Stars that Move Together Were Born Together

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 throughout the Galaxy, and their demographics can shed light on the clustered nature of star formation and the dynamical state of the disk. In previous work we presented a set of simulations of the Galactic disk that followed the clustered formation and dynamical evolution of 4 billion individual stars over the last 5 Gyr. The simulations predict that a high fraction of co-moving stars with physical and 3D velocity separation of $\Delta r < 20$ pc and $\Delta v < 1.5$ km s$^{-1}$ are co-natal. In this \textit{Letter}, we use \textit{Gaia} DR2 and LAMOST DR4 data to identify and study co-moving pairs. We find that the distribution of relative velocities and separations of pairs in the data is in good agreement with the predictions from the simulation. We identify 111 co-moving pairs in the Solar neighborhood with reliable astrometric and spectroscopic measurements. These pairs show a strong preference for having similar metallicities when compared to random field pairs. We therefore conclude that these pairs were very likely born together. The simulations predict that co-natal pairs originate preferentially from high-mass and relatively young ($< 1$ Gyr) star clusters. \textit{Gaia} will eventually deliver well-determined metallicities for the brightest stars, enabling the identification of thousands of co-natal pairs due to disrupting star clusters in the solar neighborhood.Comment: 6 pages, 4 figures, 1 table. Submitted to ApJL. Catalog here: http://harshilkamdar.github.io/2019/04/03/pairs.htm

A Dynamical Model for Clustered Star Formation in the Galactic Disk

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 kind has been mostly limited to bound clusters and moving groups. In this paper, we present a new dynamical model of the Galactic disk that takes into account the clustered nature of star formation. This model predicts that the combined phase and chemical space is rich in substructure and that this structure is sensitive to both the precise nature of clustered star formation and the large-scale properties of the Galaxy. The model self-consistently evolves 4 billion stars over the last 5 Gyr in a realistic potential that includes an axisymmetric component, a bar, spiral arms, and giant molecular clouds. All stars are born in clusters with an observationally motivated range of initial conditions. As direct N-body calculations for billions of stars are computationally infeasible, we have developed a method of initializing star cluster particles to mimic the effects of direct N-body effects, while the actual orbit integrations are treated as test particles within the analytic potential. We demonstrate that the combination of chemical and phase space information is much more effective at identifying truly conatal populations than either chemical or phase space alone. Furthermore, we show that comoving pairs of stars are very likely to be conatal if their velocity separation is <2 km s-1 and their metallicity separation is <0.05 dex. The results presented here bode well for harnessing the synergies between Gaia and spectroscopic surveys to reveal the assembly history of the Galactic disk.The computations in this paper were run on the Odyssey cluster, supported by the FAS Division of Science, Research Computing Group at Harvard University. H.M.K. acknowledges support from the DOE CSGF under grant No. DE-FG02- 97ER25308. C.C. acknowledges support from the Packard Foundation. Y.S.T. is supported by NASA Hubble Fellowship grant HST-HF2-51425.001 awarded by the Space Telescope Science Institute

Deep Potential: Recovering the Gravitational Potential from a Snapshot of Phase Space

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 distribution of matter—both baryonic and dark—throughout the galaxy. We present a novel method for determining the gravitational field from a snapshot of the phase-space positions of stars, based only on minimal physical assumptions, which makes use of recently developed tools from the field of deep learning. We first train a normalizing flow on a sample of observed six-dimensional phase-space coordinates of stars, obtaining a smooth, differentiable approximation of the distribution function. Using the collisionless Boltzmann equation, we then find the gravitational potential—represented by a feed-forward neural network—that renders this distribution function stationary. This method, which we term “Deep Potential,” is more flexible than previous parametric methods, which fit restricted classes of analytic models of the distribution function and potential to the data. We demonstrate Deep Potential on mock data sets and demonstrate its robustness under various nonideal conditions. Deep Potential is a promising approach to mapping the density of the Milky Way and other stellar systems, using rich data sets of stellar positions and kinematics now being provided by Gaia and ground-based spectroscopic surveys

Stars that Move Together Were Born Together

It is challenging to reliably identify stars that were born together outside of actively star-forming regions and bound stellar systems. However, conatal stars should be present throughout the Galaxy, and their demographics can shed light on the clustered nature of star formation and the dynamical state of the disk. In previous work we presented a set of simulations of the Galactic disk that followed the clustered formation and dynamical evolution of 4 billion individual stars over the last 5 Gyr. The simulations predict that a high fraction of comoving stars with physical and 3D velocity separation of Δr < 20 pc and Δv < 1.5 km s-1 are conatal. In this Letter, we use Gaia DR2 and LAMOST DR4 data to identify and study comoving pairs. We find that the distribution of relative velocities and separations of pairs in the data is in good agreement with the predictions from the simulation. We identify 111 comoving pairs in the solar neighborhood with reliable astrometric and spectroscopic measurements. These pairs show a strong preference for having similar metallicities when compared to random field pairs. We therefore conclude that these pairs were very likely born together. The simulations predict that conatal pairs are born in clusters that follow the overall cluster mass function and in relatively young (<1 Gyr) star clusters. Gaia will eventually deliver well-determined metallicities for the brightest stars, enabling the identification of thousands of conatal pairs due to disrupting star clusters in the solar neighborhood.Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement