Related papers: Topological approach to void finding applied to th…
We investigate the cosmological constraints from the void-lensing cross-correlation assuming the $w$CDM model for the Chinese Space Station Survey Telescope (CSST) photometric survey. Using Jiutian simulations, we construct a mock galaxy…
Cosmic voids, the largest underdense regions in the Universe, provide unique laboratories for studying galaxy formation and constitute powerful probes of cosmology. Recent work has shown that individual galaxy bias (b_i), which quantifies…
We have completed a pilot survey imaging 15 SDSS selected void galaxies in HI in local (d=50 to 100 Mpc) voids. This small sample makes up a surprisingly interesting collection of galaxies, consisting of galaxies with asymmetric and…
Detecting the large-scale structure of the Universe based on the galaxy distribution and characterising its components is of fundamental importance in astrophysics but is also a difficult task to achieve. Wide-area spectroscopic redshift…
We characterize structures such as monotonicity, convexity, and modality in smooth regression curves using persistent homology. Persistent homology is a key tool in topological data analysis that detects higher-dimensional topological…
We apply the Alcock-Paczynski (AP) test to the stacked voids identified using the large-scale structure galaxy catalog from the Baryon Oscillation Spectroscopic Survey (BOSS). This galaxy catalog is part of the Sloan Digital Sky Survey…
We present the Smoothed Hessian Major Axis Filament Finder (SHMAFF), an algorithm that uses the eigenvectors of the Hessian matrix of the smoothed galaxy distribution to identify individual filamentary structures. Filaments are traced along…
Persistent homology has been devised as a promising tool for the topological simplification of complex data. However, it is computationally intractable for large data sets. In this work, we introduce multiresolution persistent homology for…
Topological correctness is critical for segmentation of tubular structures, which pervade in biomedical images. Existing topological segmentation loss functions are primarily based on the persistent homology of the image. They match the…
We present catalogues of voids for the SDSS DR7 redshift survey and for Millennium I simulation mock data. We aim to compare the observations with simulations based on a $\Lambda$CDM model and a semi-analytic galaxy formation model. We use…
We use high-resolution N-body simulations, combined with a halo occupation model of galaxy bias, to investigate voids in the galaxy distribution. Our goal is to address the 'void phenomenon' of Peebles (2001), which presents the observed…
Using the Parkes radio telescope, we study the 21cm neutral hydrogen (HI) properties of a sample of galaxies with redshifts z<0.13 extracted from the optical 2dF Galaxy Redshift Survey (2dFGRS). Galaxies at 0.04<z<0.13 are studied using new…
We describe an algorithm to detect voids in galaxy redshift surveys. The method is based on the void finder algorithm of El-Ad & Piran. We apply a series of tests to determine how accurately we are able to recover the volumes of voids using…
We measure the star formation properties of two large samples of galaxies from the SDSS in large-scale cosmic voids on time scales of 10 Myr and 100 Myr, using H$\alpha$ emission line strengths and GALEX FUV fluxes, respectively. The first…
We introduce a new 2-D hexagon technique to probe the topological structure of the universe, in which we map regions of the sky with high and low galaxy densities onto a 2-D lattice of hexagon unit cells, We define filled cells as…
We present a purely geometrical method for probing the expansion history of the Universe from the observation of the shape of stacked voids in spectroscopic redshift surveys. Our method is an Alcock-Paczynski (AP) test based on the average…
We consider the task of topology discovery of sparse random graphs using end-to-end random measurements (e.g., delay) between a subset of nodes, referred to as the participants. The rest of the nodes are hidden, and do not provide any…
Cosmic voids are underdense regions within the large-scale structure of the Universe, spanning a wide range of physical scales - from a few megaparsecs (Mpc) to the largest observable structures. Their distinctive properties make them…
The large-scale structure (LSS) of the Universe is comprised of galaxy filaments, tendrils, and voids. The majority of the Universe's volume is taken up by these voids, which exist as underdense, but not empty, regions. The galaxies found…
Using a set of $\Lambda$CDM simulations of cosmic structure formation, we study the evolving connectivity and changing topological structure of the cosmic web using state-of-the-art tools of multiscale topological data analysis (TDA). We…