activity
20172023
most cited4MOST: Project overview and information for the First Call for Proposals

311 citations · 670 across the 13 of their papers we have counts for

collaborators

23 papers

astro-ph.SR20229 cited

The Gaia-ESO Survey: Probing the lithium abundances in old metal-rich dwarf stars in the Solar vicinity

M. L. L. Dantas, G. Guiglion, R. Smiljanic +14

We test a scenario in which radial migration could affect the Li abundance pattern of dwarf stars in the solar neighbourhood. This may confirm that the Li abundance in these stars…

astro-ph.GA202249 cited

The Gaia-ESO Survey: Age-chemical-clock relations spatially resolved in the Galactic disc

C. Viscasillas Vázquez, L. Magrini, G. Casali +33

The last decade has seen a revolution in our knowledge of the Galaxy thanks to the Gaia and asteroseismic space missions and the ground-based spectroscopic surveys. To complete thi…

astro-ph.SR202126 cited

The Gaia-ESO survey: Lithium abundances in open cluster Red Clump stars

L. Magrini, R. Smiljanic, E. Franciosini +25

It has recently been suggested that all giant stars with mass below 2 suffer an episode of surface lithium enrichment between the tip of the red giant branch (RGB) and…

astro-ph.GA202155 cited

The Gaia-ESO Survey: Galactic evolution of lithium from iDR6

D. Romano, L. Magrini, S. Randich +31

We exploit the unique characteristics of a sample of open clusters (OCs) and field stars for which high-precision 7Li abundances and stellar parameters are homogeneously derived by…

astro-ph.SR2021

The Gaia-ESO survey: Mixing processes in low-mass stars traced by lithium abundance in cluster and field stars

L. Magrini, N. Lagarde, C. Charbonnel +42

We aim to constrain the mixing processes in low-mass stars by investigating the behaviour of the Li surface abundance after the main sequence. We take advantage of the data from th…

astro-ph.GA2020

The RAdial Velocity Experiment (RAVE): Parameterisation of RAVE spectra based on convolutional neural networks

G. Guiglion, G. Matijevic, A. B. A. Queiroz +22

In the context of large spectroscopic surveys of stars, data-driven methods are key in deducing physical parameters for millions of spectra in a short time. Convolutional neural ne…