Can I read Modeling Dense Star Clusters in the Milky Way and Beyond with the Cluster Monte Carlo Code on EtoBox?

Modeling Dense Star Clusters in the Milky Way and Beyond with the Cluster Monte Carlo Code by Rodriguez, Carl L.; Weatherford, Newlin C.; Coughlin, Scott C.; Seoane, Pau Amaro; Breivik, Katelyn; Chatterjee, Sourav; Fragione, Giacomo; Kıroğlu, Fulya; Kremer, Kyle; Rui, Nicholas Z.; Ye, Claire S.; Zevin, Michael; Rasio, Frederic A. is a scholarly article available to read on EtoBox.

What is Modeling Dense Star Clusters in the Milky Way and Beyond with the Cluster Monte Carlo Code about?

We describe the public release of the Cluster Monte Carlo Code (CMC) a parallel, star-by-star $N$-body code for modeling dense star clusters. CMC treats collisional stellar dynamics using H\'enon's method, where the cumulative effect of many two-body encounters is statistically reproduced as a single effective encounter between nearest-neighbor particles on a relaxation timescale. The star-by-star approach allows for the inclusion of additional physics, including strong gravitational three- and four-body encounters, two-body tidal and gravitational-wave captures, mass loss in arbitrary galactic tidal fields, and stellar evolution for both single and binary stars. The public release of CMC is pinned directly to the COSMIC population synthesis code, allowing dynamical star cluster simulations and population synthesis studies to be performed using identical assumptions about the stellar physics and initial conditions. As a demonstration, we present two examples of star cluster modeling: first, we perform the largest ($N = 10^8$) star-by-star $N$-body simulation of a Plummer sphere evolving to core collapse, reproducing the expected self-similar density profile over more than 15 orders

Author

Rodriguez, Carl L.; Weatherford, Newlin C.; Coughlin, Scott C.; Seoane, Pau Amaro; Breivik, Katelyn; Chatterjee, Sourav; Fragione, Giacomo; Kıroğlu, Fulya; Kremer, Kyle; Rui, Nicholas Z.; Ye, Claire S.; Zevin, Michael; Rasio, Frederic A.

Published

2021

Language

EN