Related papers: Enhancing Galaxy Classification with U-Net Variati…
Next generation telescopes, like Euclid, Rubin/LSST, and Roman, will open new windows on the Universe, allowing us to infer physical properties for tens of millions of galaxies. Machine learning methods are increasingly becoming the most…
We present the first James Webb Space Telescope/NIRCam-led determination of $7<z<9$ galaxy properties based on broadband imaging from 0.8 to 5~$\mathrm{\mu m}$ as part of the GLASS-JWST Early Release Science program. This is the deepest…
We apply variational autoencoders to automatically discover galaxy populations using publicly available high-redshift \textit{JWST} spectra without prior classification knowledge. Our unsupervised method identifies distinct astrophysical…
Deconvolution of large survey images with millions of galaxies requires to develop a new generation of methods which can take into account a space variant Point Spread Function (PSF) and have to be at the same time accurate and fast. We…
Variational Autoencoders (VAE) are probabilistic deep generative models underpinned by elegant theory, stable training processes, and meaningful manifold representations. However, they produce blurry images due to a lack of explicit…
(Abridged) We determine the quantitative morphology and star formation properties of galaxies in six nearby X-ray detected, poor groups using multi-object spectroscopy and wide-field R imaging. We measure structural parameters for each…
We analyze 347 galaxies at redshift $4<z<9.5$ using JWST observations from the CEERS program by fitting a two-dimensional parametric model simultaneously to the seven-filter NIRCam images to measure the overall structural parameters and…
We present Swift Ultraviolet Optical Telescope (UVOT) observations of the deep field GOODS-N in four near-UV filters. A catalog of detected galaxies is reported, which will be used to explore galaxy evolution using ultraviolet emission.…
UV slopes ($\beta$) are a powerful diagnostics for galaxies at the Epoch of Reionization, tracing star formation, ISM ionization, and the escape fraction $f_{esc}$ of ionizing photons. Studies at low and intermediate z find a gradual…
Astronomical images are essential for exploring and understanding the universe. Optical telescopes capable of deep observations, such as the Hubble Space Telescope, are heavily oversubscribed in the Astronomical Community. Images also often…
JWST observations have revealed an overabundance of bright galaxies at $z \geq 9$, creating apparent tensions with theoretical predictions within standard $\Lambda$CDM cosmology. We address this challenge using a semi-empirical approach…
To address the challenge of estimating redshifts when only single-band images are available, this study introduces a deep learning model named ViT-MDNz. Leveraging robust statistical priors learned from large-scale data concerning the…
Accelerating deep neural networks (DNNs) has been attracting increasing attention as it can benefit a wide range of applications, e.g., enabling mobile systems with limited computing resources to own powerful visual recognition ability. A…
Bulge-disk (B-D) decomposition is an effective diagnostic to characterize the galaxy morphology and understand its evolution across time. So far, high-quality data have allowed detailed B-D decomposition to redshift below 0.5, with limited…
Modern radio telescope surveys, capable of detecting billions of galaxies in wide-field surveys, have made manual morphological classification impracticable. This applies in particular when the Square Kilometre Array Observatory (SKAO)…
We present a study of seventeen LAEs at redshift 2$<z<$3 gravitationally lensed by massive early-type galaxies (ETGs) at a mean redshift of approximately 0.5. Using a fully Bayesian grid-based technique, we model the gravitational lens mass…
We present results on the morphological and structural evolution of a total of 4265 galaxies observed with JWST at $1.5 < z < 8$ in the JWST CEERS observations that overlap with the CANDELS EGS field. This is the biggest visually classified…
We present a new prospective analysis of deep multi-band imaging with the James Webb Space Telescope (JWST). In this work, we investigate the recovery of high-redshift $5<z<12$ galaxies through extensive image simulations of accepted JWST…
Quantitative morphological classification of galaxies is important for understanding the origin of type frequency and correlations with environment. But galaxy morphological classification is still mainly done visually by dedicated…
With the increasing number of deep multi-wavelength galaxy surveys, the spectral energy distribution (SED) of galaxies has become an invaluable tool for studying the formation of their structures and their evolution. In this context,…