cluster to be discovered through its gravitational effects rather than by its…
Aims: We study galaxy clustering and explore the dependence of galaxy properties on the the environment up to a redshift z~1, on the basis of a deep multi-band survey in the Chandra Deep Field South. Methods: We have developed a new method…
We develop a novel statistical strong lensing approach to probe the cosmological parameters by exploiting multiple redshift image systems behind galaxies or galaxy clusters. The method relies on free-form mass inversion of strong lenses and…
We present a study on the variations of the luminosity function of galaxies around clusters in a numerical simulation with semi-analytic galaxies, attempting to detect these variations in the 2dF Galaxy Redshift Survey. We subdivide the…
We introduce a new clustering algorithm, MulGuisin (MGS), that can identify distinct galaxy over-densities using topological information from the galaxy distribution. This algorithm was first introduced in an LHC experiment as a Jet Finder…
We present a large catalog of loose groups of galaxies in the Southern Galactic Hemisphere, selected from the Perseus-Pisces redshift Survey (PPS). Particular care is taken in order to obtain group samples as homogeneous as possible to…
Classically, Bayesian clustering interprets each component of a mixture model as a cluster. The inferred clustering posterior is highly sensitive to any inaccuracies in the kernel within each component. As this kernel is made more flexible,…