相关论文: Improved Tomographic Binning of 3x2pt Lens Samples…
Semantic segmentation for medical 3D image stacks enables accurate volumetric reconstructions, computer-aided diagnostics and follow up treatment planning. In this work, we present a novel variant of the Unet model called the NUMSnet that…
We use a contrastive self-supervised learning framework to estimate distances to galaxies from their photometric images. We incorporate data augmentations from computer vision as well as an application-specific augmentation accounting for…
Studies of cosmology, galaxy evolution, and astronomical transients with current and next-generation wide-field imaging surveys like the Rubin Observatory Legacy Survey of Space and Time (LSST) are all critically dependent on estimates of…
Efficient algorithms are being developed to search for strong gravitational lens systems owing to increasing large imaging surveys. Neural networks have been successfully used to discover galaxy-scale lens systems in imaging surveys such as…
Although redshift-space distortions only affect inferred distances and not angles, they still distort the projected angular clustering of galaxy samples selected using redshift dependent quantities. From an Eulerian view-point, this effect…
We introduce a new effective strategy to assign group and cluster membership probabilities $P_{mem}$ to galaxies using photometric redshift information. Large dynamical ranges both in halo mass and cosmic time are considered. The method…
We introduce an ordinal classification algorithm for photometric redshift estimation, which significantly improves the reconstruction of photometric redshift probability density functions (PDFs) for individual galaxies and galaxy samples.…
Galaxies whose images overlap in the focal plane of a telescope, commonly referred to as blends, are often located at different redshifts. Blending introduces a challenge to weak-lensing cosmology probes since such blends are subject to…
In this paper we describe weighting techniques used for the optimal coaddition of CCD frames with differing characteristics. Optimal means maximum signal-to-noise (s/n) for stellar objects. We derive formulae for four applications: 1)…
We introduce a new method for constraining the redshift distribution of a set of galaxies, using weak gravitational lensing shear. Instead of using observed shears and redshifts to constrain cosmological parameters, we ask how well the…
This paper follows series of our works on the applicability of various machine learning methods to the morphological galaxy classification (Vavilova et al., 2021, 2022). We exploited the sample of 315776 SDSS DR9 galaxies with absolute…
The Red-Sequence Cluster Survey (RCS) provides a large and deep photometric catalog of galaxies in the $z'$ and $R_c$ bands for ~90 square degrees of sky, and supplemental $V$ and $B$ data have been obtained for 33.6 deg$^{2}$. We compile a…
Photometric redshift classifiers provide a means of estimating galaxy redshifts from observations using a small number of broad-band filters. However, the accuracy with which redshifts can be determined is sensitive to the star formation…
Neural networks can very effectively perform multidimensional nonlinear classification. However, electronic networks suffer from significant bandwidth limitations due to carrier lifetimes and capacitive coupling. This project investigates…
We study the effect of magnification in the Dark Energy Survey Year 3 analysis of galaxy clustering and galaxy-galaxy lensing, using two different lens samples: a sample of Luminous red galaxies, redMaGiC, and a sample with a…
Forthcoming imaging surveys will potentially increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of tens of millions of galaxies will have to be inspected to identify potential…
Recently, it has been shown that cross-correlating CMB lensing and 3D cosmic shear allows to considerably tighten cosmological parameter constraints. We investigate whether similar improvement can be achieved in a conventional tomographic…
Determining accurate redshift distributions for very large samples of objects has become increasingly important in cosmology. We investigate the impact of extending cross-correlation based redshift distribution recovery methods to include…
We present a galaxy catalog simulator which turns N-body simulations with subhalos into multiband photometric mocks. The simulator assigns galaxy properties to each subhalo to reproduce the observed cluster galaxy halo occupation…
We outline how redshift-space distortions (RSD) can be measured from the angular correlation function w({\theta}), of galaxies selected from photometric surveys. The natural degeneracy between RSD and galaxy bias can be minimized by…