Related papers: Comparing simulated Milky Way satellite galaxies w…
Using detailed mock galaxy redshift surveys we investigate to what extent the kinematics of large samples of satellites galaxies extracted from flux-limited surveys can be used to constrain halo masses. Previous host-satellite selection…
We revisit the well known discrepancy between the observed number of Milky Way (MW) dwarf satellite companions and the predicted population of cold dark matter (CDM) sub-halos, in light of the dozen new low luminosity satellites found in…
This paper is a first step towards developing a formalism to optimally extract dark energy information from number counts using multiple cluster observation techniques. We use a Fisher matrix analysis to study the improvements in the joint…
We present a new method for quantifying the abundance of satellites around field galaxies and in groups. The method is designed to work with samples, such as local photometric redshift catalogues, that do not have full spectroscopic…
We present a comparison of three cluster finding algorithms from imaging data using Monte Carlo simulations of clusters embedded in a 25 deg^2 region of Sloan Digital Sky Survey (SDSS) imaging data: the Matched Filter (MF; Postman et al.…
We introduce a new concept -- termed "planarity" -- which aims to quantify planar structure in galaxy satellite systems without recourse to the number or thickness of planes. We use positions and velocities from the Gaia EDR3 to measure…
The number density and correlation function of galaxies are two key quantities to characterize the distribution of the observed galaxy population. High-$z$ spectroscopic surveys, which usually involve complex target selection and are…
Galaxy morphology offers significant insights into the evolutionary pathways and underlying physics of galaxies. As astronomical data grows with surveys such as Euclid and Vera C. Rubin , there is a need for tools to classify and analyze…
We have tested the application to Sloan Digital Sky Survey data of the software package MATCH, which fits color-magnitude diagrams (CMDs) to estimate stellar population parameters and distances. These tests on a set of six globular clusters…
We present a detailed characterization of planes of satellite galaxies in the Milky Way (MW) and M31. For a positional analysis, we introduce an extension to the `4-galaxy-normal density plot' method \citep[][P13]{Pawlowski13}. It finds the…
We have developed a method that maps large astronomical images onto a two-dimensional map and clusters them. A combination of various state-of-the-art machine learning (ML) algorithms is used to develop a fully unsupervised image quality…
Clustering is an essential data mining tool that aims to discover inherent cluster structure in data. As such, the study of clusterability, which evaluates whether data possesses such structure, is an integral part of cluster analysis. Yet,…
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…
Galaxy-scale strong lenses in galaxy clusters provide a unique tool to investigate their inner mass distribution and the sub-halo density profiles in the low-mass regime, which can be compared with the predictions from cosmological…
Galaxy clusters provide a multitude of observational data across wavelengths and their structure and morphology are of considerable interest in cosmology as well as astrophysics. We develop a framework that allows the combination of lensing…
We use \texttt{GRUMPY}, a simple regulator-type model for dwarf galaxy formation and evolution, to forward model the dwarf galaxy satellite population of the Milky Way (MW) using the Caterpillar zoom-in simulation suite. We show that…
Unsupervised machine learning, and in particular data clustering, is a powerful approach for the analysis of datasets and identification of characteristic features occurring throughout a dataset. It is gaining popularity across scientific…
We develop a novel method to explore the galaxy-halo connection using the galaxy imaging surveys by modeling the projected two-point correlation function measured from the galaxies with reasonable photometric redshift measurements. By…
We develop a new method which measures the projected density distribution w_p(r_p)n of photometric galaxies surrounding a set of spectroscopically-identified galaxies, and simultaneously the projected correlation function w_p(r_p) between…
Any successful model of dark matter must explain the diversity of observed Milky Way (MW) satellite density profiles, from very dense ultrafaints to large, low density satellites such as Crater~II that appear to be larger their anticipated…