60 citations · 263 across the 10 of their papers we have counts for
9 papers · 1 filter
Mapping the Milky Way in 5-D with 170 Million Stars
Joshua S. Speagle, Catherine Zucker, Ana Bonaca +18
We present "augustus", a catalog of distance, extinction, and stellar parameter estimates to 170 million stars from and with dr…
Deep Potential: Recovering the gravitational potential from a snapshot of phase space
Gregory M. Green, Yuan-Sen Ting, Harshil Kamdar
One of the major goals of the field of Milky Way dynamics is to recover the gravitational potential field. Mapping the potential would allow us to determine the spatial distributio…
Stellar Streams in the Galactic Disk: Predicted Lifetimes and Their Utility in Measuring the Galactic Potential
Harshil Kamdar, Charlie Conroy, Yuan-Sen Ting
In this paper, we present a holistic view of the detection, characterization, and origin of stellar streams in the disk of a simulated Milky Way-like galaxy. The star-by-star simul…
Deep Potential: Recovering the gravitational potential from a snapshot of phase space
Gregory M. Green, Yuan-Sen Ting
One of the major goals of the field of Milky Way dynamics is to recover the gravitational potential field. Mapping the potential would allow us to determine the spatial distributio…
Spatial and Kinematic Clustering of Stars in the Galactic Disk
Harshil Kamdar, Charlie Conroy, Yuan-Sen Ting +1
The Galactic disk is expected to be spatially, kinematically, and chemically clustered on many scales due to both star formation and non-axisymmetries in the Galactic potential. In…
Stars that Move Together Were Born Together
Harshil Kamdar, Charlie Conroy, Yuan-Sen Ting +3
It is challenging to reliably identify stars that were born together outside of actively star-forming regions and bound stellar systems. However, co-natal stars should be present t…
A Dynamical Model for Clustered Star Formation in the Galactic Disk
Harshil Kamdar, Charlie Conroy, Yuan-Sen Ting +3
The clustered nature of star formation should produce a high degree of structure in the combined phase and chemical space in the Galactic disk. To date, observed structure of this…
Machine Learning and Cosmological Simulations I: Semi-Analytical Models
Harshil M. Kamdar, Matthew J. Turk, Robert J. Brunner
We present a new exploratory framework to model galaxy formation and evolution in a hierarchical universe by using machine learning (ML). Our motivations are two-fold: (1) presenti…
Machine Learning and Cosmological Simulations II: Hydrodynamical Simulations
Harshil M. Kamdar, Matthew J. Turk, Robert J. Brunner
We extend a machine learning (ML) framework presented previously to model galaxy formation and evolution in a hierarchical universe using N-body + hydrodynamical simulations. In th…