Theory predicts that we should find fast, ejected (runaway) stars of all masses around dense, young star-forming regions. N-body simulations show that the number and distribution of these ejected stars could be used to constrain the initial spatial and kinematic substructure of the regions. We search for runaway and slower walkaway stars within 100 pc of the Orion Nebula Cluster (ONC) using Gaia DR2 astrometry and photometry. We compare our findings to predictions for the number and velocity distributions of runaway stars from simulations that we run for 4 Myr with initial conditions tailored to the ONC. In Gaia DR2, we find 31 runaway and 54 walkaway candidates based on proper motion, but not all of these are viable candidates in three dimensions. About 40 per cent are missing radial velocities, but we can trace back nine 3D runaways and 24 3D walkaways to the ONC, all of which are low/intermediate mass (<8 M⊙). Our simulations show that the number of runaways within 100 pc decreases the older a region is (as they quickly travel beyond this boundary), whereas the number of walkaways increases up to 3 Myr. We find fewer walkaways in Gaia DR2 than the maximum suggested from our simulations, which may be due to observational incompleteness. However, the number of Gaia DR2 runaways agrees with the number from our simulations during an age of ∼1.3–2.4 Myr, allowing us to confirm existing age estimates for the ONC (and potentially other star-forming regions) using runaway stars.
The Astropy Project supports and fosters the development of open-source and openly developed Python packages that provide commonly needed functionality to the astronomical community. A key element of the Astropy Project is the core package astropy, which serves as the foundation for more specialized projects and packages. In this article, we summarize key features in the core package as of the recent major release, version 5.0, and provide major updates on the Project. We then discuss supporting a broader ecosystem of interoperable packages, including connections with several astronomical observatories and missions. We also revisit the future outlook of the Astropy Project and the current status of Learn Astropy. We conclude by raising and discussing the current and future challenges facing the Project.
Stars with circumstellar disks may form in environments with high stellar and gas densities which affects the disks through processes like truncation from dynamical encounters, ram pressure stripping, and external photoevaporation. Circumstellar disks also undergo viscous evolution which leads to disk expansion. Previous work indicates that dynamical truncation and viscous evolution play a major role in determining circumstellar disk size and mass distributions. However, it remains unclear under what circumstances each of these two processes dominates. Here we present results of simulations of young stellar clusters taking viscous evolution and dynamical truncations into account. We model the embedded phase of the clusters by adding leftover gas as a background potential which can be present through the whole evolution of the cluster, or expelled after 1 Myr. We compare our simulation results to actual observations of disk sizes, disk masses, and accretion rates in star forming regions. We argue that the relative importance of dynamical truncations and the viscous evolution of the disks changes with time and cluster density. Viscous evolution causes the importance of dynamical encounters to increase in time, but the encounters cease soon after the expulsion of the leftover gas. For the clusters simulated in this work, viscous growth dominates the evolution of the disks.
For the purpose of studying internal kinematics of a star cluster it is often convenient to convert the astrometric parameters of its members into cluster-centered Cartesian coordinates. I provide a detailed and rigorous derivation of such a coordinate transformation and briefly compare it with a selection of published procedures from literature.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.