5 papers
Microlensify: a Transformer Based Machine Learning Classifier for Microlensing Events Trained on TESS Light Curves
Atousa Kalantari, Somayeh Khakpash, Sedighe Sajadian +3
Microlensing can reveal populations of faint compact objects that are otherwise difficult to detect. Depending on their design, all-sky surveys have the potential to search for the…
COSMOS-Web: Estimating Physical Parameters of Galaxies Using Self-Organizing Maps
Fatemeh Abedini, Ghassem Gozaliasl, Akram Hasani Zonoozi +38
The COSMOS-Web survey, with its unparalleled combination of multiband data, notably, near-infrared imaging from JWST's NIRCam (F115W, F150W, F277W, and F444W), provides a transform…
Physical properties of galaxies and the UV Luminosity Function from to in COSMOS-Web
Maximilien Franco, Caitlin M. Casey, Hollis B. Akins +37
We present measurements of the rest-frame ultraviolet luminosity function (UVLF) in three redshift bins over -14 from the JWST COSMOS-Web survey. Our samples, selected us…
Leveraging Machine Learning for Accurate and Fast Stellar Mass Estimation of Galaxies
Vahid Asadi, Akram Hasani Zonoozi, Hosein Haghi +4
Unveiling the evolutionary history of galaxies necessitates a precise understanding of their physical properties. Traditionally, astronomers achieve this through spectral energy di…
COSMOS Web: Morphological quenching and size-mass evolution of brightest group galaxies from z = 3.7
Ghassem Gozaliasl, Lilan Yang, Jeyhan Kartaltepe +47
We present a comprehensive study of the structural evolution of Brightest Group Galaxies (BGGs) from redshift to using the \textit{James Webb Space Telesc…