12 citations · 27 across the 5 of their papers we have counts for
6 papers
The Impact of Simulation Resolution on Dwarf Galaxy Stellar Stream Populations in FIRE
Yasmine J. Meziani, Nondh Panithanpaisal, Robyn E. Sanderson +4
Cosmological simulations allow us to study galaxy-progenitor stream populations, allowing comparisons with observations to constrain galaxy formation physics. Previous work found t…
Baryon-Accelerated Core Collapse in SIDM Halos and its Imprint on Galactic Disks
Zeineb Mezghanni, Elliot Y. Davies, Adriana Dropulic +3
The gravitational coupling between dark matter (DM) halos and the baryonic structures they host is one of the most powerful windows into the particle nature of DM. Self-interacting…
StreamGen: Connecting Populations of Streams and Shells to Their Host Galaxies
Adriana Dropulic, Nora Shipp, Stacy Kim +3
In this work, we study how the abundance and dynamics of populations of disrupting satellite galaxies change systematically as a function of host galaxy properties. We apply a theo…
Efficient and accurate force replay in cosmological-baryonic simulations
Arpit Arora, Robyn Sanderson, Christopher Regan +8
We construct time-evolving gravitational potential models for a Milky Way-mass galaxy from the FIRE-2 suite of cosmological-baryonic simulations using basis function expansions. Th…
Revealing the Milky Way's Most Recent Major Merger with a Gaia EDR3 Catalog of Machine-Learned Line-of-Sight Velocities
Adriana Dropulic, Hongwan Liu, Bryan Ostdiek +1
Machine learning can play a powerful role in inferring missing line-of-sight velocities from astrometry in surveys such as Gaia. In this paper, we apply a neural network to Gaia Ea…
Machine Learning the 6th Dimension: Stellar Radial Velocities from 5D Phase-Space Correlations
Adriana Dropulic, Bryan Ostdiek, Laura J. Chang +3
The Gaia satellite will observe the positions and velocities of over a billion Milky Way stars. In the early data releases, the majority of observed stars do not have complete 6D p…