A Robust Study of High-redshift Galaxies: Unsupervised Machine Learning for Characterizing Morphology with JWST up to z∼ 8

C Tohill, SP Bamford, CJ Conselice… - The Astrophysical …, 2024 - iopscience.iop.org
Galaxy morphologies provide valuable insights into their formation processes, tracing the
spatial distribution of ongoing star formation and encoding signatures of dynamical …

Galaxy morphology from z∼ 6 through the lens of JWST

KG Iyer, E Angeloudi, MB Bagley… - Astronomy & …, 2024 - aanda.org
Context. The James Webb Space Telescope's (JWST's) unprecedented combination of
sensitivity, spatial resolution, and infrared coverage has enabled a new era of galaxy …

Galaxy morphological classification in deep-wide surveys via unsupervised machine learning

G Martin, S Kaviraj, A Hocking… - Monthly Notices of the …, 2020 - academic.oup.com
Galaxy morphology is a fundamental quantity, which is essential not only for the full
spectrum of galaxy-evolution studies, but also for a plethora of science in observational …

Unveiling galaxy morphology through an unsupervised-supervised hybrid approach

I Kolesnikov, VM Sampaio… - Monthly Notices of …, 2024 - academic.oup.com
Galaxy morphology offers significant insights into the evolutionary pathways and underlying
physics of galaxies. As astronomical data grow with surveys such as Euclid and Vera C …

Exploring the Morphologies of High Redshift Galaxies with Machine Learning

CB Tohill, S Bamford, C Conselice - Memorie della Società …, 2023 - torrossa.com
The morphology of a galaxy has been shown to encode the evolutionary history and
correlates strongly with physical properties such as stellar mass, star formation rates and …

Deep Learning assessment of galaxy morphology in S-PLUS Data Release 1

CR Bom, A Cortesi, G Lucatelli, LO Dias… - Monthly Notices of …, 2021 - academic.oup.com
The morphological diversity of galaxies is a relevant probe of galaxy evolution and
cosmological structure formation, but the classification of galaxies in large sky surveys is …

USmorph: An Updated Framework of Automatic Classification of Galaxy Morphologies and Its Application to Galaxies in the COSMOS Field

J Song, GW Fang, S Ba, Z Lin, Y Gu… - The Astrophysical …, 2024 - iopscience.iop.org
Morphological classification conveys abundant information on the formation, evolution, and
environment of galaxies. In this work, we refine a two-step galaxy morphological …

Beyond the hubble sequence–exploring galaxy morphology with unsupervised machine learning

TY Cheng, M Huertas-Company… - Monthly Notices of …, 2021 - academic.oup.com
We explore unsupervised machine learning for galaxy morphology analyses using a
combination of feature extraction with a vector-quantized variational autoencoder (VQ-VAE) …

Morphological classification of galaxies with deep learning: comparing 3-way and 4-way CNNs

MK Cavanagh, K Bekki… - Monthly Notices of the …, 2021 - academic.oup.com
Classifying the morphologies of galaxies is an important step in understanding their physical
properties and evolutionary histories. The advent of large-scale surveys has hastened the …

An Early Look at the Evolution of Galaxy Structure and Morphology at z= 3-9 with JWST

J Kartaltepe, C Rose, B Vanderhoof… - American …, 2023 - ui.adsabs.harvard.edu
We present a comprehensive analysis of the evolution of the morphological and structural
properties of a large sample of galaxies at z= 3-9 using the early JWST CEERS NIRCam …