Related papers: J-PLUS: Support Vector Regression to Measure Stell…
Transmission spectroscopy is still the preferred characterization technique for exoplanet atmospheres, although it presents unique challenges that translate into characterization bottlenecks when robust mitigation strategies are missing.…
We present a synthetic galaxy lightcone specially designed for narrow-band optical photometric surveys. To reduce time-discreteness effects, unlike previous works, we directly include the lightcone construction in the \texttt{L-Galaxies}…
This project outlines the complete development of a variable star classification algorithm methodology. With the advent of Big-Data in astronomy, professional astronomers are left with the problem of how to manage large amounts of data, and…
We present the photometric calibration of the twelve optical passbands for the Javalambre Photometric Local Universe Survey (J-PLUS) third data release (DR3), comprising 1642 pointings of two square degrees each. We selected nearly 1.5…
We use data from the Transiting Exoplanet Survey Satellite (TESS) to search for, and set limits on, optical to near-infrared photometric variability of the well-vetted, candidate James Webb Space Telescope (JWST) spectrophotometric…
The Southern Photometric Local Universe Survey (S-PLUS) is imaging ~9300 deg^2 of the celestial sphere in twelve optical bands using a dedicated 0.8 m robotic telescope, the T80-South, at the Cerro Tololo Inter-American Observatory, Chile.…
The SuperCLuster Assisted Shear Survey (SuperCLASS) is a legacy programme using the e-MERLIN interferometric array. The aim is to observe the sky at L-band (1.4 GHz) to a r.m.s. of 7 uJy per beam over an area of ~1 square degree centred on…
Variable star analysis and classification is an important task in the understanding of stellar features and processes. While historically classifications have been done manually by highly skilled experts, the recent and rapid expansion in…
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 becoming a significant challenge. We use data from the…
The JVAS (Jodrell Bank-VLA Astrometric Survey) and CLASS (Cosmic Lens All-Sky Survey) are well-defined surveys containing about ten thousand flat-spectrum radio sources. For many reasons, flat-spectrum radio sources are particularly…
Due to the ever-expanding volume of observed spectroscopic data from surveys such as SDSS and LAMOST, it has become important to apply artificial intelligence (AI) techniques for analysing stellar spectra to solve spectral classification…
Context. We use the Southern Photometric Local Universe Survey (S-PLUS) Fourth Data Release (DR4) to identify and classify H$\alpha$-excess point sources in the Southern Sky, combining photometric data from 12 S-PLUS filters with machine…
Spectral characterization of sub-stellar companions is essential to understand their composition and formation processes. However, the large contrast ratio of the brightness of each object to that of its parent star limits our ability to…
The James Webb Space Telescope (JWST) is predicted to make great advances in the field of exoplanet atmospheres. Its 25 m2 mirror means that it can reach unprecedented levels of precision in observations of transit spectra, and can thus…
We outline the prospects for performing pioneering radio weak gravitational lensing analyses using observations from a potential forthcoming JVLA Sky Survey program. A large-scale survey with the JVLA can offer interesting and unique…
The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) will soon start to scan thousands of square degrees of the northern extragalactic sky with a unique set of $56$ optical filters from a dedicated $2.55$m…
Our multi-view metric learning framework enables robust characterization of star categories by directly learning to discriminate in a multi-faceted feature space, thus, eliminating the need to combine feature representations prior to…
The impending Javalambre Physics of the accelerating universe Astrophysical Survey (J-PAS) will be the first wide-field survey of $\gtrsim$ 8500 deg$^2$ to reach the `stage IV' category. Because of the redshift resolution afforded by 54…
Machine learning enables rapid estimation of material parameters in solar cells via neural-network-based surrogate models. However, the reliability of extracted parameters depends on underlying assumptions such as the choice of…
The advent of large-scale surveys requires efficient ML techniques to exploit the information of massive datasets. We present OJALA, a transformer-based autoregressive foundation model designed to simultaneously classify astronomical…