activity
20162023
most citedThe Galah Survey: Classification and diagnostics with t-SNE reduction of spectral information

77 citations · 216 across the 13 of their papers we have counts for

collaborators

13 papers

astro-ph.GA20231 cited

The Prevalence of the -bimodality: First JWST -abundance Results in M31

David L. Nidever, Karoline Gilbert, Erik Tollerud +8

We present initial results from our JWST NIRSpec program to study the -abundances in the M31 disk. The Milky Way has two chemically-defined disks, the low- and high- disks…

astro-ph.GA2023

Disentangling Stellar Age Estimates from Galactic Chemodynamical Evolution

Jeff Shen, Joshua S. Speagle, J. Ted Mackereth +2

Stellar ages are key for determining the formation history of the Milky Way, but are difficult to measure precisely. Furthermore, methods that use chemical abundances to infer ages…

astro-ph.GA20236 cited

Spatial metallicity variations of mono-temperature stellar populations revealed by early-type stars in LAMOST

Chun Wang, Haibo Yuan, Maosheng Xiang +3

We investigate the radial metallicity gradients and azimuthal metallicity distributions on the Galactocentric -- plane using mono-temperature stellar populations selected fro…

astro-ph.SR20237 cited

Ba-enhanced dwarf and subgiant stars in the LAMOST Galactic surveys

Meng Zhang, Maosheng Xiang, Hua-Wei Zhang +3

Ba-enhanced stars are interesting probes of stellar astrophysics and Galactic formation history. In this work, we investigate the chemistry and kinematics for a large sample of Ba-…

astro-ph.GA202262 cited

The Stellar Halo of the Galaxy is Tilted & Doubly Broken

Jiwon Jesse Han, Charlie Conroy, Benjamin D. Johnson +7

Modern Galactic surveys have revealed an ancient merger that dominates the stellar halo of our Galaxy (\textit{Gaia}-Sausage-Enceladus, GSE). Using chemical abundances and kinemati…

astro-ph.CO2022

An Unsupervised Learning Approach for Quasar Continuum Prediction

Zechang Sun, Yuan-Sen Ting, Zheng Cai

Modeling quasar spectra is a fundamental task in astrophysics as quasars are the tell-tale sign of cosmic evolution. We introduce a novel unsupervised learning algorithm, Quasar Fa…