VST-SMASH: the VST Survey of Mass Assembly and Structural Hierarchy
Crescenzo Tortora, Rossella Ragusa, Massimiliano Gatto, Marilena, Spavone, Leslie Hunt, Vincenzo Ripepi, Massimo Dall'Ora, Abdurro'uf,, Francesca Annibali, Maarten Baes, Francesco Michel Concetto Belfiore, Nicola, Bellucco, Micol Bolzonella, Michele Cantiello, Paola Dimauro

TL;DR
VST-SMASH is a comprehensive survey using the VLT Survey Telescope to detect faint tidal features around nearby galaxies, providing critical insights into galaxy formation and hierarchical assembly.
Contribution
It introduces a deep, multi-band optical survey targeting low surface-brightness features in local galaxies within 11 Mpc, aiming to be the definitive resource for stellar streams and tidal remnants.
Findings
Detection of faint tidal features around nearby galaxies
Establishment of a low surface-brightness limit for the survey
Comprehensive catalog of stellar streams in the Local Volume
Abstract
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 diagnostic of the hierarchical nature of galaxy formation. Leveraging optimal sky conditions at ESO's Paranal Observatory, combined with the VST's multi-band optical filters, VST-SMASH aims to be the definitive survey of stellar streams and tidal remnants in the Local Volume, targeting a low surface-brightness limit of 30 mag arcsec in the g and r bands, and 28 mag arcsec in the i band, in a volume-limited sample of local galaxies within 11 Mpc and the Euclid footprint.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMachine Learning in Materials Science · Hydrocarbon exploration and reservoir analysis · Image Processing and 3D Reconstruction
