8 citations · 18 across the 8 of their papers we have counts for
8 papers
Unsupervised selection and characterisation of Little Red Dots in JWST surveys with manifold learning
Michele Ginolfi, Filippo Mannucci, Alessandro Marconi +9
Little Red Dots (LRDs) are compact, red sources discovered at high redshift by JWST whose physical nature and selection function remain debated. We investigate whether an unsupervi…
WST -- Wide-field Spectroscopic Telescope: The Next Leap in Wide-field Spectroscopy
Roland Bacon, Olga Bellido, Philippe Dierickx +52
The Wide-field Spectroscopic Telescope (WST) is a concept for a dedicated 12-m spectroscopic survey facility designed to address some of the most important questions in astrophysic…
Milky-Way-like stars in a galaxy core 8 billion years ago revealed by gravitational lensing
Quirino D'Amato, Filippo Mannucci, Alessandro Sonnenfeld +40
The assembly of stellar-dominated cores in elliptical galaxies is key to understanding how cosmic structures evolved. Gravitational lensing offers unique insights into the nature o…
Resolving stellar populations, star formation, and interstellar medium conditions with JWST in a large spiral galaxy at
Eleonora Parlanti, Giulia Tozzi, Natascha M. Förster Schreiber +30
Cosmic noon represents the prime epoch of galaxy assembly, and a sweet spot for observations with the James Webb Telescope (JWST) and ground-based near-IR integral-field unit (IFU)…
Classifying spectra of emission-line regions with neural networks -- An application to integral field spectroscopic data of M33
Caterina Bracci, Francesco Belfiore, Michele Ginolfi +13
Emission-line regions are key to understanding the properties of galaxies, as they trace the exchange of matter and energy between stars and the interstellar medium (ISM). In nearb…
VST-SMASH: the VST Survey of Mass Assembly and Structural Hierarchy
Crescenzo Tortora, Rossella Ragusa, Massimiliano Gatto +21
The VLT Survey Telescope Survey of Mass Assembly and Structural Hierarchy (VST-SMASH) aims to detect tidal features and remnants around very nearby galaxies, a unique and essential…
Inferring redshift and galaxy properties via a multi-task neural net with probabilistic outputs: An application to simulated MOONS spectra
Michele Ginolfi, Filippo Mannucci, Francesco Belfiore +11
The era of large-scale astronomical surveys demands innovative approaches for rapid and accurate analysis of extensive spectral data, and a promising direction in which to address…
Inferring stellar parameters and their uncertainties from high-resolution spectroscopy using invertible neural networks
Nils Candebat, Giuseppe Germano Sacco, Laura Magrini +3
Context: New spectroscopic surveys will increase the number of astronomical objects requiring characterization by over tenfold.. Machine learning tools are required to address this…