Better Galactic Mass Models through Chemistry

With the upcoming release of the Gaia catalog and the many multiplexed spectroscopic surveys on the horizon, we are rapidly moving into a new data-driven era in the study of the Milky Way’s stellar halo. When combined, these data sets will give us a many-dimensional view of stars in accreted structu...

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Main Authors: Robyn E. Sanderson, Andrew R. Wetzel, Sanjib Sharma, Philip F. Hopkins
Format: Article
Language:English
Published: MDPI AG 2017-08-01
Series:Galaxies
Subjects:
Online Access:https://www.mdpi.com/2075-4434/5/3/43
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author Robyn E. Sanderson
Andrew R. Wetzel
Sanjib Sharma
Philip F. Hopkins
author_facet Robyn E. Sanderson
Andrew R. Wetzel
Sanjib Sharma
Philip F. Hopkins
author_sort Robyn E. Sanderson
collection DOAJ
description With the upcoming release of the Gaia catalog and the many multiplexed spectroscopic surveys on the horizon, we are rapidly moving into a new data-driven era in the study of the Milky Way’s stellar halo. When combined, these data sets will give us a many-dimensional view of stars in accreted structures in the halo that includes both dynamical information about their orbits and chemical information about their formation histories. Using simulated data from the state-of-the-art Latte simulations of Milky-Way-like galaxies, which include hydrodynamics, feedback, and chemical evolution in a cosmological setting, we demonstrate that while dynamical information alone can be used to constrain models of the Galactic mass distribution in the halo, including the extra dimensions provided by chemical abundances can improve these constraints as well as assist in untangling different accreted components.
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spelling doaj.art-0c33eda419624cf190496325104254e72022-12-22T03:10:26ZengMDPI AGGalaxies2075-44342017-08-01534310.3390/galaxies5030043galaxies5030043Better Galactic Mass Models through ChemistryRobyn E. Sanderson0Andrew R. Wetzel1Sanjib Sharma2Philip F. Hopkins3TAPIR, California Institute of Technology, Pasadena, CA 91125, USATAPIR, California Institute of Technology, Pasadena, CA 91125, USASydney Institute for Astronomy, School of Physics, University of Sydney, Sydney NSW 2006, AustraliaTAPIR, California Institute of Technology, Pasadena, CA 91125, USAWith the upcoming release of the Gaia catalog and the many multiplexed spectroscopic surveys on the horizon, we are rapidly moving into a new data-driven era in the study of the Milky Way’s stellar halo. When combined, these data sets will give us a many-dimensional view of stars in accreted structures in the halo that includes both dynamical information about their orbits and chemical information about their formation histories. Using simulated data from the state-of-the-art Latte simulations of Milky-Way-like galaxies, which include hydrodynamics, feedback, and chemical evolution in a cosmological setting, we demonstrate that while dynamical information alone can be used to constrain models of the Galactic mass distribution in the halo, including the extra dimensions provided by chemical abundances can improve these constraints as well as assist in untangling different accreted components.https://www.mdpi.com/2075-4434/5/3/43galaxy: kinematics and dynamicsgalaxy: halogalaxy: abundancesgalaxy: structuregalaxy: formationcosmology: dark mattermethods: statisticalmethods: numerical
spellingShingle Robyn E. Sanderson
Andrew R. Wetzel
Sanjib Sharma
Philip F. Hopkins
Better Galactic Mass Models through Chemistry
Galaxies
galaxy: kinematics and dynamics
galaxy: halo
galaxy: abundances
galaxy: structure
galaxy: formation
cosmology: dark matter
methods: statistical
methods: numerical
title Better Galactic Mass Models through Chemistry
title_full Better Galactic Mass Models through Chemistry
title_fullStr Better Galactic Mass Models through Chemistry
title_full_unstemmed Better Galactic Mass Models through Chemistry
title_short Better Galactic Mass Models through Chemistry
title_sort better galactic mass models through chemistry
topic galaxy: kinematics and dynamics
galaxy: halo
galaxy: abundances
galaxy: structure
galaxy: formation
cosmology: dark matter
methods: statistical
methods: numerical
url https://www.mdpi.com/2075-4434/5/3/43
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AT andrewrwetzel bettergalacticmassmodelsthroughchemistry
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AT philipfhopkins bettergalacticmassmodelsthroughchemistry