Related papers: YOLO-CL: Galaxy cluster detection in the SDSS with…
Based on the photometric redshift catalog of Zou H. et al. (2019), we apply a fast clustering algorithm to identify 540,432 galaxy clusters at $z\lesssim1$ in the DESI legacy imaging surveys, which cover a sky area of about 20,000 deg$^2$.…
The third data release of the LOFAR Two-metre Sky Survey provides an unprecedented view of the northern sky at 144 MHz. While compact sources can be efficiently identified with automated software packages, the detection of diffuse radio…
Object detection and classification are crucial tasks across various application domains, particularly in the development of safe and reliable Advanced Driver Assistance Systems (ADAS). Existing deep learning-based methods such as…
Mergers are an important aspect of galaxy formation and evolution. We aim to test whether deep learning techniques can be used to reproduce visual classification of observations, physical classification of simulations and highlight any…
We present a new algorithm, CAMIRA, to identify clusters of galaxies in wide-field imaging survey data. We base our algorithm on the stellar population synthesis model to predict colours of red-sequence galaxies at a given redshift for an…
Galaxy groups are essential for studying the distribution of matter on a large scale in redshift surveys and for deciphering the link between galaxy traits and their associated halos. In this work, we propose a widely applicable method for…
Driven by the ever-increasing requirements of autonomous vehicles, such as traffic monitoring and driving assistant, deep learning-based object detection (DL-OD) has been increasingly attractive in intelligent transportation systems.…
This is the first in a series of papers on the weak lensing effect caused by clusters of galaxies in Sloan Digital Sky Survey. The photometrically selected cluster sample, known as MaxBCG, includes ~130,000 objects between redshift 0.1 and…
We present a new method for photometering objects in galaxy clusters. We introduce a mode-filtering technique for removing spatially variable backgrounds, improving both detection and photometric accuracy (roughly halving the scatter in the…
In this work we present combined optical and X-ray cluster detection methods in an area near the North Galactic Pole area, previously covered by the SDSS and 2dF optical surveys. The same area has been covered by shallow ($\sim 1.8$…
We present some early results from our deep imaging survey of galaxy clusters intended to detect and study intracluster light (ICL). From our observations to date, we find that ICL is common in galaxy clusters, and that substructure in the…
We present a new algorithm to detect inter-cluster galaxy filaments based upon the assumption that the orientations of constituent galaxies along such filaments are non-isotropic. We apply the algorithm to the 2dF Galaxy Redshift Survey…
Merging galaxy clusters offer a unique probe of dark matter (DM) interactions through the spatial offsets between galaxies, the intracluster medium, and the DM halo. Systems that are binary, near the plane of the sky, and observed shortly…
Object localization in satellite imagery is particularly challenging due to the high variability of objects, low spatial resolution, and interference from noise and dominant features such as clouds and city lights. In this research, we…
We present a machine-learning approach for estimating galaxy cluster masses from Chandra mock images. We utilize a Convolutional Neural Network (CNN), a deep machine learning tool commonly used in image recognition tasks. The CNN is trained…
The Blanco Cosmology Survey is 4-band (griz) optical-imaging survey that covers ~80 square degrees of the southern sky. The survey consists of two fields roughly centered at (RA,DEC) = (23h,-55d) and (5h30m,-53d) with imaging designed to…
We report on the first results of an imaging survey to detect strong gravitational lensing targeting the richest clusters selected from the photometric data of the Sloan Digital Sky Survey (SDSS) with follow-up deep imaging observations…
Dyslexia affects reading and writing skills across many languages. This work describes a new application of YOLO-based object detection to isolate and label handwriting patterns (Normal, Reversal, Corrected) within synthetic images that…
Galaxy clusters identified from the Sunyaev Zel'dovich (SZ) effect are a key ingredient in multi-wavelength cluster-based cosmology. We present a comparison between two methods of cluster identification: the standard Matched Filter (MF)…
I review recent progress in understanding and modeling galaxy clustering in cosmological simulations, with emphasis on models based on high-resolution dissipationless simulations. During the last decade, significant advances in our…