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We demonstrate that generative deep learning can translate galaxy observations across ultraviolet, visible, and infrared photometric bands. Leveraging mock observations from the Illustris simulations, we develop and validate a supervised…

Instrumentation and Methods for Astrophysics · Physics 2025-01-28 Youssef Zaazou , Alex Bihlo , Terrence S. Tricco

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…

Instrumentation and Methods for Astrophysics · Physics 2020-09-16 Florent Sureau , Alexis Lechat , Jean-Luc Starck

Galactic all-sky maps at very disparate frequencies, like in the radio and $\gamma$-ray regime, show similar morphological structures. This mutual information reflects the imprint of the various physical components of the interstellar…

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,…

Instrumentation and Methods for Astrophysics · Physics 2017-07-12 Joana Frontera-Pons , Florent Sureau , Jerome Bobin , Emeric Le Floc'h

Strong gravitational lenses are a rare and instructive type of astronomical object. Identification has long relied on serendipity, but different strategies -- such as mixed spectroscopy of multiple galaxies along the line of sight, machine…

Using single-component fits to SDSS/UKIDSS images of galaxies in the G09 region of the GAMA survey we study radial colour gradients across the galaxy population. We use the multiwavelength information provided by MegaMorph analysis of…

Galaxies can be described by features of their optical spectra such as oxygen emission lines, or morphological features such as spiral arms. Although spectroscopy provides a rich description of the physical processes that govern galaxy…

Instrumentation and Methods for Astrophysics · Physics 2020-12-01 John F. Wu , J. E. G. Peek

With the advent of new spectroscopic surveys from ground and space, observing up to hundreds of millions of galaxies, spectra classification will become overwhelming for standard analysis techniques. To prepare for this challenge, we…

Astrophysics of Galaxies · Physics 2022-06-08 Fucheng Zhong , Rui Li , Nicola R. Napolitano

In this work we explore the possibility of applying machine learning methods designed for one-dimensional problems to the task of galaxy image classification. The algorithms used for image classification typically rely on multiple costly…

Astrophysics of Galaxies · Physics 2022-02-23 F. Tarsitano , C. Bruderer , K. Schawinski , W. G. Hartley

Classification will be an important first step for upcoming surveys that will detect billions of new sources such as LSST and Euclid, as well as DESI, 4MOST and MOONS. The application of traditional methods of model fitting and…

Astrophysics of Galaxies · Physics 2020-01-29 Crispin Logan , Sotiria Fotopoulou

A fundamental bimodality of galaxies in the local Universe is apparent in many of the features used to describe them. Multiple sub-populations exist within this framework, each representing galaxies following distinct evolutionary pathways.…

Morphological classification is a key piece of information to define samples of galaxies aiming to study the large-scale structure of the universe. In essence, the challenge is to build up a robust methodology to perform a reliable…

Instrumentation and Methods for Astrophysics · Physics 2019-11-05 P. H. Barchi , R. R. de Carvalho , R. R. Rosa , R. Sautter , M. Soares-Santos , B. A. D. Marques , E. Clua , T. S. Gonçalves , C. de Sá-Freitas , T. C. Moura

A heuristic greedy algorithm is developed for efficiently tiling spatially dense redshift surveys. In its first application to the Galaxy and Mass Assembly (GAMA) redshift survey we find it rapidly improves the spatial uniformity of our…

Stellar astrophysics relies on diverse observational modalities-primarily photometric light curves and spectroscopic data from which fundamental stellar properties are inferred. While machine learning (ML) has advanced analysis within…

Solar and Stellar Astrophysics · Physics 2025-10-07 Ilay Kamai , Alex M. Bronstein , Hagai B. Perets

Intrinsic galaxy alignments are a source of bias for weak lensing measurements as well as a tool for understanding galaxy formation and evolution. In this work, we measure the alignment of shapes of satellite galaxies, in galaxy groups,…

We examine a general framework for visualizing datasets of high (> 2) dimensionality, and demonstrate it using the morphology of galaxies at moderate redshifts. The distributions of various populations of such galaxies are examined in a…

Astrophysics · Physics 2007-05-23 A. Naim , K. U. Ratnatunga , R. E. Griffiths

Mapping Nearby Galaxies at Apache Point Observatory (MaNGA), one of three core programs in the Sloan Digital Sky Survey-IV (SDSS-IV), is an integral-field spectroscopic (IFS) survey of roughly 10,000 nearby galaxies. It employs dithered…

The star formation history (SFH) of galaxies allow us to investigate when galaxies formed their stars and assembled their mass. We can constrain the SFH with high level of precision from galaxies with resolved stellar populations, since we…

Astrophysics of Galaxies · Physics 2019-02-18 Maria Argudo-Fernández , Médéric Boquien , Shiyin Shen , Fangting Yuan , Jun Yin , Ruixiang Chang , Lei Hao

Identifying the counterparts of submillimetre (submm) galaxies (SMGs) in multiwavelength images is a critical step towards building accurate models of the evolution of strongly star-forming galaxies in the early Universe. However, obtaining…

From a purely photometric perspective galaxies are generally decomposed into a bulge+disc system, with bulges being dispersion-dominated and discs rotationally-supported. However, recent observations have demonstrated that such a framework…

Astrophysics of Galaxies · Physics 2024-01-10 Fabio Rigamonti , Massimo Dotti , Stefano Covino , Francesco Haardt , Luca Cortese , Marco Landoni , Ludovica Varisco