Abstract
The number of millisecond pulsars (MSPs) observed in Milky Way globular clusters has increased explosively in recent years, but the underlying population is still uncertain due to observational biases. We use state-of-the-art N-body simulations to study the evolution of MSP populations in dense star clusters. These cluster models span a wide range in initial conditions, including different initial masses, metallicities, and virial radii, which nearly cover the full range of properties exhibited by the population of globular clusters in the Milky Way. We demonstrate how different initial cluster properties affect the number of MSPs, for which we provide scaling relations as a function of cluster age and mass. As an application, we use our formulae to estimate the number of MSPs delivered to the Galactic center from inspiralling globular clusters to probe the origin of the Galactic-center gamma-ray excess detected by Fermi. We predict about 400 MSPs in the Galactic center from disrupted globular clusters, which can potentially explain most of the observed gamma-ray excess.
| Original language | English (US) |
|---|---|
| Article number | 162 |
| Journal | Astrophysical Journal |
| Volume | 940 |
| Issue number | 2 |
| DOIs | |
| State | Published - Dec 1 2022 |
Funding
We thank Fred Rasio, Kyle Kremer, Carl Rodriguez, and the anonymous referee for useful discussions and comments. This work was supported by NSF grants AST-1716762, AST-2108624 at Northwestern University, and by the Natural Sciences and Engineering Research Council of Canada (NSERC) DIS-2022-568580. G.F. acknowledges support from NASA grant 80NSSC21K1722. This research was supported in part through the computational resources and staff contributions provided for the Quest high performance computing facility at Northwestern University, which is jointly supported by the Office of the Provost, the Office for Research, and Northwestern University Information Technology.
ASJC Scopus subject areas
- Astronomy and Astrophysics
- Space and Planetary Science