Related papers: Local Two-Sample Testing: A New Tool for Analysing…

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…

In this article, we propose some two-sample tests based on ball divergence and investigate their high dimensional behavior. First, we study their behavior for High Dimension, Low Sample Size (HDLSS) data, and under appropriate regularity…

We probe the angular scale of homogeneity in the local Universe using blue galaxies from the SDSS survey as a cosmological tracer. Through the scaled counts in spherical caps, $ \mathcal{N}(<\theta) $, and the fractal correlation dimension,…

We built a multi-wavelength dataset for galaxies from the Local Volume HI Survey (LVHIS), which comprises 82 galaxies. We also select a sub-sample of ten large galaxies for investigating properties in the galactic outskirts. The LVHIS…

Deep neural two-sample tests have recently shown strong power for detecting distributional differences between groups, yet their black-box nature limits interpretability and practical adoption in biomedical analysis. Moreover, most existing…

We propose a class of kernel-based two-sample tests, which aim to determine whether two sets of samples are drawn from the same distribution. Our tests are constructed from kernels parameterized by deep neural nets, trained to maximize test…

In this paper, we discuss a method to conduct a quantitative study of the star formation history (SFH) of Local Group (LG) galaxies using (HST) data. This method has proven to be successful in the analysis of the SFH of the same kind of…

We investigate the impact of local environment on the galaxy stellar mass function (SMF) spanning a wide range of galaxy densities from the field up to dense cores of massive galaxy clusters. Data are drawn from a sample of eight fields…

We propose a class of nonparametric two-sample tests with a cost linear in the sample size. Two tests are given, both based on an ensemble of distances between analytic functions representing each of the distributions. The first test uses…

In modern data analysis, nonparametric measures of discrepancies between random variables are particularly important. The subject is well-studied in the frequentist literature, while the development in the Bayesian setting is limited where…

We present deep H-band surface photometry and analysis of 40 Local Volume galaxies, a sample primarily composed of dwarf irregulars in the Cen A group, obtained using the IRIS2 detector at the 3.9m Anglo-Australian Telescope. We probe to a…

Here I present results from individual galaxy studies and galaxy surveys in the Local Universe with particular emphasis on the spatially resolved properties of neutral hydrogen gas. The 3D nature of the data allows detailed studies of the…

The recent success of generative adversarial networks and variational learning suggests training a classifier network may work well in addressing the classical two-sample problem. Network-based tests have the computational advantage that…

Large-scale structure (LSS) analysis in galaxy surveys is a powerful cosmological probe but is limited by tracer bias, which can obscure underlying information and weaken parameter constraints. Existing methods either model bias or restrict…

We use the scaled counts in spherical caps $\mathcal{N}(<\theta)$ and the fractal correlation dimension $ \mathcal{D}_{2}(\theta) $ procedures to search for a transition scale to homogeneity in the local universe as given by the ALFALFA…

We revisit the mass ratio Rmol between molecular hydrogen (H2) and atomic hydrogen (HI) in different galaxies from a phenomenological and theoretical viewpoint. First, the local H2-mass function (MF) is estimated from the local…

The standard paired-sample testing approach in the multidimensional setting applies multiple univariate tests on the individual features, followed by p-value adjustments. Such an approach suffers when the data carry numerous features. A…

We present a data-driven technique to analyze multifrequency images from upcoming cosmological surveys mapping large sky area. Using full information from the data at the two-point level, our method can simultaneously constrain the…

We present an analysis of the quenching of local observed and simulated galaxies, including an investigation of the dependence of quiescence on both intrinsic and environmental parameters. We apply an advanced machine learning technique…

We present the samples of galaxies and quasars used for DESI 2024 cosmological analyses, drawn from the DESI Data Release 1 (DR1). We describe the construction of large-scale structure (LSS) catalogs from these samples, which include…