Related papers: Local Two-Sample Testing: A New Tool for Analysing…
This paper deals with two-sample tests for functional time series data, which have become widely available in conjunction with the advent of modern complex observation systems. Here, particular interest is in evaluating whether two sets of…
We use weak gravitational lensing to analyse the dark matter halos around satellite galaxies in galaxy groups in the CFHTLenS dataset. This dataset is derived from the CFHTLS-Wide survey, and encompasses 154 sq. deg of high-quality shape…
Two-point correlation functions (2PCF) are widely used to characterize how points cluster in space. In this work, we study the problem of measuring the 2PCF over a large set of points, restricted to a subset satisfying a property of…
The Local Group of galaxies offer some of the most discriminating tests of models of cosmic structure formation. For example, observations of the Milky Way (MW) and Andromeda satellite populations appear to be in disagreement with N-body…
This paper provides a nonparametric test for the identity of two multivariate continuous distribution functions (d.f.'s) when they differ in locations. The test uses Wilcoxon rank-sum statistics on distances between observations for each of…
We present a demographic analysis of integrated star formation and gas properties for a sample of galaxies representative of the overall population at z~0. This research was undertaken in order to characterise the nature of star formation…
We introduce the localized Lasso, which is suited for learning models that are both interpretable and have a high predictive power in problems with high dimensionality $d$ and small sample size $n$. More specifically, we consider a function…
By combining high-resolution observations from JWST and HST, we have measured the stellar masses, star formation rates (SFRs), and multi-wavelength morphologies of galaxies in the CANDELS fields. Furthermore, based on rest-frame 1 $\mu$m…
We study the local dimensions and local multifractal properties of measures on doubling metric spaces. Our aim is twofold. On one hand, we show that there are plenty of multifractal type measures in all metric spaces which satisfy only mild…
Inspired by the recent remarkable progress in the experimental test of local realism, we report here such a test that achieves an efficiency greater than (78%)^2 for entangled photon pairs separated by 183 m. Further utilizing the…
Strong gravitational lensing by galaxies is a powerful tool for studying cosmology and galaxy structure. The China Space Station Telescope (CSST) will revolutionize this field by discovering up to $\sim$100,000 galaxy-scale strong lenses, a…
Surveys with submillimetre telescopes are revealing large numbers of gravitationally lensed high-redshift sources. I describe how, in practice, these lensed systems could be simultaneously used to estimate the values of cosmological…
The most effective use of data from current and upcoming large scale structure~(LSS) and CMB observations requires the ability to predict the clustering of LSS with very high precision. The Effective Field Theory of Large Scale Structure…
We present HST imaging of eight spectroscopically-confirmed giant arcs, pairs and arclets. These objects have all been extensively studied from the ground and we demonstrate the unique advantages of HST imaging in the study of such features…
It is of great interest to test the equality of the means in two samples of functional data. Past research has predominantly concentrated on low-dimensional functional data, a focus that may not hold up in high-dimensional scenarios. In…
We investigate the transition scale to homogeneity, $R_H$, using as cosmic tracer the spectroscopic sample of blue galaxies from the Sloan Digital Sky Survey (SDSS). Considering the spatial distribution of the galaxy sample we compute the…
Spatial Transcriptomics (ST) provides spatially resolved gene expression profiles within intact tissue architecture, enabling molecular analysis in histological context. However, the high cost, limited throughput, and restricted data…
Deep learning based discriminative methods, being the state-of-the-art machine learning techniques, are ill-suited for learning from lower amounts of data. In this paper, we propose a novel framework, called simultaneous two sample learning…
We present detailed clustering analysis of a large K-band selected local galaxy sample, which is constructed from the 2MASS and the SDSS and consists of $82,486$ galaxies with $10 < K < 13.5$ and $0.01 < z < 0.1$. The two-point correlation…
The amount of collected data in many scientific fields is increasing, all of them requiring a common task: extract knowledge from massive, multi parametric data sets, as rapidly and efficiently possible. This is especially true in astronomy…