摘要：We present a new fully data-driven approach to derive spectro-photometric distances based on artificial neural networks. The method was developed and tested on Sloan Extension for Galactic Understanding and Exploration survey (SEGUE) data and will serve as a reference for the Contributed Data Product SPdist of the William Hershel Telescope Enhanced Area Velocity Explorer (WEAVE) survey. With this method, the relative precision of the distances is of ∼13%. The catalogue of more than 300 000 SEGUE stars for which we have derived spectro-photometric distances is publicly available on the Vizier service of the Centre de Données de Strasbourg. With this 6D catalogue of stars with positions, distances, line-of-sight velocity, and Gaia proper motions, we were able to identify stars belonging to the Cetus stellar stream in the integrals of motion space. Guided by the properties we derived for the Cetus stream from this 6D sample, we searched for additional stars from the blue horizontal and red giant branches in a 5D sample. We find that the Cetus stream and the Palca overdensity are two parts of the same structure, which we therefore propose to rename the Cetus-Palca stream. We find that the Cetus-Palca stream has a stellar mass of '1.5 × 106 M and presents a prominent distance gradient of 15 kpc over the ∼100◦ that it covers on the sky. Additionally, we also report the discovery of a second structure almost parallel to the Cetus stream and covering ∼50◦ of the sky, which could potentially be a stellar stream formed by the tidal disruption of a globular cluster that was orbiting around the Cetus stream progenitor.
关键词：Galaxy: halo;methods: data analysis;galaxies: dwarf;Galaxy: kinematics and dynamics;stars: distances;catalogs
