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Synthetic Gaia DR3 Surveys from the FIRE Cosmological Simulations of Milky Way-mass Galaxies
Tri Nguyen, Xiaowei Ou, Nondh Panithanpaisal, Nora Shipp, Lina Necib, Robyn Sanderson and Andrew Wetzel The Astrophysical Journal 966(1) 108 (2024) https://doi.org/10.3847/1538-4357/ad35ba
Applying machine learning to Galactic Archaeology: how well can we recover the origin of stars in Milky Way-like galaxies?
Andrea Sante, Andreea S Font, Sandra Ortega-Martorell, Ivan Olier and Ian G McCarthy Monthly Notices of the Royal Astronomical Society 531(4) 4363 (2024) https://doi.org/10.1093/mnras/stae1398
Generating synthetic star catalogs from simulated data
for next-gen observatories with py-ananke
Adrien C. R. Thob, Robyn E. Sanderson, Andrew P. Eden, Farnik Nikakhtar, Nondh Panithanpaisal, Nicolás Garavito-Camargo and Sanjib Sharma Journal of Open Source Software 9(102) 6234 (2024) https://doi.org/10.21105/joss.06234
Exploring the ex-situ components within Gaia DR3
Zhuohan Li, Gang Zhao, Ruizhi Zhang, Xiang-Xiang Xue, Yuqin Chen and João A S Amarante Monthly Notices of the Royal Astronomical Society 527(4) 9767 (2023) https://doi.org/10.1093/mnras/stad3817
Robust clustering of the local Milky Way stellar kinematic substructures with Gaia eDR3
High-resolution Chemical Abundances of the Nyx Stream
Shuyu 书玉 Wang 汪, Lina Necib, Alexander P. Ji, Xiaowei Ou, Mariangela Lisanti, Mithi A. C. de los Reyes, Allison L. Strom and Mimi Truong The Astrophysical Journal 955(2) 129 (2023) https://doi.org/10.3847/1538-4357/acec4d
Machine learning for galactic archaeology: a chemistry-based neural network method for identification of accreted disc stars
Thorold Tronrud, Patricia B Tissera, Facundo A Gómez, et al. Monthly Notices of the Royal Astronomical Society 515(3) 3818 (2022) https://doi.org/10.1093/mnras/stac2027
The GALAH Survey: chemical tagging and chrono-chemodynamics of accreted halo stars with GALAH+ DR3 and Gaia eDR3
Sven Buder, Karin Lind, Melissa K Ness, et al. Monthly Notices of the Royal Astronomical Society 510(2) 2407 (2022) https://doi.org/10.1093/mnras/stab3504
Sensitivity estimation for dark matter subhalos in synthetic Gaia DR2 using deep learning
Reading the CARDs: The Imprint of Accretion History in the Chemical Abundances of the Milky Way's Stellar Halo
Emily C. Cunningham, Robyn E. Sanderson, Kathryn V. Johnston, Nondh Panithanpaisal, Melissa K. Ness, Andrew Wetzel, Sarah R. Loebman, Ivanna Escala, Danny Horta and Claude-André Faucher-Giguère The Astrophysical Journal 934(2) 172 (2022) https://doi.org/10.3847/1538-4357/ac78ea
The chemo-dynamical groups of Galactic globular clusters
Thomas M Callingham, Marius Cautun, Alis J Deason, et al. Monthly Notices of the Royal Astronomical Society 513(3) 4107 (2022) https://doi.org/10.1093/mnras/stac1145
3D gas-phase elemental abundances across the formation histories of Milky Way-mass galaxies in the FIRE simulations: initial conditions for chemical tagging
Matthew A Bellardini, Andrew Wetzel, Sarah R Loebman, et al. Monthly Notices of the Royal Astronomical Society 505(3) 4586 (2021) https://doi.org/10.1093/mnras/stab1606
The Milky Way, coming into focus: Precision astrometry probes its evolution and its dark matter
Using action space clustering to constrain the recent accretion history of Milky Way-like galaxies
Youjia Wu, Monica Valluri, Nondh Panithanpaisal, et al. Monthly Notices of the Royal Astronomical Society 509(4) 5882 (2021) https://doi.org/10.1093/mnras/stab3306
Searching for Dwarf Galaxies in Gaia DR2 Phase-space Data Using Wavelet Transforms
Chasing Accreted Structures within Gaia DR2 Using Deep Learning
Lina Necib, Bryan Ostdiek, Mariangela Lisanti, Timothy Cohen, Marat Freytsis and Shea Garrison-Kimmel The Astrophysical Journal 903(1) 25 (2020) https://doi.org/10.3847/1538-4357/abb814
Evidence from the H3 Survey That the Stellar Halo Is Entirely Comprised of Substructure
Rohan P. Naidu, Charlie Conroy, Ana Bonaca, Benjamin D. Johnson, Yuan-Sen 源森 Ting 丁, Nelson Caldwell, Dennis Zaritsky and Phillip A. Cargile The Astrophysical Journal 901(1) 48 (2020) https://doi.org/10.3847/1538-4357/abaef4