activity
20122026
most citedThe GALAH Survey: Scientific Motivation

839 citations · 3.6k across the 45 of their papers we have counts for

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Showing 2020Show all

10 papers · 1 filter

astro-ph.SR2020★ 17 cited

The GALAH+ Survey: A New Library of Observed Stellar Spectra Improves Radial Velocities and Hints at Motions within M67

Tomaž Zwitter, Janez Kos, Sven Buder +25

GALAH+ is a magnitude-limited survey of high resolution stellar spectra obtained by the HERMES spectrograph at the Australian Astronomical Observatory. Its third data release provi…

astro-ph.GA2020★ 626 cited

The GALAH+ Survey: Third Data Release

Sven Buder, Sanjib Sharma, Janez Kos +44

The ensemble of chemical element abundance measurements for stars, along with precision distances and orbit properties, provides high-dimensional data to study the evolution of the…

astro-ph.SR2020★ 23 cited

The GALAH survey: Chemical homogeneity of the Orion complex

Janez Kos, Joss Bland-Hawthorn, Sven Buder +17

Due to its proximity, the Orion star forming region is often used as a proxy to study processes related to star formation and to observe young stars in the environment they were bo…

astro-ph.IM2020★ 9 cited

An optimised tiling pattern for multi-object spectroscopic surveys: application to the 4MOST survey

E. Tempel, T. Tuvikene, M. M. Muru +22

Large multi-object spectroscopic surveys require automated algorithms to optimise their observing strategy. One of the most ambitious upcoming spectroscopic surveys is the 4MOST su…

astro-ph.SR2020★ 41 cited

The GALAH Survey: A new constraint on cosmological lithium and Galactic lithium evolution from warm dwarf stars

Xudong Gao, Karin Lind, Anish M. Amarsi +22

Lithium depletion and enrichment in the cosmos is not yet well understood. To help tighten constraints on stellar and Galactic evolution models, we present the largest high-resolut…

astro-ph.SR2020★ 11 cited

The GALAH survey: Characterization of emission-line stars with spectral modelling using autoencoders

Klemen Čotar, Tomaž Zwitter, Gregor Traven +11

We present a neural network autoencoder structure that is able to extract essential latent spectral features from observed spectra and then reconstruct a spectrum from those featur…