Related papers: Local Two-Sample Testing: A New Tool for Analysing…
We examine a general framework for visualizing datasets of high (> 2) dimensionality, and demonstrate it using the morphology of galaxies at moderate redshifts. The distributions of various populations of such galaxies are examined in a…
In recent years the census of known satellites in our own Local Group and in nearby galaxy groups has increased substantially due to sensitive wide-area surveys. In the Local Group these surveys have more than doubled its known galaxy…
Strong lensing has developed into an important astrophysical tool for probing both cosmology and galaxies (their structure, formation, and evolution). Using the gravitational lensing theory and cluster mass distribution model, we try to…
In many scientific applications, the target probability distribution cannot be evaluated in closed form or sampled from directly. Instead, it can often be decomposed into multiple components, some of which are accessible only through…
Exploiting a sample of 680 star-forming galaxies from the Padova-Millennium GalaxyGroup Catalog (PM2GC) (Calvi et al. 2011) in the range 0.038<z<0.104, we present a detailed analysis of the Star Formation Rate (SFR)-stellar mass (M_star)…
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…
This thesis investigates the evolution of galaxies in diverse environments, utilizing Sloan Digital Sky Survey (SDSS) data to explore the impact of environmental richness on central and satellite galaxies across stellar mass ranges,…
This is a model-independent analysis that investigates the statistical isotropy in the Local Universe using the ALFALFA survey data ($0 < z < 0.06$). We investigate the angular distribution of HI extra-galactic sources from the ALFALFA…
A two-sample hypothesis test is a statistical procedure used to determine whether the distributions generating two samples are identical. We consider the two-sample testing problem in a new scenario where the sample measurements (or sample…
We propose a two-sample testing procedure based on learned deep neural network representations. To this end, we define two test statistics that perform an asymptotic location test on data samples mapped onto a hidden layer. The tests are…
We present a self-consistent framework to perform the wavelet analysis of two-dimensional statistical distributions. The analysis targets the 2D probability density function (p.d.f.) of an input sample, in which each object is characterized…
Modern data empower observers to describe galaxies as the spatially and biographically complex objects they are. We illustrate this through case studies of four, $z\sim1.3$ systems based on deep, spatially resolved, 17-band + G102 + G141…
We develop a new empirical methodology to study the relation between the stellar mass of galaxies and the mass of their host subhaloes. Our approach is similar to abundance matching, and is based on assigning a stellar mass to each subhalo…
Hypothesis testing is a statistical inference approach used to determine whether data supports a specific hypothesis. An important type is the two-sample test, which evaluates whether two sets of data points are from identical…
We present new multi-wavelength scaling relations between the neutral hydrogen content (HI) and the stellar properties of nearby galaxies selected from the HI Parkes All-Sky Survey (HIPASS). We use these new scaling relations to investigate…
We propose a two-sample test for the means of high-dimensional data when the data dimension is much larger than the sample size. Hotelling's classical $T^2$ test does not work for this "large $p$, small $n$" situation. The proposed test…
In spite of considerable practical importance, current algorithmic fairness literature lacks technical methods to account for underlying geographic dependency while evaluating or mitigating bias issues for spatial data. We initiate the…
Machine learning and deep learning have been used extensively to classify physical surfaces through images and time-series contact data. However, these methods rely on human expertise and entail the time-consuming processes of data and…
The abundance of neutral hydrogen (HI) in satellite galaxies in the Local Group is important for studying the formation history of our Local Group. In this work, we generated mock HI satellite galaxies in the Local Group using the high mass…
We propose novel methodology for testing equality of model parameters between two high-dimensional populations. The technique is very general and applicable to a wide range of models. The method is based on sample splitting: the data is…