Related papers: Galaxy Light profile neural Networks (GaLNets). II…
Next generation large sky surveys will observe up to billions of galaxies for which basic structural parameters are needed to study their evolution. This is a challenging task that, for ground-based observations, is complicated by seeing…
The development of two-dimensional (2D) bulge-to-disk decomposition techniques has shown their advantages over traditional one-dimensional (1D) techniques, especially for galaxies with non-axisymmetric features. However, the full potential…
We perform two-dimensional, Point-Spread-Function-convolved, bulge+disk decompositions in the $g$ and $r$ bandpasses on a sample of 1,123,718 galaxies from the Legacy area of the Sloan Digital Sky Survey Data Release Seven. Four different…
A new method for spectroscopic bulge-disc decomposition is presented, in which the spatial light profile in a two-dimensional spectrum is decomposed wavelength-by-wavelength into bulge and disc components, allowing separate one-dimensional…
Characterizing and accurately decomposing galaxies into structural components, such as bulges and disks, is essential for understanding galaxy formation and evolution, particularly at high redshift, where galaxies are compact and faint.…
We present a set of bulge-disk decompositions for a sample of 71,825 SDSS main-sample galaxies in the redshift range 0.003<z<0.05. We have fit each galaxy with either a de Vaucouleurs ('classical') or an exponential ('pseudo-') bulge and an…
Galaxy photometric redshift (photo-$z$) is crucial in cosmological studies, such as weak gravitational lensing and galaxy angular clustering measurements. In this work, we try to extract photo-$z$ information and construct its probability…
We present a deep learning model to predict the r-band bulge-to-total light ratio (B/T) of nearby galaxies using their multi-band JPEG images alone. Our Convolutional Neural Network (CNN) based regression model is trained on a large sample…
We present a two-dimensional (2-D) fitting algorithm (GALFIT, Version 3) with new capabilities to study the structural components of galaxies and other astronomical objects in digital images. Our technique improves on previous 2-D fitting…
The accuracy of galaxy photometric redshift (photo-$z$) can significantly affect the analysis of weak gravitational lensing measurements, especially for future high-precision surveys. In this work, we try to extract photo-$z$ information…
We measure galaxy structural properties and colour gradients using HST images to trace the evolution of galaxy components. We jointly fit 3D bulge and disk models to 2505 galaxies in GOODS-South across seven bands (bvizYJH) to IAB = 25.5,…
Recent observations and simulations have shown that a buckled bar in the face-on view can be considered as a combination of a long flat bar and a short round barlens (corresponding to the boxy/peanut bulge in the edge-on view). However, the…
Bulge-disc decomposition is a valuable tool for understanding galaxies. However, achieving robust measurements of component properties is difficult, even with high quality imaging, and it becomes even more so with the imaging typical of…
In the era of large sky surveys, photometric redshifts (photo-z) represent crucial information for galaxy evolution and cosmology studies. In this work, we propose a new Machine Learning (ML) tool called Galaxy morphoto-Z with neural…
We present the results of a new and improved study of the morphological and spectral evolution of massive galaxies over the redshift range 1<z<3. Our analysis is based on a bulge-disk decomposition of 396 galaxies with Mstar>10^11 Msolar…
We present results exploring the role that probabilistic deep learning models can play in cosmology from large-scale astronomical surveys through photometric redshift (photo-z) estimation. Photo-z uncertainty estimates are critical for the…
Structural decomposition of galaxies into bulge, disk, and bar components is important to address a number of scientific problems. Measuring bulge, disk, and bar structural parameters will set constraints on the violent and secular…
Because of the 3D nature of galaxies, an algorithm for constructing spatial density distribution models of galaxies on the basis of galaxy images has many advantages over surface density distribution approximations. We present a method 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…
The upcoming imaging survey of the Chinese Space-station Survey Telescope (CSST) will deliver high-resolution imaging of an unprecedented number of galaxies for galaxy studies. To understand CSST's capability, and to support the preparation…